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Predictive maintenance is a maintenance strategy driven by predictive analytics. The solutions are used for detecting failure patterns or anomalies, but are only deployed when there is high probability of imminent failure. This helps in deploying limited resources, maximizing device or equipment uptime, enhancing quality and supply chain processes, and thus improving the overall satisfaction for all the stakeholders involved.
Predictive maintenance focuses on predicting when device failure will occur and preventing that occurrence of failure with the help of maintenance monitoring so that maintenance can be planned before an issue manifests. One of the distinct features of predictive maintenance is that the maintenance frequency is a bare minimum, and it helps in preventing unplanned reactive maintenance and the expenses associated with preventive maintenance. The failure prediction in cases of predictive maintenance can be done with the help of one of many techniques. Based on the expert opinion and device in use, the proper technique is selected.
There are many benefits associated with predictive maintenance when used as a maintenance strategy. As maintenance is performed when failure is likely to occur, there is high cost savings related to the production hours lost to maintenance, expenses related to parts and supplies and the time for the equipment to be fixed. Predictive maintenance can minimize issues with reliability or quality. It can help in preventing expensive failures from occurring. Overstock can also be reduced in inventory thanks to predictive maintenance.
However, there are drawbacks associated with predictive maintenance. The expertise and skill level required for the data analysis in predictive maintenance needs to be highly specialized. The monitoring techniques used are also quite expensive.
Predictive maintenance is well suited for devices or equipment which perform critical functions or which have failure modes that can be cost-effectively predicted with the help of periodic monitoring.