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AI/ML Based Predictive Maintenance

What is Predictive Maintenance?

Today’s maintenance teams are leveraging INDUSTRY 4.0 driven PdM to bring digital transformation to their maintenance practice.

Predictive maintenance (PdM) is maintenance that measures the performance and condition of equipment of in-service equipment during normal operation to identify any faults developing. It provides cost savings and better reliability over routine or time-based preventive maintenance.

Where Should I Use It?

Planned (PM)

For assets whose failures modes increases with time or use and can be prevented with regular maintenance e.g. valves.

Predictive (PdM)

For assets whose failures modes increases with the condition of operation and can be prevented with monitoring/measurements e.g. rotating and reciprocating.

Reliability Centered (RCM)

For assets whose failures modes are identifiable and controllable e.g. aircraft engines , large turbines.

Where Does It Fit in Your Maintenance Strategy?

Common PdM Tools

Root Cause Analysis (RCA) Makes PdM Even More Powerful

The goal of predictive maintenance is to measure equipment condition and then predict its failure, followed by a root cause analysis and then preventing the failure through corrective maintenance.

Now is the right time to change how we sense, predict and troubleshoot machine failures

IIoT sensor technology has made it possible to measure machine condition parameters like vibration, ultrasound, temperature, etc affordably and without human intervention. Machine-learning models can increase the accuracy of the predictions and make it easy for the maintenance team to run the program across a large number of equipment with minimal knowledge of condition monitoring techniques.


Affordable sensor and microcontroller technologies.


IoT is making sensor connectivity easier, secure and more reliable.


Machine Learning (ML), Artificial Intelligence (AI) and Bi Data are making predictions possible.

Benefits of IoT and ML driven digital transformation in maintenance