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Key Takeaways Predictive maintenance market growing from $10.93B (2024) to $70.73B (2032) at 26.5% CAGR 95% of adopters report positive ROI, with 27% achieving full amortization within one year Organizations achieve 25-30% maintenance cost reduction and 35-50% downtime reduction 10x return on investment possible with comprehensive CMMS implementation The global predictive maintenance market is experiencing unprecedented growth, reaching $10.93 billion in 2024 and projected to surge to $70.73 billion by 2032 at a compound annual growth rate of 26.5%. This expansion is a fundamental shift in how organizations approach equipment management, moving from reactive firefighting to intelligent, data-driven maintenance strategies. What is even more amazing is that 95% of predictive maintenance adopters report positive ROI, with 27% achieving full amortization within just one year, according to recent industry studies. Illustration: WorkTrek / Data: itefy For maintenance organizations, the stakes couldn't be higher. On average, industrial manufacturers lose $50 billion annually to unplanned downtime, with median costs exceeding $125,000 per hour across industries. In semiconductor manufacturing, each hour of unexpected downtime costs over $1 million. Given these staggering statistics, it is clear that traditional maintenance methods cannot compete with the precision and efficiency of modern predictive maintenance solutions that can reduce maintenance costs by 25-30% while cutting unplanned downtime by 35-50%. As we look toward 2025 and beyond, eight transformative trends we are covering in this article are reshaping the predictive maintenance landscape. 1. Artificial intelligence (AI) AI is dominating the news. AI, built on machine learning algorithms, has reached a tipping point for the maintenance industry. Based on a recent study, AI-driven predictive analytics can increase failure prediction accuracy up to 90% while reducing maintenance costs by 12%. Illustration: WorkTrek / Data: InsightAce Analytics Modern machine learning algorithms can quickly analyze large quantities of sensor data, historical maintenance records, and operational parameters. Using this data, these models can identify patterns invisible to human operators. Companies have already started implementing AI-powered predictive maintenance solutions. Recent reports show dramatic improvements in operational performance. Industry Studies One example is Rolls-Royce. Using AI-powered predictive analytics, they managed to cut costs by 30%. Another study shows that data centers utilizing neural networks achieved a 30% reduction in false alarms and 40% increase in detection accuracy. The AI systems are designed not only to process data, but also to learn from it continuously. This helps improve future failures. Technology Behind Predictive Maintenance What powers predictive maintenance and the technology behind it revolves around advanced machine learning algorithms, particularly Long Short-Term Memory (LSTM) deep learning networks. Illustration: WorkTrek / Data: Research Gate This new approach can significantly enhance the accuracy of predictive maintenance compared to traditional statistical methods. One recent study shows that these systems are smart enough to predict equipment failures with weeks of advance notice. This enables maintenance teams to plan interventions during scheduled downtime, rather than responding to emergency breakdowns. What makes AI particularly powerful in predictive maintenance is its ability to identify subtle correlations across multiple data points that would otherwise go unnoticed. By analyzing vibration patterns, temperature fluctuations, energy consumption, and dozens of other variables simultaneously, AI systems create comprehensive equipment health profiles that enable unprecedented predictive insights. 2. Internet of Things (IoT) IoT is transforming how organizations monitor their physical assets. The technology is projected to go through explosive growth. That expansion is currently projected at a 28% compound annual growth rate according to a recent study by Prom Wad Electronics Design. Illustration: WorkTrek / Data: IoT Mag Modern facilities now deploy thousands of sensors across their equipment. This helps create a comprehensive monitoring networks that provide 24/7 visibility into asset health and performance. What can IoT track? What are some of the IoT devices that can be used in predictive maintenance? The list of devices includes: Temperature Sensors Vibration Monitoring Sensors Acoustic & Ultrasonic Sensors Pressure Monitors Electrical & Power Monitoring Devices Pressure and Flow Sensors Oil and Lubrication Sensors Depending on the type of equipment you are tracking, either some or all of these devices can help improve predictive maintenance. Benefits to Maintenance Organizations According to a recent study by Deloitte, companies adopting sensor-driven predictive maintenance reduce unplanned downtime by up to 25%. This was accomplished by eliminating the need for time-consuming manual inspections, thereby saving a significant number of labor hours. These systems can instantly detect anomalies that indicate impending failures, triggering automated alerts and work orders. ThyssenKrupp improved elevator service reliability by 50% through IoT-connected predictive maintenance. What this demonstrates is that IoT can enhance both operational efficiency and customer satisfaction. Wind turbine operators are achieving even more dramatic results, with some companies saving $200,000 per turbine annually through IoT-enabled condition monitoring that predicts component failures before they cause catastrophic damage. This level of sophistication of modern IoT sensors can greatly extend what is achievable via simple threshold monitoring. 3. Digital Twins Digital twin is an emerging technology that has the potential to transform predictive maintenance. What exactly is a digital twin? Think of it as a digital replica of a physical asset. This enables maintenance teams to perform simulation, testing, and optimization without disrupting actual operations. Benefits of Digital Twins Several industries have started to implement digital twins. That's mainly because organizations can garner significant cost savings using them. Illustration: WorkTrek / Data: Anvil Labs GE Digital estimates digital twins could cut equipment downtime by 30%. This can represent millions in potential savings for asset-intensive organizations. By using real-time data, these virtual models mirror the exact conditions of their physical counterparts. This enables maintenance teams to simulate various scenarios and predict the impact of different maintenance strategies. One industry that has adopted digital twins is the petrochemical industry. Aircraft manufacturers have also started to utilize this technology. Both industries have implemented digital twins to improve the performance of monitoring and maintenance planning. Power of Digital Twins One of the powers of a digital twin strategy lies in its ability to combine historical data, real-time sensor information, and predictive modeling into comprehensive asset management platforms. For instance, COMPREDICT partnered with Renault Group to develop virtual sensor-based predictive maintenance systems. These systems can predict component failures without physical sensors, dramatically reducing monitoring costs while maintaining prediction accuracy. Source: WorkTrek Digital twins also enable advanced data analysis optimization techniques that were previously considered impossible. For example, maintenance teams can test different replacement schedules, compare various maintenance approaches, and identify optimal timing for interventions within the virtual environment. These tests can be accomplished without affecting production systems or slowing down production. 4. Edge Computing Cloud computing has been the primary driver of technological progress over the past decade. However, there are downsides to cloud computing when it comes to managing physical assets or IoT devices. Enter edge computing. This approach is a fundamental change in how predictive maintenance systems process and respond to equipment data. Instead of communicating with the cloud system, edge computing moves that computing power to the equipment level. Edge computing can significantly accelerate anomaly detection while minimizing network latency. This approach not only reduces overall bandwidth and cloud costs but also has the potential to reduce response times for critical maintenance decisions. Illustration: WorkTrek / Data: itweb IDC predicts 50% of enterprise data will be processed at the edge by 2025, driven primarily by the need for instantaneous responses in industrial environments. One example is manufacturing facilities that are implementing edge computing solutions that can analyze vibration patterns locally and trigger immediate equipment shutdowns when dangerous conditions are detected. Analyzing this data at the edge can drastically improve response times. Ideal Environments for Edge Computing Edge computing offers particular advantages in environments with limited connectivity or where latency is critical. For example, remote mining operations utilize edge computing for autonomous equipment monitoring. These are areas where connectivity is limited or expensive to implement. Another industry utilizing edge computing is healthcare. Critical assets, such as monitoring and imaging equipment, can generate huge volumes of data. Instead of transferring this data to cloud systems, healthcare companies can perform immediate analysis. One primary reason to implement edge computing is data security. Healthcare data is highly sensitive and heavily regulated by laws like HIPAA. Keeping data closer to the source reduces exposure and helps maintain data sovereignty. Real Time Insight Since the data collection and analysis are local, edge computing enables more sophisticated predictive maintenance algorithms to provide real-time insight. AI and machine learning algorithms can access this data quickly without network latency. Some advanced systems can provide alerts and prevent failures within seconds or minutes of detection, which can give you improved operational efficiency. For any high-speed manufacturing process, where delays can cause significant production loss, this capability is essential. A recent study shows that by 2025, nearly 50% of enterprise-generated data will be processed at the edge. 5. Augmented and Virtual Reality Augmented and virtual reality technologies are transforming how maintenance teams work. These technologies can be used to help with training and learning how to perform complex procedures. ABI Research reports AR adoption in industrial maintenance increasing 66% annually until 2025, with IDC projecting $4.1 billion investment in AR/VR for industrial maintenance by 2024 Illustration: WorkTrek / Data: Field Circle The main benefit of AR is that it provides maintenance technicians with hands-free access to real-time equipment data, interactive repair guides, and remote expert assistance. Technicians wearing AR glasses can view IoT sensor data overlaid directly onto equipment, receive step-by-step maintenance procedures, and collaborate with experts located anywhere in the world (https://www.interal.com/en/iot-cmms/). This technology is particularly valuable for complex procedures on critical equipment where precision is essential. Virtual Training Virtual reality creates risk-free training environments. This allows technicians to practice complex maintenance scenarios without expensive equipment or safety concerns. One example is in the aircraft industry, where maintenance teams use VR simulations to train on emergency procedures and dangerous maintenance tasks. This type of training typically requires extensive practice before being applied in real-world situations. Benefits of AR for Predictive Maintenance With AR and VR, maintenance teams can create predictive maintenance systems that provide technicians with predictive insights, training, and execution guidance through integrated platforms. This approach can significantly improve maintenance quality while reducing the time required to train new technicians on complex equipment. 6. Autonomous Maintenance Systems Imagine a world where failing equipment fixed itself. That's where autonomous maintenance systems come in. They represent the next evolution in predictive maintenance, where AI-powered equipment can monitor itself, diagnose problems, and perform basic repairs without human intervention. How does it work? These self-healing systems combine predictive analytics with automated responses to prevent equipment failures before they occur. Systems can automatically adjust operating parameters when sensors detect conditions that could lead to equipment damage. For example, motors can automatically reduce their load when temperature sensors indicate overheating. HVAC systems can also adjust their operation based on performance data to prevent component wear. The main benefit: these systems operate 24/7 without human oversight, while providing continuous protection for critical equipment. Additional benefits Autonomous maintenance is not only used for fixing equipment. It can be extended beyond simple parameter adjustments to include autonomous maintenance scheduling and parts ordering. Some advanced systems can predict when components will need replacement, automatically generate work orders, and even order replacement parts from suppliers based on predictive algorithms. 7. 5G Connectivity Traditionally, connectivity has been a barrier to deploying predictive maintenance. With the wide deployment of 5G connectivity, that barrier has been reduced. 5G networks now cover 51% of the world population with ultra-low latency and massive device connectivity capabilities essential for comprehensive predictive maintenance systems. Benefits of 5G Connectivity Manufacturing facilities can now connect thousands of sensors through 5G networks without bandwidth limitations. This creates a comprehensive monitoring ecosystem that was previously impossible. Illustration: WorkTrek / Data: Market.us The technology can also support millions of connected devices per square kilometer while maintaining the ultra-low latency required for real-time maintenance responses. One area of maintenance that benefits from 5G connectivity is remote operations. Industries such as mining, offshore oil exploration, and construction have been demanding to monitor remotely. With 5G technology, organizations can easily create remote monitoring staging, which can reduce travel costs. Industry Example One example is the use of 5G in mining operations for monitoring autonomous equipment. These facilities leverage the technology for continuous asset monitoring and remote maintenance support. This is one of the ways that the oil and gas industry is cutting back on maintenance costs and reducing injury. Ericsson has successfully enabled predictive maintenance applications through 5G cellular networks. This approach demonstrates the technology's ability to support industrial applications with mission-critical reliability requirements. With 5G's communication capabilities, organizations can enable more sophisticated maintenance collaboration. This is enabled by allowing remote experts to assist field technicians through high-quality video connections and augmented reality applications. 8. Sustainability and Green Maintenance Practices Environmental considerations are becoming central to predictive maintenance strategies as organizations seek to minimize their carbon footprint while reducing operational costs. Illustration: WorkTrek / Data: Eptura Based on recent studies, companies implementing energy efficiency improvements through predictive maintenance see average cost savings of 15%. This is accomplished while simultaneously reducing their environmental impact. Reduce Equipment Energy Use Green maintenance practices make minimizing energy consumption a focal point of maintenance strategy. Aside from reducing energy consumption, green energy practices can minimize costs, extend asset lifespan, and reduce waste. One approach is to implement smart energy management systems that integrate with predictive maintenance platforms. These systems can identify opportunities for efficiency improvements while maintaining optimal equipment performance. Another benefit is that predictive maintenance supports sustainability goals by preventing catastrophic failures that often result in significant environmental damage and waste. How does it work? By predicting and preventing equipment failures, organizations avoid emergency repairs that typically require extensive resource consumption and generate significant waste. Additionally, the technology enables more precise maintenance timing, minimizing the need for replacement parts and consumables. Renewable energy integration is becoming standard in maintenance facilities, with solar panels and energy storage systems supporting maintenance operations while reducing carbon footprints. Organizations are also implementing carbon footprint tracking within their maintenance management systems. This enables them to quantify and optimize the environmental impact of their maintenance activities. How CMMS powers Predictive Maintenance It will be nearly impossible to implement a preventive maintenance program without a modern Computerized Maintenance Management System like WorkTrek. CMMS is the foundation for successful predictive maintenance implementations, providing the integration, automation, and analytics capabilities necessary to transform sensor data into actionable maintenance insights. One study showed that organizations implementing CMMS-enabled predictive maintenance achieve up to 40% cost reduction and 75% equipment downtime reduction. Illustration: WorkTrek / Data: eMaint CMMS platforms excel at integrating diverse data sources, from IoT sensors and monitoring systems. This system can then store and analyze this data to provide a unified asset management ecosystem. These systems can connect and automatically collect real-time sensor data, analyze trends and patterns, and generate predictive alerts when equipment conditions indicate potential failures. With its comprehensive approach to maintenance management, WorkTrek CMMSstands out as an ideal predictive maintenance solution. With a high-performance cloud-based architecture, WorkTrek provides the scalability necessary for large-scale IoT. This is done while maintaining the reliability required for mission-critical maintenance operations. WorkTrek's mobile application ensures that maintenance teams can access predictive insights anywhere. This enables immediate responses to equipment alerts and optimized maintenance scheduling. The platform's API connectivity enables seamless integration with IoT devices and monitoring systems. Additionally, WorkTrek's analytics and reporting capabilities put the necessary predictive maintenance data at your fingertips. Organizations can track key performance indicators, including downtime reduction, maintenance cost savings, and asset availability improvements, through comprehensive dashboards designed for both operational and executive audiences. Business reasons to adopt predictive maintenance If you are a maintenance manager, how do you make the business case for predictive maintenance? Improved Equipment UpTime You can start by looking at industry statistics. For example, companies report 10-20% increase in equipment uptime and availability. This is alongside a significant reduction in emergency maintenance situations and unplanned production interruptions. Optimized Resource Utilization With predictive maintenance, teams benefit from more efficient resource utilization. A recent study shows a 20-50% reduction in maintenance planning time. This is accomplished by increasing maintenance technician productivity through optimized maintenance schedules. Reduce Spare Parts Cost Predictive insights enable just-in-time maintenance approaches that minimize inventory carrying costs. Due to its predictive capabilities, you only get parts when they are needed rather than storing them in your storage room. Using demand forecasting, organizations report 5-10% inventory cost reduction through improved demand forecasting and optimized parts management. Improved Quality and Improved Safety Quality improvements represent another significant benefit. Some manufacturers report achieving 33% reduction in quality defects through predictive maintenance programs. With predictive maintenance, organizations can improve safety by identifying potential hazards early. Financial Impact The financial impact extends beyond direct maintenance savings. It includes improved customer satisfaction and enhanced brand reputation. Organizations implementing predictive maintenance position themselves as industry leaders while building the operational excellence necessary for long-term success in increasingly competitive markets. Conclusion The eight trends shaping the future of predictive maintenance are a fundamental transformation in how organizations manage their physical assets and optimize their maintenance operations. From AI-driven analytics that predict failures with unprecedented accuracy to autonomous systems that can heal themselves, these technologies are creating opportunities for operational excellence that were unimaginable just a few years ago. Illustration: WorkTrek / Data: Grand View Research The statistics speak for themselves: 95% positive ROI adoption rates, 10x returns on investment 25-50% reductions in downtime and maintenance costs Organizations that embrace these trends will be industry leaders. On the other hand, if you delay adoption of predictive maintenance, you risk falling behind competitors who have already realized the transformative benefits of modern predictive maintenance solutions. By implementing these eight trends through comprehensive platforms like WorkTrek, maintenance teams can transform their operations, reduce costs, and improve reliability. All of this helps build the foundation for sustained operational excellence in an increasingly competitive global marketplace.

