Predictive Maintenance Management

Predictive Maintenance CMMSeWorkOrders Predictive Maintenance Program empowers organizations with additional tools to create more accurate predictions on when a piece of equipment will require maintenance or replacement. Predictive Maintenance is a condition-based maintenance program where assets are monitored with sensor devices that supply data about the asset’s operation and possible defects. The data is used to predict when the asset will require maintenance or replacement. 


eWorkOrders CMMSS software solution will automatically create a work order when it detects that an asset has fallen outside of the defined parameters.  Alerts will be sent to the maintenance team to assess and repair the issue. With the alerts being identified and sent directly to the technicians in real-time, the elimination of extensive downtime is minimized.

What is Predictive Maintenance

Predictive maintenance (PdM) is a proactive maintenance strategy that tracks and monitors the performance and condition of equipment during normal operation. These monitoring tools detect various deterioration signs, anomalies, and equipment performance issues.  Based on these measurements, maintenance work can be done just before a failure happens. 

Predictive vs. Preventive Maintenance

Predictive Maintenance monitors the performance and condition of equipment during normal production operations. Predictive Maintenance estimates the exact moment of a failure, and repairs can be scheduled when necessary. This is a cost-effective approach with minimal impact on production.

Preventive Maintenance tasks are completed based on a recurring time schedule or a given amount of usage or cycles. A planned and scheduled maintenance routine is put in place to extend the life of assets and reduce downtime. The maintenance is performed on predetermined assumptions, based on manufacturers’ recommendations or history

Predictive Maintenance Objective

The main objective of Predictive Maintenance is to first predict when equipment failure might occur (based on certain factors), and be able to prevent the failure with regularly scheduled and corrective maintenance. 

How Predictive Maintenance Works

Predictive Maintenance depends on condition monitoring, which collects and analyzes data from the machine during operations, to ensure the optimal use of equipment. 

There are three main elements that allow PdM to track asset conditions and alert technicians about projected equipment failures:

  • With real-time tracking, each piece of equipment is monitored through installed and fitted sensors that capture data about equipment deterioration and performance.
  • Internet of Things (IoT) technology collects and shares the data enabling the assets to communicate, work together, analyze data, and recommend appropriate action to be taken directly based on how the system is set up. 
  • Predictive Data collected is analyzed using predictive algorithms that identify trends when an asset will require repair, servicing, or replacement.

Predictive Maintenance/Condition Monitoring Techniques 

There are numerous condition-monitoring devices and techniques that can be used for effectively predicting failure, as well as providing advanced warnings for maintenance teams.  Some of them include:

Thermography/Temperature Measurements/Infrared Thermography is the measurement of heat patterns in machines and objects.  Infrared cameras are able to detect high temperatures (hotspots) in equipment.

Ultrasonic Monitoring/Acoustic Analysis/Airborne Ultrasonics. monitors  equipment, bearings, and rotating parts and uses high-frequency sound waves to detect part defects such as leaks, faulty gears, and other conditions such as lack of lubrication

Vibration Analysis/Dynamic Monitoring is primarily used for high-speed rotating equipment.  Vibration analysis provides technicians the ability to monitor a machine’s levels and patterns of vibration signals within a component, machinery, or structure, and use this information to analyze how healthy the machines and their components are.

Oil Analysis/Tribology gives technicians the ability to check the oil’s condition and determine if other particles and contaminants are present.

Laser Interferometry measures changes in wave displacement based on a laser-generated, highly accurate wavelength of light. 

Motor Circuit Analysis is a set of computerized tests on an electric motor to determine the motor’s overall condition, health, and possible sources of potential failures.

Radiography/Radiation Analysis/Neutron Radiography uses radiation imaging to view and identify internal defects in equipment and parts. This technique helps in locating and quantifying defects and degradation in material properties that would lead to failures.

What Circumstances Call For Predictive Maintenance?

Predictive maintenance (PdM) applications include those that: possess a crucial operational role and possess failure modes that are reasonably predictable with routine monitoring.

Some applications that predictive maintenance is not appropriate for include those that don’t perform a critical task and do not have a cost-effective predictable failure mode.

Who Uses Predictive Maintenance?

In general, a maintenance manager and maintenance team monitor impending equipment failure and repair tasks using predictive maintenance technologies and asset management systems.

A Few Examples of Predictive Maintenance

Prevention of Power Outages

Power outages can be extremely inconvenient for those affected, and they can even be fatal in places like hospitals or assisted care facilities. They can be prevented by using predictive maintenance technology, which allows for early detection. Using cloud-based computers and artificial intelligence, sensors offer information into assets. Companies in the energy sector are informed by this knowledge when equipment failure is most likely to occur.

