What is Condition-Based Monitoring and Maintenance?

All too often, maintenance action is based on one of two factors: a rigid schedule or equipment failure. Under these plans, maintenance often occurs too early (i.e., the preventive, scheduled replacement of a component, even if it is still in good working order) or too late (i.e., the aforementioned equipment failure). Each of these approaches leads to waste:

• In a purely preventive maintenance approach, resources and parts are consumed whether or not they are needed

• In a purely reactive approach, costly downtime and extensive repairs are necessary

The solution — a way to reduce these wasteful efforts — is condition-based monitoring (CBM), a maintenance strategy based on monitoring and reacting to the performance state of equipment, with the goal of remedying possible failures well before they lead to equipment shutdowns. Condition-based maintenance is facilitated by ongoing, real-time monitoring of key performance metrics, such as vibration and temperature, as well as by connectivity and communication that allows for data collection and performance alerts to drive maintenance activity.

A condition-based maintenance system will include industrial sensors, network communication infrastructure, data collection and analysis software, computerized maintenance management systems (CMMS) and more — all based on IIoT (Industrial Internet of Things) principles and data-driven decision-making.

According to the U.S. Department of Energy, predictive and condition-based approaches can reduce maintenance costs by 25–30%, eliminate breakdowns by 70–75%, and reduce downtime by 35–45% when properly implemented. 

CBM sits between preventive and predictive maintenance — offering the responsiveness of real-time monitoring with the foresight of predictive models. This makes CBM a core component of a broader reliability centered maintenance framework — one that balances proactive insights with practical execution. 

How do manufacturers benefit from condition monitoring?

Implementing a condition-based maintenance plan offers manufacturers a proactive approach to equipment upkeep, leading to significant operational and financial benefits: 

Reduction or Prevention of Asset Failures 

Condition-based maintenance is specifically designed to detect the beginnings of potential equipment problems, well before they become production problems due to equipment failure. By reducing or eliminating purely reactive tactics, equipment is optimized and operational more of the time. 

Increased Uptime 

With a condition-based maintenance strategy, planned downtime can be scheduled more effectively, leading to measurable increases in productivity. By addressing issues before they result in failures, manufacturers can maintain continuous operations and meet production targets more reliably. 

A McKinsey report estimates that predictive and condition-based maintenance strategies can reduce machine downtime by 30% to 50%, significantly enhancing operational efficiency. 

More Efficient Use of Maintenance Resources 

Unlike time-based maintenance, condition-focused approaches rely on actual equipment data — not just cycles or calendars. This data-driven method ensures that maintenance tasks are performed only when necessary, reducing unnecessary maintenance activities. 

This improves labor use, reduces excess parts orders and keeps the maintenance team focused where they’re needed most.  

Greater Insight into Equipment Health 

Data is the backbone of condition monitoring. Comparing historical benchmarks against live performance data enables real-time alerts when abnormalities arise. This continuous monitoring enables maintenance teams to forecast potential failures and understand root causes more rapidly. 

With the right analytics dashboard, teams can forecast failure timelines and understand root causes faster. Enhanced visibility into equipment health allows for informed decision-making, aligning with reliability-centered maintenance principles that prioritize system reliability and performance. 

Reduced Environmental Impact 

CBM supports sustainability goals by limiting waste through fewer unnecessary maintenance activities, optimized energy usage and reduced material consumption. By ensuring equipment operates efficiently and only servicing it when needed, manufacturers can lower their environmental footprint. 

This approach not only conserves resources but also aligns with corporate social responsibility initiatives focused on environmental stewardship. 

Improved Maintenance Cost Management 

The financial impact is clear: maintenance costs decrease with fewer surprise breakdowns and better resource planning. By addressing issues proactively, manufacturers can avoid costly emergency repairs and extend the lifespan of equipment. 

For example, a study highlighted that predictive maintenance strategies could lead to a 25% reduction in maintenance costs, showcasing the economic advantages of transitioning from reactive to proactive maintenance models. 

More Accuracy in MRO 

Data from condition-based maintenance software also allows for increased accuracy and effectiveness in inventory practices including MRO ordering and management. By understanding the actual condition of equipment, organizations can better predict the need for spare parts, reducing inventory holding costs and ensuring the availability of critical components when needed. 

This precision in inventory management prevents overstocking and stockouts, leading to more streamlined operations and cost savings. 

How does condition-based maintenance work?

Condition monitoring uses connected industrial sensors to continually monitor performance aspects that are known to be failure-mode indicators. This proactive approach enables real-time visibility into asset health and supports data-driven decision-making to prevent unplanned downtime.

The list of potential areas to monitor is extensive, but some of the most common are listed below:

• Vibration monitoring: Vibration monitoring can be used on any rotating part and is an effective indicator of potential equipment malfunctions or maintenance issues. Sensors are able to detect even slight fluctuations in vibration levels that may indicate part wear, improper calibration, damage or other issues — which can then be investigated and remedied.

• Temperature monitoring: Most equipment operates at a consistent temperature. Temperatures that are higher than normal can indicate increased friction in moving parts, which can lead to premature wear and equipment failure. By sounding an alert if the temperature rises outside an acceptable range, these failures are now preventable.

• Ultrasonic monitoring: Sound is an excellent indicator of equipment performance. Ultrasonic monitoring takes sound detection to the next level. By using sensors that can detect high-frequency sounds that cannot be heard by the human ear, leaks and holes in equipment such as hoses and tanks can be zeroed in on right away.