Key takeaways: In the U.S., control system maintenance includes ensuring compliance with the National Electrical Code. Maintenance must follow strict OSHA requirements for Lockout/Tagout and PPE procedures. Elevator load tests are typically performed at 125% of rated load capacity. How confident are you in your team’s elevator maintenance routine? After all, these complex machines require consistent, detailed attention to stay safe and reliable for daily use. If you’re looking for a clear, organized way to structure your maintenance efforts, read on. In the following sections, we will provide a step-by-step checklist that covers every critical inspection point, helping you ensure safety and operational efficiency without missing a step. Machine Room The elevator's machine room houses key equipment, so keeping it in perfect condition is a top priority. For starters, this space must be kept clean and free of any dust or clutter. It should never be used as a storage closet for unrelated items, as this can create fire hazards and obstruct maintenance personnel's access. The image below shows exactly what you want to avoid. Source: Colley Elevator Beyond general cleanliness, it's crucial to inspect the main equipment. Check that the motor, controller, and drive units have proper ventilation and show no signs of overheating. Also, look carefully for fluid leaks around the machinery. A thorough visual inspection will help you confirm that all these critical components are in good working order and are not at risk of failing unexpectedly. Additionally, verify that lighting is adequate, access doors are secure, and that all safety signage is visible and up to date. These small details contribute to a safer working environment. Plus, a clean, well-kept machine room also reduces the risk of control system issues. Control System On that note, carefully inspecting the control system and its components may be the most important item on this checklist. Teams need to carefully examine every fuse, relay, and contactor for wear, corrosion, or damage. Wiring should be neatly routed and securely fastened to prevent accidental shorts or interference with moving parts. Also, look closely at circuit boards and components for burn marks or discoloration, as these can indicate electrical stress or a failing component. As Master Electrician David Herres explains, compliance with the National Electrical Code (NEC) standards is essential during this stage in the maintenance process. Illustration: WorkTrek / Quote: JADE Learning Proper grounding, wire sizing, and circuit protection are essential for safety and are legal requirements directly impacting liability. Once visual inspections are complete, the crew should perform continuity tests on safety relays and simulate fault conditions to confirm circuit integrity. This includes checking door interlocks, emergency stop circuits, and limit switches to ensure they trigger appropriate responses. This detailed check ensures the elevator responds correctly to commands and that all safety circuits are functioning as they should. Hoistway (Shaft) The hoistway is the next most important item on this checklist after the control system, as issues here can cause entrapment, fire risk, or even elevator derailment. Listed below are some of the essential maintenance aspects to consider: Source: WorkTrek During inspection, carefully check the guide rails for proper alignment and lubrication, and any signs of wear. Similarly, inspect the counterweights and their guide shoes for any damage. Cracks, chips, or loose fittings can compromise the elevator’s balance and braking performance. Also, the hoistway must be completely clear at all times, so look for any debris or obstructions that could interfere with the elevator's movement. You should also inspect all the elevator ropes, including the governor's rope, to ensure these overspeed protection devices are in excellent working order. Fraying, corrosion, or slack in this rope can prevent the system from activating during a free-fall scenario. Finally, other safety systems, including the limit switches and gear, should be tested under expert supervision and following strict safety protocols. Elevator Pit The elevator pit, located at the bottom of the hoistway, requires regular attention to prevent long-term problems. The most important first step is to ensure the pit is clean and dry. Standing water, oil residue, or accumulated debris can accelerate corrosion and compromise the integrity of mechanical components over time. In case of unforeseen circumstances, like the pit flooding faced by this Reddit commenter, action must be taken immediately to prevent rust and equipment failure. Source: Reddit While the maintenance crew is in the pit, they should inspect the buffers—whether they are spring or oil-based—for any signs of wear or damage. The pit ladder should also be checked to ensure it is stable, clean, and safe, to prevent safety issues during regular maintenance or emergencies. Along with the ladder, confirm that the entire pit has proper lighting and that any Ground Fault Circuit Interrupter (GFCI) outlets are functioning correctly, as these are crucial safety features for maintenance personnel. Car Top Inspecting the top of the elevator car is a critical part of any thorough maintenance routine, as some key operational components are located here. The image below provides a clear view of the different parts that will need to be examined. Source: Schmelevator Start by checking that the inspection station is fully functional—verifying that all switches, buttons, and indicator lights respond correctly. Pay close attention to the power and communication cables, which supply power and communication to the car. Look for any signs of wear, fraying, or kinking, and ensure they are properly suspended and not rubbing against any part of the hoistway. To complete the inspection, the emergency exit hatch and its light should be tested to ensure they work correctly, and the car’s ventilation fan should be verified as operational. Inside the Elevator Car The interior of the elevator car is where passengers interact directly with the system, so ensuring everything works perfectly is essential for their safety and comfort. The control panel requires the most careful inspection, as shown in the image below. Source: Worktrek Focus on the essentials, such as testing the emergency call button or phone for clear intercom connections and ringing the alarm bell. Next, the buttons controlling the door's operation and the floor number buttons are checked to ensure they work as they should, and to check for wear on accessibility features like the Braille notations. Beyond these items, you should verify that the elevator car works smoothly and levels accurately with the floor, as even small misalignments can be a trip hazard. So, listen for odd vibrations during travel and verify proper leveling at each landing. Hall Stations and Doors on Each Floor Elevator maintenance extends beyond the elevator car to every floor the elevator serves. So, maintenance teams need to inspect the hall stations and doors to ensure a seamless user experience. At each landing, check that the call buttons are responsive and light up when pressed. Door tracks and sills should be clean and clear of debris, as small objects can easily cause the doors to jam or become misaligned. Finally, test the door reopening devices, such as the electronic sensors or safety edges, to ensure they correctly detect obstructions and prevent the doors from closing. Operational & Safety Tests We've mentioned various safety checks throughout this guide, but this area is so important that it deserves its focus. For starters, you need to ensure the elevator can operate at its full rated capacity without any issues like slipping or stalling. This is confirmed through a load test—typically performed annually or as required by local safety codes—which, according to multiple sources, should use 25% more weight than the elevator's maximum rated load. Illustration: WorkTrek / Data: Stanley Elevator During this test, you are looking for any signs of slipping, stalling, or unusual strain on the motor and brakes. Next, a detailed inspection of the brake system is crucial, covering its mechanical and electrical components. Source: WorkTrek As a crucial safety mechanism, you need to ensure the brake engages smoothly and holds the car firmly in place without any drift or hesitation. On a related note, you must also test the emergency power system to ensure the elevator can safely operate and reach a floor during a power outage. A final, critical step is to perform a fire service recall test, but only if your maintenance crew is trained and authorized to do so. Documentation Proper documentation is an often-overlooked aspect of maintenance operations. However, having teams track their maintenance efforts is an important step that should be performed continuously during every other step on our checklist. At a minimum, logs should always include the following entries: Inspection dates A description of all tasks performed A list of any parts that were replaced Notes on any issues or problems that were found The name or signature of the technician who did the work Trying to manage all of this with pen and paper can be tough, and it's easy for details to get lost, which can lead to overlooked repairs or worse, compromise the safety of the entire elevator system. This is where a modern tool can help. Using a computerized maintenance management software (CMMS) like WorkTrek makes logging everything much simpler. Source: WorkTrek For instance, technicians can update tasks directly from their phones and attach photos of a problem to the work order. The system also sends out automatic reminders for upcoming maintenance, so you never have to worry about forgetting an inspection. Best of all, every piece of information is stored in one central place, making it easy to pull up records for an audit and ensuring no task is ever overlooked. Ultimately, solid elevator maintenance documentation keeps your team accountable and helps improve future operations. Bonus Tips for Maintenance Techs To round out our guide, here are some important bonus tips that every maintenance manager should keep in mind. First and foremost is ensuring the personal safety of your crew. This means directly enforcing the strict safety procedures outlined by the Occupational Safety and Health Administration (OSHA). As noted in this article by the National Elevator Industry Educational Program (NEIEP): "OSHA holds companies accountable for providing safe working conditions by setting and enforcing standards to ensure workplaces are free from serious recognized hazards." One of these standards includes ensuring teams follow proper lockout/tagout (LOTO) procedures before starting any work on electrical components. It is also critical for teams to wear the required Personal Protective Equipment (PPE) at all times, including gloves, a helmet, safety glasses, and non-slip shoes. In addition, fall protection gear is essential for shaft and top-of-car work to prevent deadly falls. Beyond personal safety, all personnel should be properly trained and certified according to industry standards like ASME A17.1/CSA B44 and be informed on resources like the ASME A17.2 inspection guide. Source: ASME Beyond these general standards, it is your responsibility to ensure your team always consults and adheres to the specific manufacturer’s guidelines for every elevator model. This is best achieved by maintaining an accessible digital or physical library of all relevant service manuals. You can further integrate these requirements by incorporating model-specific tasks directly into your maintenance checklists or CMMS work orders, ensuring technicians review them before beginning any job. Ultimately, this dual focus on safety and technical compliance will take the success and reliability of your maintenance operations even further. Conclusion With this clear maintenance checklist in hand, preferably digitized and easy to use, elevator care becomes much more straightforward. As you integrate these checks into your daily, weekly, and yearly maintenance routines, you’ll catch minor issues before they turn into big headaches. This steady approach—supported by maintenance management tools—will extend the lifespan of your clients’ elevators and maximize your team’s efforts.

