Predictive maintenance, or condition-based maintenance, is maintenance that monitors the performance and condition of equipment during normal operation to reduce the likelihood of failures. By performing periodic (offline) or continuous (online) equipment condition monitoring, the ultimate goal of the approach is to perform maintenance at a scheduled point in time when the maintenance activity is most cost-effective and before the equipment loses performance within a threshold.

In order to predict these failures, it’s necessary to analyze the data that is generated by sensors, vibrations, CMMS, etc. Predictive data analytics is aimed at making predictions about future outcomes based on historical data and analytics techniques such as statistical modeling and machine learning.

Predictive maintenance relies on condition monitoring, which is the continuous monitoring of machines during process conditions in order to ensure the optimal use of machines. There are three facets of condition monitoring: online, periodic and remote.

Online condition monitoring is defined as the continuous monitoring of machines or production processes, with data collected on critical speeds and changing spindle positions. Periodic condition monitoring is achieved through vibration analysis. Remote condition monitoring allows equipment to be monitored from a remote location, with data transmitted for analysis.

The monitoring of your assets and processes through predictive analytics can 

  1. produce actionable responses through a CMMS program and 
  2. let you assess the condition of parts and the presence of defects previously impossible to detect.

With a CMMS program and monitoring system, you are able to automatically generate work orders based on the data collected and the triggered responses to that data. If a sensor picks up a defective reading on a bearing, for example, a work order can be generated and sent to the proper technician to check on the problem immediately.

There are also AI tools available, such as Proteus’ “Ask Steve” chatbot, which allow you to converse with your maintenance data in real-time to discover patterns and trends in your data and asset condition.

Predictive analytics tools give users deep, real-time insights into an almost endless array of business activities. Tools can be used to predict various types of behavior and patterns, such as how to allocate resources at particular times, when to replenish stock or the best moment to launch a marketing campaign, basing predictions on an analysis of data collected over a period of time. 

For more information please contact us at +1 (262) 241-3845, email us at, or sign-up for a Free Live Demo.