The use of predictive maintenance software originally grew out of the car industry as a way for automating the replacement of car parts. This article takes a look at the background of these types of maintenance software and current usage trends.
Predictive maintenance software was originally developed as a way of analyzing and determining when components were actually going to fail. The idea is that preventative maintenance can then be actioned to replace the components before they fail, possibly causing more damage (e.g. scheduled replacement of the fan belt on your car).
Each component on any machine, electronic or mechanical, has its own pre-determined life span potential based upon how it is normally treated, the environment in which it is used and its running (how often it is operational). The real goal of maintenance software is to use historical data of component failures, along with statistical analysis to take the guess work out of when components will begin failing.
The next step in this software is the automatic notification of imminent failures to engineers. These can even generate work tickets/orders by paper, via email/text or using other systems for any planned maintenance work that is ongoing.
The benefit of using such software is that the amount of failures are considerably limited/reduced, as is the amount of systems downtime. Automating work orders can also streamline the smooth operations of a business without the need for excessive human intervention.
The latest trend in predictive maintenance is to incorporate these tools with preventative maintenance software. For example, in expensive mainframes and server systems they frequently have backup components installed from day one which the maintenance can use up to its predicted failure date then invoke its own PC maintenance software to shut down the used component (e.g. drives/RAM) and switch over all processing to the fresh component.