Key Takeaways Preventive maintenance uses scheduled intervals while predictive maintenance relies on real-time equipment condition data Preventive maintenance works best for simple equipment and predictive maintenance suits critical or high-value assets Most companies benefit from combining both strategies rather than choosing just one approach Equipment maintenance keeps businesses running, but choosing the wrong approach can waste resources. Many companies struggle to decide between fixing things on a schedule or waiting for data to tell them when maintenance is needed. This is where predictive and preventive maintenance come in. The main difference is that Preventive maintenance follows fixed schedules based on time or usage. In contrast, predictive maintenance uses real-time data and sensors to determine when equipment actually needs attention. Illustration: WorkTrek / Data: EasyMaint This difference affects everything from maintenance costs to the equipment lifespan. Understanding Preventive and Predictive Maintenance Both preventive and predictive maintenance strategies are proactive maintenance strategies. They are designed to help organizations prevent equipment from breaking down. The key difference lies in timing and data usage for scheduling maintenance activities. Definition of Preventive Maintenance Preventive maintenance uses regular schedules to maintain equipment at set intervals. This maintenance strategy follows a set of predetermined timeframes. That could be either calendar dates, usage hours, or historical data. There are three major types of preventive maintenance: Usage-based maintenance - Schedules work based on equipment usage metrics Time-based maintenance - Sets specific calendar intervals for maintenance tasks Condition-based maintenance - Plans work around asset wear patterns Maintenance technicians use checklists during preventive maintenance visits. Source: WorkTrek These lists can include: Cleaning Adjustments Part replacements Inspections One good practice is to minimize unplanned downtime and schedule routine maintenance in advance. At times, preventive maintenance can lead to over-maintenance or under-maintenance. This can result in increased labor and material costs. For example, equipment might receive service when it is not needed, or problems might develop between scheduled visits. Definition of Predictive Maintenance Predictive maintenance, on the other hand, utilizes real-time data to monitor asset conditions and forecast when equipment is likely to fail. This is done by using sensors that continuously collect information about machine performance. Predictive maintenance also uses a number of advanced technologies. They include: Artificial intelligence analyzes patterns in equipment data Machine learning algorithms predict future failures Internet of Things (IoT) sensors monitor equipment conditions Enterprise asset management software processes maintenance data Illustration: WorkTrek / Data: Business Insider There are also various monitoring techniques to identify equipment problems before they cause failures. One example is temperature sensors that can detect overheating components. Another example is vibration analysis that can automatically identify misaligned parts. Sound monitoring is designed to pick up unusual noises that humans cannot hear. Oil analysis can reveal contamination or degradation in lubricants. The good news is that one recent study shows that predictive maintenance can reduce downtime by 35-50% compared to other maintenance strategies. Predictive maintenance can also increase equipment lifespan by 20-40%. Overview of Maintenance Strategies One approach that is popular with a number of maintenance organizations is combining multiple maintenance strategies. The choice depends on the importance of the asset, replacement costs, and the impact of failure. Reactive maintenance works best for equipment with predictable failure patterns. It suits assets where downtime impact remains relatively low. Illustration: WorkTrek / Data: Oxmaint Predictive maintenance benefits high-value, critical equipment. The strategy requires substantial data collection and modern infrastructure to implement effectively. Before choosing either of the strategies, consider training requirements. Predictive maintenance is more complex and demands specialized skills for data interpretation and system management. Also, consider your budget constraints. In the short term, preventive maintenance can cost less to implement than predictive systems. Key Differences Between Preventive and Predictive Maintenance So, what you might be asking is the main difference? Preventive and predictive maintenance differ primarily in how they schedule work, utilize technology, and trigger maintenance actions. Scheduling Methods Preventive maintenance is a maintenance practice that follows a fixed schedule based on calendar dates or usage hours. Maintenance teams perform tasks every 30 days, 90 days, or after specific operating hours, regardless of equipment condition. Source: WorkTrek This approach treats all equipment uniformly. For example, a bearing gets lubricated every month whether it needs it or not. An air filter gets replaced every quarter, even if it's still clean. Predictive maintenance scheduling depends entirely on equipment condition rather than predetermined intervals. Work orders are generated only when data shows potential problems. Maintenance planning can be more flexible with predictive methods. Teams can focus their time on equipment that actually needs work instead of following rigid schedules. Technology and Data Requirements Preventive maintenance requires basic tools like calendars, checklists, and simple tracking systems. Most organizations can implement preventive programs with existing resources and minimal technology investment. While teams typically use spreadsheets or basic maintenance software to track when tasks were completed, implementing a full-featured CMMS like WorkTrek can streamline the process. Source: WorkTrek Predictive maintenance also works in conjunction with a CMMS, but it also requires advanced technology, such as sensor data, IoT devices, and analytical software. Wireless vibration sensors continuously monitor equipment, collecting data on temperature and movement. Machine learning algorithms analyze this data to identify patterns and predict failures. The technology processes thousands of data points to determine when maintenance is truly needed. Triggering Maintenance Tasks Preventive maintenance tasks get triggered by time or usage milestones. When the calendar reaches the scheduled date, maintenance occurs automatically, regardless of whether the equipment shows any problems or not. Usage-based triggers include operating hours, production cycles, or miles driven. A truck gets serviced every 5,000 miles regardless of how it's running. Predictive maintenance triggers originate from actual equipment condition data that reveals anomalies or degradation. Vibration patterns, temperature changes, or oil analysis results indicate when work is needed. Illustration: WorkTrek / Data: ADVMM Real-time monitoring means problems get detected immediately rather than waiting for the next scheduled inspection. Equipment health determines the timing, rather than arbitrary dates. The predictive approach prevents both unnecessary maintenance and unexpected failures by responding to the actual needs of the equipment. Benefits and Limitations of Each Approach Both maintenance strategies offer advantages in managing asset performance and controlling costs. Preventive maintenance offers straightforward implementation, while predictive maintenance provides precise, data-driven insights that optimize resource allocation. Advantages of Preventive Maintenance With preventive maintenance, you can deliver immediate value through its simple implementation approach. Companies can start programs quickly without complex technology investments or specialized training requirements. Key benefits include: Reduced unplanned downtime through scheduled interventions Extended asset lifespan via regular care and inspections Lower initial costs compared to advanced monitoring systems Improved safety through consistent equipment checks Illustration: WorkTrek / Data: Brightly Preventive maintenance increases overall equipment productivity, which can benefit any organization. It can also allow for better workforce planning and budget allocation throughout the year. Advantages of Predictive Maintenance Predictive maintenance can take the guesswork out of maintenance. With predictive maintenance, real-time monitoring identifies problems before equipment failures occur. Primary advantages: Optimized maintenance costs through intervention timing Maximum asset performance via condition-based scheduling Reduced repair costs by catching issues early Minimal planned downtime with precise scheduling Illustration: WorkTrek / Data: dynaway The approach is designed to reduce and, in some cases, eliminate unnecessary maintenance work. Based on sensor data, the equipment receives attention only when the data indicates an actual problem. You can manage your inventory a lot better if you have better visibility to detect failures. Instead of randomly buying parts, companies stock parts based on the actual conditions of their equipment. Challenges and Drawbacks Both approaches face significant limitations that affect their implementation and effectiveness in different situations. Preventive maintenance challenges: Risk of unnecessary interventions and wasted resources Planned downtime for equipment that doesn't require service Limited effectiveness for complex, high-value assets Predictive maintenance requires higher initial investments in technology and specialized personnel. The complexity of data analysis demands specific skills that many organizations lack. Implementation barriers include: Advanced sensor and monitoring technology costs Need for trained data analysts and technicians Complex system integration requirements Implementation Requirements and Tools Both maintenance approaches need technology to streamline the process. Maintenance software platforms help manage schedules and data, while sensors provide real-time equipment insights. Maintenance Software and CMMS A computerized maintenance management system forms the backbone of both maintenance strategies. CMMS platforms track work orders, schedule tasks, and store equipment history in one central location. Soure: WorkTrek For preventive maintenance, the CMMS can easily manage calendar-based schedules. Teams can set up recurring tasks like "change oil filter every 60 days" or "inspect belts monthly," and have them assigned to maintenance teams. Key CMMS features for preventive work: Automated work order generation Asset history tracking Parts inventory management Labor time recording Predictive maintenance demands more advanced capabilities. The maintenance software must handle sensor data feeds and generate alerts when readings exceed normal ranges. Advanced CMMS requirements: Real-time data integration Dashboard analytics Mobile access for technicians Custom reporting tools Role of Sensors and Condition Monitoring Condition monitoring can transform raw sensor data into actionable maintenance decisions. By implementing temperature sensors, vibration monitors, and oil analysis tools, you can get continuous equipment health updates. Common sensor types: Vibration sensors - Detect bearing wear and alignment issues Temperature probes - Monitor motor heat and friction Pressure gauges - Track hydraulic and pneumatic systems Oil analysis kits - Check contamination levels Vibration analysis stands out as one of the most valuable predictive tools. These sensors detect early signs of mechanical problems weeks before equipment fails. The data flows from sensors to maintenance software platforms that analyze patterns. Machine learning algorithms compare current readings to historical baselines. Data analysis requirements: Baseline establishment period Alert threshold settings Pattern recognition software Historical trend storage Illustration: WorkTrek / Data: EU Automation Installation costs can vary based on equipment complexity. For example, a simple temperature sensor might cost hundreds of dollars, while more complex sensors like vibration monitors might cost thousands. Training and Team Readiness Maintenance teams need to learn different skills for each approach. When considering preventive maintenance, your team needs to be efficient in following procedures and accurately documenting completed tasks. Preventive maintenance skills: Following maintenance schedules Basic troubleshooting techniques Parts replacement procedures Safety protocol compliance Predictive maintenance, on the other hand, demands higher technical knowledge. Maintenance technicians must be skilled at interpreting sensor data and recognizing equipment failure patterns. Predictive maintenance training needs: Data analysis fundamentals Sensor technology basics Condition monitoring techniques Predictive insights interpretation If you don't have a plan in place, it is much easier to start with preventive methods while building predictive capabilities. This approach lets teams learn gradually without overwhelming existing workflows. Training programs should cover both technical skills and software operation. Implementation timeline considerations: 3-6 months for basic preventive setup 12-18 months for full predictive deployment Ongoing education for new technologies Regular refresher training sessions Success depends on management support and clear performance metrics. Teams perform better when they understand how their work impacts overall business goals. Impact on Operations and Asset Lifespan Both maintenance strategies significantly affect how equipment operates and how long it lasts. The timing and approach of each method create different outcomes for machine availability and overall equipment effectiveness. Reducing Machine Downtime Preventive maintenance can reduce unplanned downtime by following set schedules. With regular equipment service intervals, teams can identify and address problems before they lead to breakdowns. This approach will require planned downtime for routine tasks. There is, however, a downside to preventive maintenance. Since this is set to a fixed schedule, sometimes equipment is serviced when it is not necessary. This can lead to increased labor and material costs. Preventive maintenance involves planned downtime for service at regular intervals, which can be scheduled during non-peak hours. A predictive maintenance program takes a different approach as part of maintenance management. It constantly monitors equipment and only schedules work when data indicates a problem is imminent. This method minimizes unplanned downtime by performing maintenance just-in-time, before failure occurs. The result is less total downtime. Equipment runs longer between maintenance tasks because work only happens when truly needed, leading to cost savings. Improving Asset Performance Preventive maintenance can improve equipment performance. Scheduled tasks like lubrication, cleaning, and part replacement maintain steady performance. This is no different than changing the oil in your car every 5000 miles. However, some assets might get serviced too early or too late compared to their actual condition. Predictive maintenance can optimize asset performance by using real-time data. Sensors track vibration, temperature, and other factors that affect how equipment works. Illustration: WorkTrek / Data: LLCBuddy Predictive maintenance keeps machines in optimal condition and reduces emergency repairs. This type of preventative maintenance strategy is ideal for high-value and critical equipment. Conclusion The choice between preventive and predictive maintenance isn't an either-or decision. While preventive maintenance offers simplicity and immediate implementation benefits, predictive maintenance provides data-driven precision that optimizes resource allocation. Innovative organizations recognize that each approach serves different equipment types and operational needs. Simple assets benefit from scheduled preventive care, while critical, high-value equipment justifies investments in predictive technology. The most successful maintenance strategies combine both approaches, starting with preventive maintenance as a foundation while gradually incorporating predictive capabilities where they deliver the most significant value. This hybrid approach maximizes equipment reliability, minimizes costs, and positions companies for long-term operational excellence.