• Pressure monitoring: Pressure monitoring provides a constant, real-time assessment of fluid and air pressure in hoses, tanks, compressors and other key equipment. It offers real-time access and the ability to sound an alert at even the slightest pressure drop.

• Thermographic testing: Thermographic testing uses infrared sensors to measure the amount of heat emitted from electrical components. As these components begin to wear, electrical resistance will start to increase, which in turn leads to an increased amount of heat generated at these wear points. Thermographic testing allows these signs of wear to be detected and addressed early.

• Oil analysis: Oil analysis uses sensors to gauge the composition and wear of engine oil, detecting issues that could lead to improper lubrication and damage to engine components. In oil analysis, sensors can monitor the pH level of oil, as well as the presence of excessive water, coolant and other unwanted materials. With these sensors, personnel can have a definitive indication of when oil should be changed.

Role of edge and cloud platforms

Edge computing enables local data filtering and alerting, while cloud platforms aggregate large datasets across facilities for trend analysis. This architecture reduces network latency, improves real-time responsiveness and enables broader performance benchmarking across multiple production sites. 

These systems feed data into a CMMS to trigger maintenance task creation or escalation when thresholds are exceeded. Automation minimizes manual oversight and ensures that the right actions are assigned to the right personnel — with time-sensitive alerts reducing the risk of unnoticed asset degradation. 

Example: A temperature spike above baseline in a gear reducer triggers a CMMS ticket, prompting inspection before failure occurs. 

What are condition monitoring sensors?

Machine condition monitoring sensors track primary machine maintenance indicators, such as the state of vibration, temperature and motor functions — detecting the earliest beginnings of the failure-mode indicators mentioned above.

Industrial sensors constantly track machine health — around the clock, 24/7/365 — and provide real-time data and alerting, enabling a higher degree of certainty in predictive maintenance. The connected nature of sensors enables remote monitoring from anywhere, allowing facilities to manage their machine assets from any location.

Sensor categories

• Mechanical – Vibration, force, ultrasonic sound 

• Thermal – Temperature, infrared thermography 

• Fluid-Based – Pressure, oil analysis, viscosity, chemical contamination 

Each is designed for specific roles in equipment maintenance: 

• Thermal sensors are ideal for HVAC and electrical systems. 

• Vibration sensors are commonly used in motors and rotating equipment. 

• Oil sensors suit industries like manufacturing, transportation and mining. 

Sensor Performance Best Practices 

Calibration is essential for sensor accuracy. Improper calibration leads to false alarms or missed faults. As part of regular maintenance protocols, calibration schedules should align with OEM recommendations and sensor drift data to ensure optimal reliability. 

Sensor data should be integrated with the CMMS and analytics dashboards to enable maintenance personnel to take informed and timely action. Integration enables automated workflows, escalations and alert prioritization — reducing human error and increasing operational agility. 

Remote Monitoring Benefits 

Sensors enable 24/7/365 remote visibility. This supports decentralized teams and helps ensure real-time alerts reach the right people, wherever they are. Remote monitoring also improves safety by reducing the need for manual inspections in hazardous or hard-to-access areas. 

Key challenges and considerations when implementing CBM

While the advantages of CBM are compelling, implementation requires upfront planning and strategy. 

Initial Investment 

Sensors, connectivity infrastructure and integration with platforms like CMMS or ERP systems can require significant upfront cost. Organizations must account for not just hardware, but also software licensing, network upgrades and long-term support contracts when budgeting for CBM. 

Staff Training & Change Management 

Technicians and operators must be trained on data interpretation, alert handling and new workflows — a shift from traditional maintenance strategy norms. This often requires a cultural shift toward proactive decision-making and collaboration across departments, especially when integrating digital tools into legacy workflows. 

Setting KPIs & Thresholds 

Choosing the right metrics is essential. Improperly set thresholds can lead to false alarms or missed failures. Maintenance teams should pilot threshold settings and refine them based on historical asset behavior, severity levels and business-critical outcomes. 

Integration with Existing Systems 

CBM must be compatible with current software stacks to ensure a seamless workflow. Without proper integration, alerts and insights may become siloed — reducing response time and complicating execution of maintenance plans. 

Data Overload Risk 

Too much data without the right tools leads to confusion. Visualization and AI-powered analytics tools help interpret what matters. Raw sensor data must be filtered and contextualized through asset-specific algorithms to generate relevant insights and reduce signal noise. 

Dashboards that consolidate KPIs and automate alerts streamline execution for your maintenance team. These interfaces should be customizable, mobile-accessible and integrated with user roles to ensure the right people receive the right alerts at the right time. 

Condition monitoring of machines from ATS

As part of our predictive maintenance services, ATS uses the latest machine health monitoring technology to keep maintenance personnel and operations teams updated in real-time about asset health and potential failures through our cloud-based analytics platform and reliability engineer expert support. Our technology-driven approach to maintenance helps you eliminate unplanned downtime and reduce costs. 

Reliability 360® helps organizations move from reactive to truly proactive maintenance. 

Features of Reliability 360® include: 

• 24/7 asset condition monitoring 

• Real-time alerts integrated with your CMMS 

• Expert reliability engineer support 

• Actionable insights via cloud-based dashboards 

• Remote visibility into asset health 

• Integration with broader asset management platforms 

Reliability 360® aligns with IIoT principles — helping operations unlock smarter, more efficient maintenance across facilities.  

Want to see how it works?

Not all condition monitoring solutions are created equal. Learn more about the value Reliability 360® Machine Health Monitoring can bring to your operations below. Ready to get started? Contact us today.

Next Post

What is Plant Maintenance?