  Predictive maintenance (PdM) is a concept, which is implemented to
effectively manage maintenance plans of the assets by predicting their failures
with data driven techniques. In these scenarios, data is collected over a
certain period of time to monitor the state of equipment. The objective is to
find some correlations and patterns that can help predict and ultimately
prevent failures. Equipment in manufacturing industry are often utilized
without a planned maintenance approach. Such practise frequently results in
unexpected downtime, owing to certain unexpected failures. In scheduled
maintenance, the condition of the manufacturing equipment is checked after
fixed time interval and if any fault occurs, the component is replaced to avoid
unexpected equipment stoppages. On the flip side, this leads to increase in
time for which machine is non-functioning and cost of carrying out the
maintenance. The emergence of Industry 4.0 and smart systems have led to
increasing emphasis on predictive maintenance (PdM) strategies that can reduce
the cost of downtime and increase the availability (utilization rate) of
manufacturing equipment. PdM also has the potential to bring about new
sustainable practices in manufacturing by fully utilizing the useful lives of
components.