Key Takeaways: Predictive maintenance delivers an average ROI of 10:1, with savings of 18-25% compared to preventive maintenance Modern preventive and predictive maintenance solutions are more accessible than ever, with cloud-based CMMS platforms offering entry-level options Companies using predictive maintenance report 30-50% reduction in machine downtime and 20-40% increase in equipment life Integration with existing systems is simpler today, with 65% of companies already using CMMS to monitor operations Picture this: your HVAC system is humming along perfectly when suddenly, a critical compressor fails. Production grinds to a halt. Your maintenance teams scramble to find replacement parts. Energy bills skyrocket as backup systems strain to compensate. Sound familiar? This scenario plays out daily across facilities worldwide. This can cost companies millions in unnecessary downtime and reactive maintenance. Illustration: WorkTrek / Data: IndustryWeek Yet many organizations still cling to outdated beliefs about predictive maintenance that prevent them from embracing this game-changing approach. The truth is, predictive maintenance has evolved dramatically. What was once complex machinery reserved for Fortune 500 companies is now accessible, cost-effective technology that saves money while keeping operations running smoothly. According to recent industry data, companies implementing predictive maintenance see an average return on investment of 10:1, with some organizations reporting savings of up to $1,000 per machine annually. Let's separate fact from fiction by examining six common myths about predictive maintenance. Myth 1: Predictive Maintenance Is Too Expensive for Most Companies One of the most persistent and costly misconceptions about predictive maintenance is that it requires a massive upfront cost that is only accessible to large corporations that can afford it. This outdated belief comes from the early days of condition monitoring. In those days, specialized equipment could cost six figures and require dedicated teams of certified professionals to operate. The Reality Today Today, modern predictive maintenance has become remarkably cost-effective. The benefits are clear, according to the U.S. Department of Energy, predictive maintenance saves 8-12% more than preventive maintenance. What is even more impressive is that it can save up to 40% compared to reactive maintenance approaches. The big question is whether these savings can offset initial investments. Research from McKinsey shows that predictive maintenance can reduce maintenance costs by 18-25%. Given those savings, you can calculate your ROI while delivering additional value through increased uptime. Illustration: WorkTrek / Data: IoT Analytics Today's predictive maintenance solutions come in various price points: Entry-level vibration analysis tools start at a few thousand dollars Cloud-based monitoring systems operate on subscription models, eliminating huge upfront capital expenditures CMMS platforms with predictive capabilities offer scalable pricing based on your maintenance needs IoT sensors have dropped dramatically in price, making real-time data collection affordable The key is starting small. You don't need to monitor every piece of equipment from day one. Keep your focus on critical assets where equipment failures cause the most expensive repairs or unnecessary downtime. As you see and evaluate results, you can expand your predictive maintenance program. Myth 2: Only Large Manufacturing Plants Need Predictive Maintenance Surveys and studies show that many facility managers believe predictive maintenance is overkill for their operations. This thinking is tied to the belief that predictive maintenance should only be used on complex machinery. This myth causes smaller operations to miss out on significant cost savings and operational efficiency gains. Illustration: WorkTrek / Data: EasyMaint Why Every Facility Benefits The reality is that any organization with critical equipment can benefit from data-driven maintenance decisions. Whether you're managing HVAC systems in an office building, maintaining a fleet of delivery vehicles, or overseeing equipment in a small manufacturing plant, predictive maintenance delivers value. Consider these statistics: A 29-story office building saved $16,742 in operating costs and $32,300 in repair costs annually by implementing predictive maintenance for its HVAC systems alone The transportation industry expects to see the fastest growth in predictive maintenance adoption between 2020 and 2025 Even small manufacturers report 5-10% increases in overall equipment effectiveness (OEE) with predictive maintenance Small and medium-sized businesses often see faster ROI because: Lower complexity means easier implementation Fewer assets require less initial investment Tighter budgets make cost savings more impactful Limited staff benefit more from automated monitoring The automotive sector has seen a 15% increase in productivity through the use of predictive maintenance applications. These aren't just massive assembly plants; they include smaller suppliers and service centers that have embraced proactive maintenance. Modern CMMS solutions like WorkTrek make predictive maintenance accessible regardless of company size. These user-friendly platforms can monitor equipment performance, track maintenance data, and predict potential failures without requiring a dedicated data science team. Myth 3: Predictive Maintenance Eliminates All Equipment Failures Some organizations hesitate to invest in predictive maintenance since it is not a perfect solution. We all know that even the most preventative maintenance schedules can result in equipment failure. Organizations assume that because of that, predictive maintenance won't fare much better. Setting Realistic Expectations No maintenance strategy can eliminate all equipment failures. However, predictive maintenance dramatically reduces both the frequency and impact of breakdowns over just regular maintenance. Industry data shows that organizations implementing predictive maintenance programs see: 70-75% elimination of breakdowns 35-45% reduction in downtime 30-50% decrease in unplanned equipment failures 20-40% extension in equipment life The goal isn't always perfection, but rather optimizing routine maintenance to maximize efficiency. Illustration: WorkTrek / Data: SAP Predictive maintenance utilizes real-time data and condition monitoring to identify issues before they lead to costly repairs or operational disruptions. While you can't prevent every failure, you can: Minimize downtime by scheduling repairs during planned maintenance windows Reduce the severity of asset failures by catching problems early before they cascade Improve safety by preventing catastrophic failures Optimize resources by focusing maintenance tasks where they're needed most One good example is a steel manufacturer that uses predictive maintenance on its transformers, which provides a perfect example. When sensors detect unusual heat patterns, they can schedule maintenance during a planned shutdown. This can prevent long downtimes that cost a lot of money. Think of predictive maintenance as your early warning system. Just as smoke detectors don't prevent all fires, they can give you time to respond. Predictive maintenance enables the early detection necessary to prevent minor issues from escalating into major failures. Myth 4: Implementing Predictive Maintenance Requires Replacing All Existing Equipment Many maintenance teams believe they need to scrap their current equipment and invest in new machinery with built-in sensors to implement predictive maintenance. This misconception keeps organizations stuck with reactive maintenance and rising maintenance costs. Working with What You Have The truth is, most existing equipment can be retrofitted with monitoring capabilities. You don't need to replace functioning assets to gain predictive insights. A lot of the modern solutions are designed to work with legacy equipment: Retrofit Options: External sensors can be attached to existing motors, pumps, and other equipment Wireless vibration sensors mount directly on bearing housings Temperature monitoring devices clip onto equipment surfaces Current sensors wrap around existing power cables Ultrasonic detectors identify leaks without equipment modification Illustration: WorkTrek / Data: openPR Even 20-year-old equipment (the average age of industrial assets in the U.S.) can benefit from predictive monitoring. Original equipment manufacturers (OEMs) increasingly offer retrofit packages specifically designed for older models. These solutions provide: Compatibility with existing control systems Minimal installation downtime Training for your current maintenance teams Integration with your existing CMMS Start with your most critical assets that are most critical to your organization. Remote monitoring capabilities enable you to track equipment performance from anywhere, either in your office or on your mobile phone. Myth 5: Predictive Maintenance Technology Is Too Complex for Most Teams There is a fear in the industry that predictive maintenance requires data scientists, complex algorithms, and extensive training. This misconception ignores how user-friendly modern predictive maintenance solutions have become. Simplicity Through Smart Design Today's predictive maintenance tools are designed for maintenance teams, not IT specialists. A lot of the modern platforms emphasize: Intuitive Interfaces: Dashboard views that highlight critical information Color-coded alerts for quick problem identification Automated reporting that translates data into actionable insights Mobile apps that put information in technicians' hands According to industry surveys, 80% of maintenance personnel still prefer preventive maintenance, often because they're intimidated by predictive technology. Illustration: WorkTrek / Data: MDPI However, companies that have made the switch report that the learning curve is much gentler than expected. Consider how modern CMMS platforms handle predictive analytics: Automated data collection eliminates manual recording errors Pre-built algorithms identify patterns without custom programming Plain-language alerts explain issues without technical jargon Recommended actions guide maintenance decisions Integration with existing workflows minimizes disruption Training requirements are surprisingly minimal. Most vendors provide: On-site implementation support Online training modules at your own pace Ongoing technical assistance User communities for peer support The shift from reactive to predictive maintenance is less about complex technology and a lot of the time is about changing mindsets. When teams see the benefits of predictive analytics and how it simplifies their work, adoption becomes natural. Myth 6: Predictive Maintenance Is Only About Preventing Breakdowns It is always important to prevent equipment failure. However, viewing predictive maintenance only through this lens drastically undervalues its benefits. This narrow perspective results in the organization missing opportunities for operational efficiency. The Broader Impact of Predictive Maintenance Predictive maintenance can transform your entire maintenance operation into a finely tuned machine. Here's what organizations actually gain: Energy Efficiency Improvements Energy costs make up a significant part of any manufacturing facility's budget. It is also not a surprise that well-maintained equipment uses less energy. Dirty filters, misaligned components, and worn parts force machines to work harder, driving up energy bills. The good news is that predictive maintenance identifies these inefficiencies before they impact your bottom line. According to a study, companies report 5-10% reductions in energy consumption simply by maintaining optimal equipment performance. Extended Asset Life: Instead of running equipment to failure or replacing parts on arbitrary schedules, predictive maintenance helps you maximize equipment life. It does this by using real-time data that reveals actual wear patterns, allowing you to: Replace components at optimal times Adjust operating parameters to reduce wear and tear Balance loads across multiple assets Identify and eliminate root causes of premature failure Studies show predictive maintenance can extend asset lifespan by 20-40%, delivering massive savings in capital expenditure. Enhanced Safety Early detection of potential failures doesn't just save money—it saves lives. Predictive maintenance identifies safety risks before they become hazards: Detecting bearing failures before catastrophic equipment breakdown Identifying electrical issues before they cause fires Monitoring structural integrity to prevent collapses Alerting teams to abnormal operating conditions Better Resource Allocation: With predictive insights, maintenance teams can: Schedule work during planned downtime Order parts just in time, reducing inventory costs by 20-50% Assign certified professionals to tasks that truly need their expertise Eliminate unnecessary preventive maintenance tasks Source: WorkTrek Competitive Advantage Companies using predictive maintenance report improved product quality, better customer satisfaction, and increased market competitiveness. How CMMS Helps Bridge the Gap to Predictive Maintenance When it comes to asset maintenance, the transition from reactive or preventive maintenance to predictive maintenance doesn't happen overnight. This is where a robust CMMS becomes your most valuable ally, serving as the foundation for your data-driven maintenance evolution. Building Your Predictive Foundation with CMMS A modern CMMS, like WorkTrek, transforms scattered maintenance data into actionable, predictive insights. Here's how CMMS platforms enable effective predictive maintenance: Centralized Data Collection Before you can predict failures, you need a comprehensive maintenance history. CMMS automatically captures: Complete work order histories Actual vs. planned maintenance costs Equipment performance trends Failure patterns and frequencies Parts usage and inventory levels Source: WorkTrek his historical data becomes the baseline for predictive analytics, helping identify patterns that human observation might miss. Integration Capabilities Modern CMMS platforms seamlessly connect with: IoT sensors for real-time equipment monitoring Building management systems for HVAC performance ERP systems for cost tracking Mobile devices for field data collection The Real Cost of Believing These Myths While we've debunked these common myths individually, it is important to understand the cumulative impact of maintaining these outdated beliefs. The Hidden Price of Inaction Consider these industry statistics: Unplanned downtime costs manufacturers an average of $260,000 per hour In the automotive industry, that figure reaches $695 million annually per plant 82% of companies have experienced at least one unplanned outage in the past three years But the costs go well beyond just downtime: Maintenance Overspending Organizations using reactive maintenance spend 40% more than those using predictive approaches. Premature Equipment Replacement Without predictive insights, companies replace equipment based on age rather than condition. Studies show that less than 10% of industrial equipment actually wears out, but most failures are preventable with proper maintenance. Energy Waste Poorly maintained equipment consumes 15-30% more energy. For a facility spending $500,000 annually on energy, that's up to $150,000 in unnecessary costs. Safety Incidents Equipment failures cause 35% of workplace accidents. The human cost is immeasurable, while the financial impact can be insurmountable for organizations. The Competitive Disadvantage While you're busy dealing with unexpected breakdowns and emergency repairs, your competitors using predictive maintenance are: Delivering products on time, every time Operating at lower costs Investing savings into innovation Building a reputation for reliability The longer you wait, the wider this gap becomes. Taking the First Step Toward Predictive Maintenance We can report based on our experience that breaking free from these maintenance myths doesn't require a complete overhaul of your operations. The journey to predictive maintenance can start with simple, strategic steps that deliver immediate value. Once you get experience, you can continue to push predictive maintenance programs to add to additional equipment. Below is a simple schedule for rolling out predictive maintenance: Start Small, Think Big Week 1-2: Assess Your Current State List and document your most problematic equipment Calculate current downtime costs Identify maintenance data you're already collecting Evaluate your team's technical comfort level Month 1: Choose Your Pilot Program Select 1-3 critical assets for initial monitoring Focus on equipment with: High failure rates Expensive downtime impact Available historical data Clear failure patterns Month 2-3: Implement Basic Monitoring Deploy simple sensors (vibration, temperature) Begin collecting baseline data Set up basic alerts for abnormal conditions Track results and refine thresholds Month 4-6: Expand and Optimize Add additional assets based on initial success Integrate monitoring with your CMMS Train team on interpreting predictive insights Calculate ROI and plan broader rollout Making the Business Case To gain buy-in from leadership, focus on these compelling points: Quick Wins: Predictive maintenance typically pays for itself within 6-12 months Even preventing one major failure can justify the entire investment Energy savings alone often cover 30-40% of implementation costs Risk Mitigation: Reduced liability from equipment-related incidents Improved compliance with safety regulations Better insurance rates due to fewer claims Protection against supply chain disruptions Strategic Value: Competitive advantage through reliability Improved customer satisfaction Better capacity planning Enhanced sustainability metrics Conclusion The myths surrounding predictive maintenance have kept organizations trapped in cycles of reactive repairs. This has naturally led to an increase in reactive maintenance. As this blog post has highlighted, modern predictive maintenance is accessible, affordable, and achievable for organizations of all sizes. Illustration: WorkTrek / Data: Grand View Research Whether you're managing a small facility with basic HVAC systems or overseeing complex manufacturing equipment, the tools and technologies exist to transform your maintenance operations. The only question remaining is: how much longer can you afford to wait? Take the first step toward predictive maintenance today. Your equipment, your team, and your bottom line will thank you.