Building Management

With the aid of environmental monitoring and software for ventilation and energy management, buildings can be managed and controlled remotely. By using sensors tailored to the desired result, owners and managers can also control the temperature of the building environment and monitor humidity or moisture. The sensors provide the data to cloud-based data analysis tools, which enable you to spot anomalies or changes over time and schedule maintenance as necessary. This kind of monitoring can reduce the building’s overall energy costs.

Building Management

Since a manufacturing plant tends to have many costly assets and valuable equipment, they might invest in infrared imagers to monitor aspects of assets, such as temperature, to prevent overheating. This predictive maintenance system helps plants avoid overusing essential equipment, pushing machinery to the point of disruptive breakdowns.


  • Fewer asset failures result in reduced downtime.
  • Reduced total labor time and cost spent on equipment maintenance.
  • Automatic insights into your data.
  • Control of spare parts inventory.
  • Improves worker and environmental safety.
  • Increases employee efficiency.
  • Increases production and ROI with properly maintained equipment.

Remote Monitoring

Automatically taking readings and entering them into eWorkOrders is possible by connecting an IoT sensor device to your equipment. When conditions fall outside the set parameters, a work order is generated and sent to a technician for an inspection or repair.


Sensor readings can be used to display graphs or exported into a spreadsheet for a specific date range. Reports for detailing predictive maintenance work orders and asset history are easily generated.

Additional Expense

Depending on your needs, implementing a Predictive Maintenance Program requires some additional purchase of hardware, such as equipment for monitoring assets: Vibration, Thermography, Oil Analysis or Ultrasonic.

Implementing a Predictive Maintenance Program in your facility requires additional employee training on the use of the equipment and interpreting the analysis.

Predictive Maintenance and CMMS

As businesses move from reactive to proactive to predictive maintenance, computerized maintenance management software (CMMS) plays a critical part to help facilitate predictive maintenance.

To be successful PdM requires the right balance of technology and human interaction.  CMMS makes the process easier and here is why:

  • CMMS is the engine that drives the PdM functionality. All of the information on asset performance that has been gathered and stored throughout the years in your CMMS is a starting point and the initial dataset before PdM implementation. 
  • CMMS integrates with PdM technology to generate alerts and work orders. With condition-monitoring sensor integration, some CMMS can automatically create an alert or generate a work order whenever sensors detect that an asset is operating outside predefined parameters. These alerts prompt the maintenance team to take preventive actions before the machine fails and causes unexpected downtime.
  • CMMS is a centralized system that gathers and stores all of the information into one centralized platform that is accessible at any time from anywhere.

Predictive Maintenance and Return on Investment (ROI)

Implementing a predictive maintenance program requires a significant investment in money, resources, and training.  In taking these things into consideration the initial investment into predictive maintenance’s return on investment (ROI) far outweighs any of these costs.

The reasons why:

  • Reactive maintenance costs, resource time, loss of productivity, inventory backlog, delays in production, equipment downtime, and more are all hitting your bottom line.
  • Having access to more accurate data gives you the ability to extend equipment life and improve the efficiency of maintenance operations.

eWorkOrders CMMS Predictive Maintenance

Predictive Maintenance (PdM) gives you the ability to predict failures and monitor performance on your most important assets.  While the costs of investing in PdM technology may seem to be very high, over time this solution can provide significant ROI cost savings and better machine performance. 

Linking the condition monitoring data to your CMMS allows for quicker dispatching of technicians, making it easier for repairs to get done faster. With eWorkOrders CMMS Predictive Maintenance you can define equipment operation boundaries, import the readings, graph results and automatically trigger an email to generate a work order when the readings go outside of the set boundaries.   Having all of your data stored within a CMMS can help improve asset reliability, reduce costs and increase the efficiency of your maintenance operations.

If you are interested in learning about Predictive Maintenance or any of the other CMMS features, please feel free to contact one of our account executives, who will answer your questions and provide you with a free demo.



GetApp Category Leader Award for CMMS, Preventive Maintenance, Fixed Asset Management, Work Order, Fleet Maintenance, and Facility Management      #1 Rated Maintenance System for CyberSecurity      Capterra Shortlist Award for CMMS, EAM, Asset Tracking, Fixed Asset Management, Fleet Maintenance, Facility Management, Field Service Management, and Preventive Maintenance