Key Takeaways: Predictive maintenance can reduce unplanned equipment downtime by up to 50%. Regular maintenance helps extend equipment lifespan by preventing accelerated wear and tear caused by neglect. IoT sensors and CMMS software enable proactive maintenance by providing real-time equipment data and automating workflows. Keeping your equipment operational is only possible with solid maintenance workflows. So, if you are looking for ways to reduce surprise repair costs and keep your operations running smoothly, this guide is for you. In this article, we will explore the importance of equipment maintenance, but also some of the common challenges that come with this practice. Finally, we will introduce you to the modern tools that can make the entire process much easier to manage. Why Is Equipment Maintenance Important? While most people recognize that maintenance matters, the specifics often get overlooked or misunderstood. This can lead to maintenance being treated as a “nice to have” rather than a necessity, and to postponing or skipping key tasks. Ultimately, all of this leads to costly breakdowns and setbacks. So, let’s go over three specific benefits of maintenance to show you why it’s so important. Minimizes Downtime Equipment will inevitably fail or break down at some point. However, regular maintenance ensures this does not suddenly disrupt your operations or production lines. With a good maintenance plan, you ensure that your machines and tools are always in optimal condition, making all the necessary checks and adjustments before they can turn into major failures. Of course, while a piece of equipment will usually not be operational during maintenance, this scheduled downtime costs significantly less than the unplanned one, research shows. Illustration: WorkTrek / Data: Intelliarts This is because it can be planned for periods when operational disruption will be minimal. By allowing a small amount of planned downtime for maintenance, you significantly reduce the risk of unexpected, prolonged equipment failure during critical times. In fact, the 2024 Siemens report shows that predictive maintenance can reduce unplanned downtime by as much as 50%, and even help predict when downtime might occur. Illustration: WorkTrek / Data: Siemens After all, when maintenance is done proactively and not as a reaction to something breaking, you are in control. Ultimately, planned maintenance makes operations more stable and reduces the chances of unexpected and costly interruptions. Extends Equipment Lifespan Another big benefit of regular maintenance is that it helps keep your equipment functional and efficient for longer. It is important, however, to understand just how much proper maintenance can reduce the wear and tear on your machines. This article discusses this topic in detail, referencing Raymond Bayer's 2002 book, Wear Analysis for Engineers. When discussing different wear rates, the book explains that certain damaging mechanisms, especially abrasion and adhesion, can dramatically accelerate the rate at which a machine's parts degrade. Illustration: WorkTrek / Data: Machinery Lubrication Every piece of equipment has a normal wear rate that is predicted by its manufacturer. However, when a machine goes unmaintained, its components can be damaged much more quickly, thereby drastically shortening its useful life. But it's not just about damage prevention. Regular maintenance can also help increase your Overall Equipment Effectiveness (OEE), a standard measure of how productive your operations truly are. Source: WorkTrek After all, well-maintained equipment functions closer to its designed specifications and produces fewer defective parts because its components are properly calibrated and in good condition. What that means is that maintenance keeps your assets in optimal shape, ensuring they last as long as possible while delivering the best possible results. Improves the Safety of Your Personnel Maybe the most important benefit of regular maintenance is that it ensures your workplace is a safe environment for your staff. It should come as no surprise that well-maintained equipment is significantly less likely to malfunction and cause accidents, injuries, or worse. This is because regular inspections can help identify worn-out parts, potential electrical issues, or structural weaknesses before they lead to a catastrophic failure. Failing to address these issues promptly can result in serious consequences. For example, consider the case of a deadly factory blast in March 2024 at a facility owned by LifeLong India, an automotive components manufacturer. Source: Business and Human Rights Resource Center While several factors were investigated, the incident was allegedly caused by poor equipment maintenance. Specifically, reports pointed to the failure to properly clean and maintain the dust collectors within the company's buffing department, leading to a fatal explosion. Of course, accidents can happen in any operation, but consistent maintenance and proper safety protocols are essential for preventing incidents like this and minimizing their impact. Plus, maintenance is essential for compliance with major industry safety standards and regulations, such as: The Occupational Safety and Health Administration (OSHA) standards The Provision and Use of Work Equipment Regulations (PUWER) in the UK ISO 45001 for occupational health and safety management In short, a commitment to maintenance is a commitment to safety. By keeping your equipment in excellent working order, you’re protecting both your assets and your staff. What Are the Challenges of Equipment Maintenance? Despite its clear benefits, equipment maintenance comes with its own set of challenges. From limited budgets and a lack of expert staff to poor data tracking and reactive mindsets, these hurdles can make even basic upkeep feel overwhelming. Understanding these obstacles is the first step toward building a more proactive maintenance plan. In the following sections, we’ll explore some of the main issues you can face. Limited Budgets The reality for many facilities is that they must operate under tight budgets, which limits the funds that can be allocated to maintenance. As a result, maintenance tasks are often deferred, or the strategy becomes reactive, with maintenance tasks being done on equipment that has already broken down. Unfortunately, without regular preventive maintenance, the likelihood of equipment inefficiencies and unexpected downtime increases significantly. This often results in much higher long-term costs for emergency repairs or complete replacements. The only solution is to use these limited maintenance budgets smartly. For instance, the cost of certain technologies for preventive and predictive maintenance, like Internet of Things (IoT) sensors, has gone down drastically over time. Illustration: WorkTrek / Data: McKinsey These small devices can be attached to equipment to collect real-time data on metrics like temperature, vibration, and performance. While collecting and analyzing this data requires an initial investment, the prevention of just one costly equipment failure is often worth it. Yes, proactive maintenance practices can be very labor-intensive and expensive. But, with modern tools and automation, maintenance teams can become much more productive, using fewer staff hours to achieve better results and keep essential machinery running smoothly. Poor Maintenance Documentation Even when maintenance is regularly performed, its effectiveness can be difficult to manage without accurate and consistent records. Put simply, proper record-keeping and building a service history is key. This documentation enables you to analyze failure patterns, track costs, and make informed decisions about current and future maintenance needs. Unfortunately, using outdated methods like paper records and spreadsheets often makes this problem worse. While helpful maintenance spreadsheet templates do exist, they come with significant disadvantages, such as being prone to human error during manual data entry. Source: Simple Sheets Combine that with weak documentation practices that aren’t enforced, and it becomes even more difficult to track maintenance accurately and ensure equipment reliability. Records may be incomplete, inaccurate, or omitted entirely, making your maintenance history unreliable. A key part of the solution is implementing a standardized digital system for tracking maintenance tasks, work logs, and equipment status across the facility. Source: WorkTrek A centralized digital platform, such as a CMMS, ensures that all the relevant information is stored in one place and accessible to anyone who needs it. This approach standardizes and often automates how data is recorded, reducing the chance of human errors and making it easy to pull up the complete history of any asset. While strong documentation procedures are still a must, combining them with a solid tech solution can help build the foundation of an efficient maintenance program. Lack of Skilled Staff Consider this fact: the average age of a maintenance technician in the U.S. is currently 47 years old. In the coming years, facilities will have to manage the reality of their most experienced workers slowly retiring. In fact, according to the U.S. Bureau of Labor Statistics, the job outlook for machinery maintenance workers is projected to grow by 15% from 2023 to 2033, a rate much higher than the 4 percent average for all occupations. Source: BLS This creates the challenge of finding new maintenance technicians to replace the retiring workforce, while also ensuring they have the necessary skills to do their job effectively. The latter is a major hurdle in itself, as equipment becomes more technologically advanced. According to the 2022 State of Industrial Maintenance Report, over half of organizations outsource at least some of their maintenance work due to a lack of skilled staff in-house. Illustration: WorkTrek / Data: ATS The solution to this challenge is not simple, but it primarily focuses on education. This involves both investing in robust training programs for new employees and cross-skilling existing staff to handle a wider variety of maintenance tasks. What can also really help is providing the right support in the form of technology, which we will cover next. Overall, by focusing on training and smart tools, you can build a capable team prepared for the future. Tools for Better Equipment Maintenance Management To make the most out of your equipment maintenance, relying on outdated processes and tools won’t be enough. Luckily, modern solutions like CMMS platforms and Internet of Things (IoT) devices address many of the common maintenance challenges while enabling a more proactive approach. Additionally, according to a report from McKinsey & Company, digitizing and automating your maintenance processes can result in significant cost savings. Illustration: WorkTrek / Data: McKinsey Let’s take a look at IoT sensors, for example. As Boris Dinkevich, Co-founder of the hardware-as-a-service platform Xyte, explains, these devices can continuously collect a vast amount of valuable equipment data. Illustration: WorkTrek / Quote: Xyte Let’s illustrate this with an example. Say you placed a vibration sensor on a critical motor. Suppose the sensor detects unusual vibration patterns that suggest a bearing is about to fail. In that case, it can automatically send an alert to the maintenance team long before the motor breaks down. All of this data is transmitted via the cloud for easy access and greatly synergizes with CMMS systems. For example, WorkTrek is one such solution, designed to help businesses manage their maintenance operations within a single platform. It can handle everything from work orders, asset data, preventive maintenance tasks, inventory, and more. For instance, a work order can be created directly in the system, assigned to a specific technician, and its progress tracked until completion. Source: WorkTrek Instead of using paper-based documents or slow communication channels, everything is streamlined with instant notifications to managers and key staff. Additionally, WorkTrek supports condition-based maintenance scheduling by processing IoT sensor data and other key equipment metrics, allowing you to schedule proactive maintenance tasks based on real-world operating conditions. Overall, by combining real-time equipment data with a centralized software, you can keep your equipment running reliably and efficiently. Conclusion As you can see, while equipment maintenance has its challenges, its advantages are well worth the effort. Plus, some of the modern tools and systems we covered make managing these tasks simpler than ever, turning a difficult job into a streamlined process. With this foundation, you’re well-equipped to delve deeper into equipment maintenance and develop strategies that safeguard your valuable assets while enhancing operational efficiency.

Key Takeaways High initial costs are the top barrier for 34% of organizations, but starting with pilot programs on critical assets can demonstrate ROI quickly 95% of predictive maintenance adopters report positive ROI, with 27% achieving payback in less than a year Unplanned downtime costs average $260,000 per hour, making the investment in predictive maintenance technology worthwhile Starting with a CMMS platform provides a cost-effective foundation for building predictive maintenance capabilities over time Let's address the elephant in the room: implementing predictive maintenance isn't as straightforward as many would have you believe. While the promise of reduced downtime and lower maintenance costs is compelling, the path can be rocky. Those who go down the path are seeing the fruits of their labor. According to recent research from IoT Analytics, 95% of predictive maintenance adopters reported a positive ROI, with 27% of these reporting amortization in less than a year. Illustration: WorkTrek / Data: TinkerTrak Yet, despite the data, organizations still struggle with their predictive maintenance strategy. Understanding these challenges and knowing how to overcome them is key to implementing a successful predictive maintenance strategy. Challenge 1: High Initial Investment Costs The sticker shock of implementing predictive maintenance can stop many organizations in their tracks. Based on our experience with existing clients, predictive maintenance can be expensive. What are some of the typical costs? Usually includes installing sensors, integrating advanced analytics software, and upgrading existing infrastructure. Since many manufacturing maintenance organizations operate on a tight margin, the upfront investment can be challenging. Illustration: WorkTrek / Data: The Planned Maintenance Playbook Consider what a typical predictive maintenance implementation requires: IoT sensors and monitoring equipment for critical assets Data transmission infrastructure Analytics software and platforms System integration with existing CMMS or ERP systems Staff training and potentially new hires with specialized skills Based on a recent study, the manufacturing sector alone accounted for nearly 30% of the market share. This makes it the most dominant vertical in which predictive maintenance systems are used. This dominance exists because larger manufacturing plants can absorb the initial costs by spreading them across several assets. Path forward for Smaller Organizations However, there's a way forward for organizations of all sizes. It is always a good idea to start small with pilot programs on your most critical equipment. Keep focused on assets where equipment failures would cause the most significant operational disruptions or pose the greatest safety risks. This approach enables you to demonstrate ROI quickly for the management team before incurring significant expenses. It is nearly impossible to implement a robust predictive maintenance strategy without a CMMS platform like WorkTrek. When considering a CMMS platform, make sure that it integrates with IoT sensors and provides the data infrastructure needed for more advanced predictive analytics down the road. Challenge 2: Data Quality and Integration Issues The most sophisticated predictive maintenance models and machine learning algorithms in the world are useless without quality, but they're useless without a large amount of data. One of the primary challenges in predictive maintenance is accurately analyzing large datasets. Analyzing data that is inconsistent or incomplete can lead to incorrect predictions. This challenge can become ever more complex when dealing with legacy equipment that wasn't designed with data collection in mind or lacks sensors. This common predictive maintenance challenge can manifest itself in several ways: Incomplete Data Older equipment may lack sensors. Sometimes, existing sensors may not capture all the necessary parameters for accurate predictions. For instance, you might have temperature data but lack vibration readings or have pressure measurements without corresponding flow rates. Data Silos Information often exists in disconnected systems—maintenance records in one database, operational data in another, and quality metrics in yet another system. Without integration, you're missing the complete picture needed for accurate failure prediction. Data Quality A large part of IoT data could contain errors, gaps, or inconsistencies. Large IoT data can also be noisy, which requires a cleanup process before it can be analyzed. Sensor drift, calibration issues, and communication failures can all compromise data integrity. Here are a few things successful organizations do to manage data quality. Conduct a data audit Implement data governance procedures Invest in data integration platforms Implement anomaly detection techniques Use AI and Machine Learning techniques to help with data normalization Retrofit legacy equipment with modern sensors Challenge 3: Lack of Skilled Personnel According to a 2025 SFG20 report, only 29% of facility managers believe their technicians are "very prepared". This is while 45% say they're "somewhat prepared", and 26% "not at all prepared" for the technological shift that predictive maintenance requires. This skills gap is one of the most significant barriers to successful implementation. Illustration: WorkTrek / Data: Vietsoft Solutions Predictive maintenance requires a unique blend of expertise that many organizations struggle to find: Data scientists who can develop and refine predictive models Data Engineers who can manage large data sets IT professionals who can manage the technology infrastructure Maintenance technicians who can interpret and act on predictive insights A lot of traditional maintenance teams are highly skilled in reactive and preventive maintenance. However, they may feel overwhelmed by the technology and data analysis requirements of predictive maintenance. According to a PwC and Mainnovation 2017 survey, technicians play a key role in predictive maintenance. Based on the research, PdM efforts are involved in 79% of the surveyed facilities. This requires organizations to invest heavily in training and development. This includes: Technical training on new systems and tools Data literacy programs to help staff understand and use analytics Cross-functional training to break down silos between maintenance, operations, and IT Consider partnering with equipment manufacturers or predictive maintenance vendors who can provide specialized training in advanced technologies. Also, some organizations may find success in hiring consultants or managed service providers to bridge the skills gap. This could be a stopgap measure while the internal team is learning predictive analytics techniques. Challenge 4: Resistance to Change Cultural resistance can undermine predictive maintenance initiatives. Maintenance teams that are already accustomed to time-based preventive maintenance schedules may view predictive maintenance technology as a threat. Operations teams might also resist the production interruptions required to install sensors or implement new procedures. Illustration: WorkTrek / Data: FieldCircle Some of the reasons for resistance include: Fear that automation will eliminate jobs Skepticism about the accuracy of predictive models Concern about the increased workload during the transition period Distrust of "black box" algorithms in making maintenance decisions While 95% of predictive maintenance adopters reported a positive ROI, organizations still struggle with adoption because they fail to address the human element of change management. Below are a few tips on a successful change management strategy: Involve Teams Early Include maintenance staff in the planning and implementation process. Their practical knowledge is invaluable for identifying which assets to monitor and what failure modes to track. Establish Clear Communication Illustration: WorkTrek / Data: WorldMetrics Explain how predictive maintenance will enhance, not replace, human expertise. Emphasize that the technology handles data analysis, freeing technicians to focus on higher-value problem-solving. Gradual Implementation Start with pilot projects that demonstrate clear wins and manage expenses. Success stories from within the organization are more convincing than vendor case studies. Continuous Support Provide ongoing training and support. Celebrate successes and learn from failures without assigning blame. Challenge 5: Scalability and Complexity Scaling from a single equipment to the entire production line can become more complex. As your organization grows, scaling predictive maintenance solutions can be difficult. Expanding the system to accommodate additional equipment, locations, or data sources requires careful planning and may involve additional costs. Illustration: WorkTrek / Data: AutomationWorld There are several dimensions to this: Technical Complexity As you add more assets and sensors, the volume of raw data explodes. Your infrastructure must support the handling of large amounts of data generated by thousands of sensors. It is important to do this without compromising performance. Organizational Complexity Facilities can have various types of equipment, different maintenance practices, and distinct organizational structures. Focus on developing a standardized predictive maintenance program that is effective across diverse operations and applications. Model Complexity Each predictive model has to be tailored to the type of equipment. Each equipment type may require its own set of algorithms and failure models, multiplying the analytical workload. The key to managing complexity is a phased, modular approach: Start with standardized equipment types across multiple locations Develop a scalable data architecture from the start Create reusable predictive models that can be adapted rather than rebuilt Establish clear governance structures for managing the expanded program Invest in platforms designed for enterprise-scale deployment Modern asset management systems like WorkTrek provide the foundation for scalable predictive maintenance by centralizing asset data and maintenance workflows across the organization. Challenge 6: Proving ROI and Gaining Buy-in Despite compelling industry statistics, many organizations struggle to develop a business case for predictive maintenance that is supported by their management teams. The PdM market is projected to grow rapidly, from $10.6 billion in 2024 to $47.8 billion by 2029, with a 35.1% annual growth rate. Yet individual organizations often find it challenging to quantify the specific benefits they'll receive. The ROI challenge has several aspects: Intangible Benefits While reduced downtime and lower maintenance costs are measurable benefits, others, such as improved safety, better product quality, and enhanced customer satisfaction, are harder to quantify. Long-term Payback According to a white paper by Deloitte, predictive maintenance can reduce maintenance costs by up to 25% and reduce unplanned downtime by up to 50%. However, these benefits may take years to fully materialize, making it difficult to justify investment based solely on quarterly financial metrics. Attribution Challenges Sometimes when equipment hums and doesn't fail, it's hard to prove that predictive maintenance prevented the failure. Like the old saying, 'no news is good news,' success often appears to be nothing happening, which doesn't make for compelling executive presentations. How do you build a strong business case? Focus on your most critical assets where failures have documented costs Use industry benchmarks but adjust for your specific context Track leading indicators like mean time between failures (MTBF) and schedule compliance Document near-misses and prevented failures Create dashboards and customized reports that show trends over time Calculate both hard savings (reduced parts, labor) and soft savings (avoided downtime) Remember that the average ROI for predictive maintenance projects is 10:1, but this requires patience and commitment. Challenge 7: Cybersecurity and Data Privacy Concerns With the increase in connected systems, organizations are now more exposed to cyber threats. According to a study, 89% of companies are worried about data security and privacy when implementing predictive maintenance systems. These concerns are well-founded, since industrial control systems have become prime targets for cyberattacks. Some of the security challenges include: Expanded Attack Surface: Every sensor, gateway, and connection point represents a potential vulnerability. Legacy equipment can lack basic security features. This makes them particularly vulnerable when connected to networks. Make sure that, at a minimum, all of your IoT devices are password-protected. Data Sensitivity Operational data can reveal production schedules, equipment capabilities, and business strategies. In the wrong hands, this information could benefit competitors or enable targeted attacks. Keep that data on protected systems. System Criticality Predictive maintenance systems often have access to critical production systems. A breach could lead to operational disruption, safety incidents, or quality issues. Keep them on separate VLANs or networks to protect your internal systems. Compliance Requirement There are strict regulations regarding data integrity and security in certain industries like food processing and pharmaceuticals. Addressing cybersecurity requires a multi-layered approach: Conduct security assessments before implementation to get a baseline Implement network segmentation to isolate critical systems Use encryption for data in transit and at rest Establish access controls and authentication protocols Schedule regular security updates and patches Train employees on cybersecurity best practices Develop an incident response planning program Work with IT security teams from the project's inception. Security shouldn't be an afterthought but should be built into the system architecture from the ground up. How WorkTrek CMMS Helps Organizations Overcome These Challenges While the challenges in implementing predictive maintenance are real, they're not insurmountable. The right technology foundation can significantly ease the implementation journey. WorkTrek CMMS addresses many of these challenges through a comprehensive, user-friendly platform designed for organizations at any stage of their predictive maintenance journey. Addressing Cost Concerns WorkTrek offers flexible, scalable pricing that enables organizations to start small and gradually expand their predictive maintenance capabilities over time. Source: WorkTrek Data Management Excellence WorkTrek centralizes all maintenance data on a single platform. This eliminates silos and ensures data integrity and quality. The system automatically tracks maintenance history, costs, and equipment performance metrics, creating the rich dataset needed for predictive analytics. Friendly User Interface Given the skills gap challenge, WorkTrek is designed for maintenance professionals, not data scientists. The intuitive interface enables technicians to easily log observations, access maintenance procedures, and respond to alerts. Source: WorkTrek Change Management Support WorkTrek's mobile capabilities allow maintenance teams to access information and complete work orders from anywhere. Source: WorkTrek Enterprise Scalability Whether managing a single facility or multiple locations, WorkTrek scales to meet your needs. Cloud-based architecture ensures the system can handle growing data volumes without performance degradation. ROI Tracking WorkTrek's comprehensive reporting and analytics make it easy to track and demonstrate ROI. The system can automatically calculate maintenance costs, track downtime, and measure key performance indicators. Source: WorkTrek Security First WorkTrek is built with enterprise-grade security features, including encryption, authentication, access controls, and audit trails. Regular security updates and compliance with industry standards provide peace of mind that your maintenance data is protected. Source: WorkTrek The Future of Predictive Maintenance Despite challenges, the trajectory of predictive maintenance is clear. As artificial intelligence and machine learning algorithms become more sophisticated, they enable more real-time analysis even in remote locations. Digital twins are creating virtual replicas of equipment that can simulate failures and test maintenance strategies. Organizations that successfully navigate the implementation challenges will gain a significant competitive advantage. Those who delay risk falling behind as predictive maintenance becomes the industry standard rather than a differentiator. The key is to start now, even if it's a small step. Build the data foundation, develop the skills, and create the culture that will support predictive maintenance. Address the challenges systematically rather than hoping they'll resolve themselves. Conclusion Implementing predictive maintenance is more than just installing sensors and running algorithms. It's a complete transformation of how you do maintenance. The seven challenges we've explored, high costs, data quality issues, skills gaps, resistance to change, scalability complexity, ROI demonstration, and cybersecurity concerns, are significant but surmountable. The key to success is to acknowledge these challenges upfront and plan accordingly. The path to predictive maintenance is a journey and not just a destination. Begin with a clear vision, but be prepared to iterate and adjust as needed. Invest in the right technology foundation, like Worktrek CMMS, that can grow with your needs. Most importantly, don't let the challenges discourage you from pursuing the significant benefits that predictive maintenance can deliver.

Key Takeaways: Safety incidents make it harder to hire new staff and cause experienced workers to leave. Non-compliance in manufacturing leads to financial penalties and reputational damage. Product recalls can cost anywhere between $8 million and $50 million. Behind every efficient, safe, and sustainable manufacturing operation is one key practice: regular equipment maintenance. Far from being just a routine chore, it’s a strategic must-have that protects your workers, bottom line, productivity, and reputation. Want to understand why maintenance matters so much in the high-stakes world of manufacturing? Keep reading, because we share the latest statistics, expert insights, and real-world examples to show you how much of a difference it can make. Reduces the Risk of Major Industrial Accidents Heavy machinery, pressurized systems, and hazardous materials. Manufacturing environments are dangerous by design. When you add aging equipment and deferred maintenance to the equation, the risk of serious incidents rises significantly. That’s exactly what the 2024 Vector Solutions survey revealed: 30% of industrial workers say their equipment is outdated, and 26% say it’s not properly maintained. As a result, 43% of them experienced a safety incident at their facility within the previous year. Illustration: WorkTrek / Data: Vector Solutions The main takeaway: manufacturing companies need to perform frequent equipment maintenance to improve workplace safety. It can help detect early signs of mechanical or electrical failure and ensure that critical safety systems, like emergency stops and pressure relief valves, are fully functional. In manufacturing, failure to address even the smallest issue on time can lead to some serious consequences. Just ask Keystone Foods, a Tyson Foods subsidiary, recently fined by OSHA after two workers were severely burned in a boiler room explosion. Source: MeatPoultry Investigators discovered that this incident occurred because maintenance was not performed according to the manufacturer's guidelines. It was only a matter of time before an event like this would take place. However, the repercussions of poor safety culture go beyond legal penalties. It can also impact your reputation and overall workforce stability. In fact, the same Vector Solutions survey we mentioned earlier found that 44% of industrial workers believe safety concerns make it harder to hire new staff. Additionally, 57% of them say such issues cause experienced workers to leave. Illustration: WorkTrek / Data: Vector Solutions In an industry already struggling with labor shortages and a growing skills gap, you can’t afford to lose good people because they don’t feel safe. That’s reason enough to prioritize regular maintenance. Helps Ensure Regulatory Compliance Manufacturers face a complex web of strict regulations covering safety, quality control, environmental protection, and operational standards. These include compliance with OSHA, FDA, CDC, USDA, and a range of local, state, and federal laws. On top of that, there are industry-specific standards set by auditing organizations, as well as internal company policies. In short, maintaining compliance in the manufacturing sector is a constant battle. The 2023 KPMG survey found that 42% of Chief Risk Officers in manufacturing identify regulatory changes and compliance issues as their top challenge over the upcoming 2–5 years. Illustration: WorkTrek / Data: KPMG Fortunately, regular maintenance can make this challenge more manageable. By conducting frequent inspections and timely minor repairs, you ensure that equipment operates reliably and within legal specifications. Additionally, consistent upkeep practices generate documentation and proof of due diligence, which are critical during audits and inspections. Compliance gets even easier when you use a CMMS, like WorkTrek, to manage your maintenance activities. WorkTrek automates preventive maintenance scheduling, helping prevent missed tasks. It allows you to configure service triggers based on time or meter readings and automatically notifies the right personnel when service is due. Source: WorkTrek This ensures machinery is maintained at optimal intervals, which reduces the risk of failure and non-compliance. Moreover, WorkTrek enables you to upload and share: Safety rules Reminders for potential hazards in the field PPE requirements LOTO procedures Field workers can access these from anywhere using their phones, ensuring they always have everything they need to complete their tasks safely and efficiently. Ultimately, WorkTrek logs an entire history of upkeep activities, calibrations, and inspection logs in one easily accessible place: Source: WorkTrek So, when an auditor shows up, you’re ready. And you certainly want to be ready, considering that the cost of non-compliance can be severe. Shawn Knowles, SVP, Director of Risk Engineering at MSIG, a commercial insurance provider, outlines the potential risks: “[Risks] include loss of competitive advantage in the market, financial penalties  [...], product recalls [...], loss of revenue, and legal ramifications where the manufacturer could face expensive lawsuits by not complying.” Skipping maintenance and exposing your operation to these risks is simply not worth it. Reduces the Production Line Downtime Equipment breakdowns can halt an entire production line, wasting valuable time, labor, and money in the process. Fortunately, proactive maintenance can prevent these disruptions by identifying signs of wear before failures occur, which will help you maintain consistent schedules and meet delivery deadlines. This is a big win, considering the actual cost of downtime. According to the 2022 ABB survey, plant outages cost industrial businesses an average of $125,000 per hour. Illustration: WorkTrek / Data: ABB The only way to rein in these massive expenses is by prioritizing regular, preventive upkeep. At Ford, they know this very well. In 2020, Ford implemented proactive maintenance across its manufacturing plants, ultimately saving more than €1 million in unplanned downtime. Source: Ford At their Body and Stamping Plant in Valencia, Manufacturing Manager Eduardo Garcia Magraner noticed that machines often slow down before they fail. To address this, he installed performance-monitoring sensors directly on machinery. These sensors track asset efficiency in real time and send alerts to engineers’ phones, warning them when performance drops. Magraner explained why this matters: Illustration: WorkTrek / Quote: Ford As a result, their operations now experience significantly less downtime, saving them time and money. This is why frequent maintenance and inspections matter. They are your first line of defense against disruptions, enabling you to get ahead of potential problems and keep your operations running smoothly. Helps Maintain Product Quality In manufacturing, product quality is directly tied to the performance and precision of your machinery. This is where equipment maintenance plays a major role, keeping machines properly calibrated, ensuring consistent operation, and helping prevent batch-to-batch inconsistencies. It also reduces the risk of product contamination, which is particularly important in highly regulated industries like food and pharmaceuticals. Unfortunately, Novo Nordisk, the company behind the popular weight-loss drug Wegovy and the type 2 diabetes medication Ozempic, learned this the hard way. In May 2022, the FDA flagged serious lapses at its main U.S. manufacturing facility, with one of the major issues being the failure to clean equipment at appropriate intervals. Source: Reuters Ultimately, this allowed microorganisms to build up on machinery used in continuous production, bringing the product quality into question. Despite the severity of the findings, Novo Nordisk saw minimal impact on production and financial performance. However, it could have been much worse. Poor asset maintenance can easily lead to product recalls, which are both financially and reputationally damaging. In 2024, Hexagon surveyed senior quality professionals and manufacturing leaders to understand the true cost of recalls. The findings were shocking, showing that product recalls can cost anywhere between $8 million and $50 million. Illustration: WorkTrek / Data: Hexagon However, the damage isn’t just financial. Respondents also reported they experienced reputational damage, delayed product launches, increased remediation expenses, and much more. Illustration: WorkTrek / Data: Hexagon As a manufacturer, your reputation hinges on the quality of your product. Don’t put that at risk, especially over something as preventable as poor equipment upkeep. Prolongs Equipment Lifespan It’s no secret that manufacturing equipment, like CNC machines, robotics, or conveyor systems, represents a significant investment. If you want to maximize the return on that investment, you’ll look for ways to extend the useful life of your assets. The most effective way to do that is through frequent inspections, cleaning, lubrication, and alignment. The ABB survey we referenced earlier backs this up, revealing that 39% of companies identify extended equipment lifespan as the top benefit of regular maintenance. Illustration: WorkTrek / Data: ABB Take conveyor systems, for example, an indispensable part of most manufacturing operations. They can range from a few thousand dollars for basic setups to millions for complex, automated solutions. Either way, that’s not a small spend and, with a bit of proactive maintenance, you can keep these assets running smoothly for much longer. AJ van Eyssen, National Field Service Manager at Tru-Trac, a company specializing in conveyor system audits, explains why frequent and thorough inspections matter: Illustration: WorkTrek / Quote: International Mining In one recent case, Eyssen’s team was called in to audit a conveyor system that had been breaking down every two weeks. After a detailed inspection, they recommended changes to the impact beds, chutes, and conveyor skating to better align with the operation’s evolving needs. According to Eyssen:   “This has successfully addressed the client’s pain points, with the conveyor system having to date gone for six months without any issues.” That’s a big win that translates to fewer repairs, longer useful life, and more value from your equipment. It all comes down to taking a proactive approach to maintenance. A little attention now can save a lot of time and money down the line. Supports Environmental Responsibility Manufacturing has a significant environmental footprint, and maintenance plays a crucial role in reducing it. It does so in multiple ways: It minimizes emissions from machinery, keeps energy-intensive systems like HVAC operating efficiently, and ensures the safe handling of waste materials such as lubricants and solvents. Stuart Thompson, President of ABB Electrification Service, shares another way maintenance can support your sustainability efforts: Illustration: WorkTrek / Quote: Data Centre Magazine The eco-friendly potential that maintenance has shouldn’t be ignored, especially as manufacturers face increasing pressure from customers, investors, and communities to go green. In fact, the 2023 Fictiv survey found that 87% of industry leaders believe the importance of sustainable manufacturing is increasing. Illustration: WorkTrek / Data: Fictiv Forward-thinking companies are taking this seriously. Take, for instance, The Blender, a factory operated by British juice and smoothie brand Innocent Drinks. They deploy a range of innovative maintenance strategies to meet their ambitious sustainability goals. One example is their use of the robot dog Spot, which monitors asset conditions in real-time. John McGowan, Head of Supply Chain at Innocent, explains: Illustration: WorkTrek / Quote: The Times This helps them catch issues early, extend the life of their equipment, and reduce unnecessary repairs, saving resources and cutting carbon output. Another great example is their pipe cleaning process. Traditional pipe cleaning in factories uses large volumes of water, but Innocent uses Fluivac, a specialized cleaning system that uses air to blast juice residue from equipment. This helps them reduce water usage by 50%. The lesson here is clear: regular maintenance is a powerful way to keep assets in peak condition and support greener operations. And it is bound to have an even bigger role in building a more responsible manufacturing future going forward. Conclusion In the industry where safety, compliance, efficiency, and sustainability all intersect on the factory floor, regular maintenance is what keeps everything together and working smoothly. It’s how you prevent disasters, maintain product quality, and keep meeting your customers’ expectations. So, don’t wait for something to go wrong in order to fix it. Instead, invest in maintenance like your future depends on it—because it does.

Key Takeaways Organizations that implement systematic maintenance tracking achieve a 545% ROI, with every dollar invested in preventive maintenance saving $5 in future costs while reducing unplanned downtime by up to 91%. Prioritizing maintenance based on criticality ensures that 60-70% of resources are allocated to equipment that most significantly impacts operations Modern CMMS platforms automate scheduling, enable mobile work order management, and provide real-time visibility—with 52% of industrial plants now using these systems to transform operations. Picture this: A telecommunications company invests $1 in preventive maintenance and recovers $5.45. That's not a typo. Based on a recent study by Jones Lan LaSalle, companies that implemented preventive maintenance realized a 545% return on investment. Illustration: WorkTrek / Data: MPlus Software Inc. Yet despite these staggering returns, most organizations still struggle with tracking maintenance effectively, leaving millions on the table through unplanned downtime and reactive repairs. The result? According to recent industry data, unplanned downtime costs U.S. businesses over $50 billion annually, with the average manufacturer losing $125,000 per hour when critical equipment goes down. Organizations that master maintenance tracking report 91% improvements in equipment downtime, 12-18% reductions in maintenance costs, and equipment lifespans extended by 20% or more. Understanding the Current Maintenance Landscape Before exploring how to keep track of maintenance in 6 steps, let's first explain why traditional approaches fail. Most organizations rely on outdated methods, like manual paper logs or spreadsheets. This can lead to all your domain knowledge walking out the door when experienced maintenance technicians leave. The statistics paint a sobering picture. According to a recent study, only 24.5% of a maintenance technician's time is actually productive. Illustration: WorkTrek / Data: Plant Services What's going on with the rest? It is generally lost to searching for parts, waiting for equipment access, or dealing with incomplete work orders. Meanwhile, 90% of equipment failures are entirely preventable. They don't happen because equipment simply wears out, but because maintenance tasks are not properly tracked and executed. This reactive approach creates a vicious cycle. When you're constantly fighting fires, there's no time for preventive maintenance tasks. Equipment can degrade more quickly, leading to increased emergencies, higher costs, and frustrated maintenance personnel. How do you break this cycle? It requires a fundamental shift in how we track and manage maintenance work. Step 1: Create a Comprehensive Asset Inventory Always start by creating a full inventory of all of your assets. You can't schedule maintenance for equipment you don't know exists, and you can't prioritize maintenance tasks without understanding the role each piece of equipment plays in your operations. Building Your Asset Database it all starts with conducting a thorough asset discovery process. Walk your facility, and document every piece of equipment that requires regular maintenance. This includes obvious assets like production machinery and HVAC systems, but don't overlook supporting equipment like compressed air systems, electrical panels, or safety equipment. Source: WorkTrek For each asset, capture essential information: Manufacturer, model, and serial numbers Installation or purchase dates Location within your facility Warranty information and service contracts Operating specifications and requirements Historical maintenance records if available You can use digital tools like a CMMS platform to streamline this process. QR codes or RFID tags on equipment enable maintenance technicians to instantly access asset information, maintenance history, and upcoming preventive maintenance schedules directly from mobile devices. This eliminates the guesswork and ensures everyone has access to accurate, up-to-date information. Standardizing Asset Information Consistency is key when building your asset inventory. Establish naming conventions that make sense for your maintenance team. Instead of "Pump 1" and "Pump 2," use descriptive identifiers like "CW-PUMP-01-NORTH" that indicate the system (cooling water), equipment type, number, and location. Create asset hierarchies that accurately reflect the relationships between equipment and your operations. Source: WorkTrek For example, a packaging line might include multiple components, such as conveyor systems, filling equipment, sealing machines, and labeling systems. Understanding these relationships enables maintenance personnel to recognize how individual maintenance tasks affect overall production. If you spend the time creating a comprehensive asset inventory, it pays dividends immediately. Step 2: Assess and Prioritize Based on Criticality Not all equipment is created equal. A critical production line that generates $100,000 in revenue per hour demands different maintenance attention than a backup air compressor in a storage area. This is where you need to assess the criticality of your equipment. Conducting Criticality Analysis When assessing the criticality of assets examine the following factors: Impact on Operations What happens if the equipment fails Can it cause production to fully stop? Are there any safety issues if it fails? Is the equipment associated with any regulatory requirements? One approach is to use a scoring system to objectively rank assets. Many maintenance teams employ the Risk Priority Number (RPN) methodology, multiplying three factors: Severity: Impact of failure (1-10 scale) Occurrence: Likelihood of failure (1-10 scale) Detection: Difficulty of detecting problems before failure (1-10 scale) For example, a main production conveyor might score: Severity: 9 (production stops) Occurrence: 4 (occasional issues) Detection: 3 (problems usually visible) RPN = 9 × 4 × 3 = 108 Compare this to a backup ventilation fan: Severity: 2 (minor comfort issue) Occurrence: 2 (rare failures) Detection: 5 (hidden from view) RPN = 2 × 2 × 5 = 20 The higher RPN indicates where maintenance resources should be focused. Creating Maintenance Priority Tiers Based on criticality scores, organize assets into tiers: Critical Assets: These represent your highest priority for preventive maintenance tasks. Failure can cause significant operational, safety, or financial impact. You should implement a comprehensive preventive maintenance program, condition monitoring, and possibly redundant systems. The ideal approach is to allocate 60-70% of your maintenance resources here. Essential Assets: This equipment is important for smooth operations, but it is also available with workarounds or backup systems. Equipment in this category receives regular preventive maintenance, but with longer intervals between inspections. The ideal approach is to dedicate 20-30% of resources to this tier. Non-Critical Assets: These assets would have minimal impact on operations if they fail. These might operate on a run-to-failure strategy or receive only basic preventive maintenance. Here, you might want to limit resource allocation to 10% or less. This tiered approach can keep your maintenance team focused on efforts that matter the most. Step 3: Develop Tailored Maintenance Strategies Now that your assets have been identified and prioritized, it's time to develop specific maintenance strategies. These strategies should be catered to each equipment category. The key is matching the right maintenance approach to each asset's criticality, failure patterns, and operational requirements. Choosing the Right Maintenance Type Time-Based Maintenance: Schedule maintenance tasks at fixed calendar intervals—daily, weekly, monthly, or annually. This approach works well for equipment with predictable wear patterns or those subject to regulatory requirements. Source: WorkTrek Some examples of time-based maintenance include monthly filter changes, annual safety inspections, or quarterly lubrication of bearings. Time-based maintenance forms the backbone of most preventive maintenance schedules. Usage-Based Maintenance: This is when maintenance tasks are triggered based on equipment usage. For instance, this could be operating hours, production cycles, or mileage. Source: WorkTrek An injection molding machine may require maintenance every 10,000 cycles, while a fleet vehicle typically needs service every 5,000 miles. This approach keeps maintenance tasks aligned with the actual wear of the equipment. Condition-Based Maintenance: This is when maintenance technicians monitor the condition of equipment through regular inspections or the use of sensors. Equipment is then scheduled for maintenance when indicators show degradation. Illustration: WorkTrek / Data: Number Analytics Vibration analysis on rotating equipment, oil analysis for hydraulic systems, or thermographic inspections of electrical panels can identify issues before failure occurs. This approach can optimize maintenance timing and reduce unnecessary maintenance tasks. Predictive Maintenance: Leverages advanced analytics and IoT sensors to forecast failures before they happen. Predictive maintenance analyzes patterns in temperature, vibration, pressure, and other parameters to identify subtle changes indicating impending problems. Illustration: WorkTrek / Data: Oxmaint While this requires more sophisticated equipment and technology, studies show that predictive maintenance can reduce maintenance costs by 20-25% compared to preventive approaches alone. How to Create a Detailed Maintenance Plan If you run a maintenance organization, you need a detailed maintenance plan. Here is how to create one: Task Procedures: These are the step-by-step instructions for completing maintenance work safely and effectively. Don't always assume knowledge. Document everything from lockout/tagout procedures to torque specifications. Illustration: WorkTrek / Data: Coast Resource Requirements: List necessary tools, parts, and materials. Include part numbers, quantities, and storage locations. This approach minimizes downtime while technicians search for resources. Skill Requirements: Specify required certifications, training, or technical skills. Some tasks might require licensed electricians, certified welders, or specialized vendor technicians. Time Estimates: Do your best to provide realistic durations for maintenance tasks. You can do that by using historical data to understand time estimates per task better. This helps maintenance planners to collaborate with production schedules and allocate resources appropriately. Safety Procedures: Source: WorkTrek Your plan should also include detailed information about the required personal protective equipment, safety protocols, and potential hazards. Never compromise safety for speed or convenience. Step 4: Implement Systems and Technology Stop using paper-based maintenance tracking. All successful maintenance organizations have one thing in common: They understand how to use technology tools to improve their operational efficiency. Digital systems can streamline the complexity of scheduling maintenance tasks, tracking work orders, managing inventory, and analyzing performance. This is where a Computerized Maintenance Management System (CMMS) becomes invaluable. Selecting the Right CMMS Platform Today's preventive maintenance software market offers solutions for every organization size and industry. 52% of industrial plants now utilize CMMS systems, and 95% report positive ROI. When evaluating options, consider: Core Functionality: At a minimum, your CMMS should handle work order management, preventive maintenance scheduling, asset tracking, and inventory management. Look for systems that automate routine tasks, such as generating work orders based on maintenance triggers or sending notifications when maintenance tasks are due. Mobile Accessibility: Source: WorkTrek With maintenance technicians spending most of their time in the field, having a CMMS product with an easy-to-use yet functional mobile app is non-negotiable. Technicians should be able to receive work orders, update task status, notifications, access equipment manuals, and record findings directly from smartphones or tablets. Integration Capabilities: Your CMMS shouldn't exist in isolation. Integration with enterprise resource planning (ERP) systems, production scheduling software, and IoT platforms creates a unified maintenance ecosystem. Source: WorkTrek User Experience: You want a system that your maintenance team wants to use. When evaluating systems, prioritize intuitive interfaces, logical workflows, and minimal training requirements. Implementation Best Practices Having a good implementation process can improve the chance of success for your organization. We suggest you consider the following phased approach: Phase 1 - Foundation (Months 1-2): Start with basic functionality. Import your asset database, set up user accounts, and begin tracking reactive maintenance through digital work orders. This allows teams to familiarize themselves with the system without overwhelming them. Phase 2 - Preventive Maintenance (Months 3-4): Add preventive maintenance schedules for critical equipment. Set up automated work order generation based on your maintenance triggers, calendar dates, meter readings, or condition thresholds. Begin tracking preventive maintenance compliance rates. Phase 3 - Optimization (Months 5-6): Expand features to include inventory management, detailed reporting, and performance analytics. Integrate with other internal systems and refine workflows based on user feedback. Add mobile access for field technicians. Phase 4 - Advanced Features (Months 6+): Implement predictive maintenance capabilities, advanced analytics, and continuous improvement processes to drive operational efficiency. By this stage, the system should be fully embedded in daily operations. WorkTrek CMMS, for example, follows this implementation philosophy, enabling organizations to start simple and scale functionality as teams become comfortable. You can very easily enable or disable features that are visible to the users. The platform's intuitive design means maintenance teams can begin logging work orders within hours, not weeks, while its comprehensive feature set supports long-term growth. Training and Adoption Strategies Technology alone isn't enough to solve all your maintenance solutions. You need staff members who are well-trained and can efficiently manage tasks. This means that you should invest heavily in training and support to ensure successful adoption: Create role-specific training programs. Maintenance technicians need different skills from maintenance planners or managers. Tailor training to each group's responsibilities and system interactions. Identify champions within your maintenance team. These early adopters can offer peer support, share best practices, and assist in troubleshooting issues. Provide ongoing support through multiple channels—documentation, video tutorials, in-app guidance, and help desk support. Remember, even experienced technicians might struggle with new technology initially. Keep track of metrics. Monitor login rates, work order completion times, and mobile app usage. Low adoption in specific areas indicates where additional training or system refinement might be needed. Step 5: Execute and Track Work Orders Systematically Once systems are in place and maintenance strategies have been defined, shift your focus to execution. This is where the proverbial rubber meets the road. Create Effective Work Orders Well-structured work orders are the backbone of maintenance operations. They communicate what needs to be done, when, by whom, and with what resources. Source: WorkTrek What should be included in every work order? Clear Descriptions: Specify exactly what maintenance work needs to be performed. Creating a work order that says "Check equipment" is insufficient. A good example is: "Inspect conveyor belt tension, adjust to 50 PSI if outside 48-52 PSI range" provides actionable guidance. Priority Levels: Source: WorkTrek Every work order should have a priority level. Emergency: Safety hazard or production stopped Urgent: Production impaired, complete within 24 hours Normal: Scheduled maintenance or minor issues Deferred: Can be bundled with future maintenance Resource Allocation: Define and assign tasks based on technician skills, availability, and workload. Also, don't just assign all electrical work to a single senior technician. You want to develop skills across the team to develop expertise. Required Parts and Tools: List everything needed to complete the job. This prevents technicians from starting work only to discover missing components, wasting time and creating incomplete maintenance tasks. Managing Work Order Flow Start by implementing a standardized workflow that moves work orders efficiently from creation to completion: Request and Review: Anyone should be able to request maintenance, but these requests need to be reviewed before they become work orders. Maintenance planners or managers verify the issue, determine priority, and identify required resources. Planning and Scheduling: Coordinate maintenance activities with production schedules to minimize disruption. Bundle related tasks when possible. If you plan on shutting down a line for one repair, complete all pending maintenance work on that equipment. Assignment and Dispatch: Assign tasks to appropriate technicians with clear completion expectations. Modern CMMS platforms, such as WorkTrek, can automate assignments based on skills, location, and availability. Execution and Documentation: Technicians should complete assigned tasks and document their work thoroughly. Record actual time spent, parts used, problems encountered, and recommendations for future maintenance. Also include any time utilized on an asset by external contractors. This historical data proves invaluable for identifying trends and optimizing maintenance schedules. Review and Closure: Maintenance managers review completed work orders for quality and completeness. Look for patterns to help identify recurring issues and perform root cause analysis. Real-Time Tracking and Communication Modern maintenance operations demand real-time visibility. Maintenance managers need to know what's happening now, not what happened yesterday. CMMS platforms enable this transparency: Mobile updates from technicians provide instant status changes and notify maintenance managers. When a critical repair takes longer than expected, managers can adjust schedules and communicate with operations immediately. Dashboards in maintenance shops and control rooms display the current work order status, technician locations, and upcoming scheduled maintenance activities. This visibility enables teams to coordinate their efforts and identify potential resource conflicts. Automated notifications keep stakeholders informed. When preventive maintenance tasks are generated, assigned technicians receive alerts. When critical equipment returns to service, operations gets notified automatically. Step 6: Measure Performance and Continuously Improve You can't improve what you don't measure. The final step in effective maintenance tracking involves establishing metrics, analyzing performance, and implementing improvements based on data-driven insights. Key Performance Indicators for Maintenance Focus on metrics that drive meaningful improvement in maintenance operations: Mean Time Between Failures (MTBF): Measures the average time between equipment failures. Increasing MTBF generally indicates improving reliability. Track this for critical assets to validate the effectiveness of your preventive maintenance program. Mean Time to Repair (MTTR): This metric tracks the average time to restore equipment to operation. Decreasing MTTR might indicate better training, improved parts availability, or more effective maintenance procedures. Preventive Maintenance Compliance (PMC): PMC measures the percentage of scheduled preventive maintenance tasks completed on time. World-class organizations achieve 90% or higher. Low compliance often predicts future reactive maintenance increases. Planned Maintenance Percentage (PMP): PMP is the ratio of planned to total maintenance hours. Leading organizations achieve 80-90% planned work. Higher percentages indicate proactive maintenance management and better resource utilization. Source: WorkTrek Overall Equipment Effectiveness (OEE): Combines availability, performance, and quality metrics. While primarily an operational metric, maintenance has a significant impact on the availability component. Source: WorkTrek Maintenance Cost as Percentage of Replacement Asset Value (RAV): Typically 2-5% for most industries. Higher percentages may indicate aging equipment that requires replacement or inefficient maintenance practices. Future Trends in Maintenance Management The maintenance field is evolving rapidly, mainly driven by technological advancements and changing business demands. Some of the technologies changing the maintenance industry include: Digital Twins and Simulation Digital twins are virtual replicas of physical assets. This enables maintenance teams to simulate different scenarios without risking actual equipment. Illustration: WorkTrek / Data: Anvil Labs It also enables maintenance teams to test maintenance strategies virtually, predict the impact of failures, and optimize maintenance intervals. As IoT sensors become ubiquitous, digital twins are projected to be used by 70% of manufacturers by 2025. Augmented Reality Support AR technology overlays digital information onto physical equipment. This guide helps maintenance technicians navigate complex procedures. Illustration: WorkTrek / Data: Cornell University Imagine pointing a tablet at a pump and seeing maintenance instructions, torque specifications, and historical failure points overlaid on the actual equipment. Autonomous Maintenance Machines increasingly maintain themselves. Self-lubricating bearings adjust oil flow based on temperature and load. Smart filters initiate replacement orders when pressure differentials indicate clogging. While human oversight remains important, autonomous maintenance will handle routine tasks, freeing technicians to focus on more complex work. Sustainability Integration Illustration: WorkTrek / Data: Eptura Maintenance organizations cannot ignore environmental considerations. Some key metrics to track include energy consumption, the use of environmentally friendly lubricants, and efforts to support the organization's sustainability goals. Conclusion Transforming maintenance from a reactive state to a proactive one is required for success. The six-step framework provides a clear path: identify your assets, apply tailored strategies, leverage technology, manage work orders, measure performance, and continually improve. The payoff extends beyond cost savings, as studies indicate that companies using CMMS report up to 78% longer equipment life and 60% fewer safety incidents. Modern platforms like WorkTrek make this transformation accessible with cloud, mobile, and intuitive tools. Each step compounds into reliability, safety, and efficiency. The tools exist, the results are proven. The only question left is: when will you begin?