Technology has matured considerably. Now the goal is to gain optimal life for the machines while avoiding failure. If deployed properly, predictive maintenance predicts future machine failures, pinpoints complex equipment problems, and identifies parts that need fixing. With those principles in place, plant operators become more attuned to planning maintenance. They can reduce unplanned machine downtime while maximizing overall equipment life. This is a bigger bite than simply identifying a motor that’s running too hot or sounds funny.
This isn’t your father’s predictive maintenance. When predictive maintenance was first introduced, it was famously the low-hanging fruit of advanced manufacturing. Predictive maintenance was typically the first step in the move to smart manufacturing.
According to MathWorks – an AI software company – these desired outcomes won’t happen without an algorithm capable of predicting a time window when machines will likely fail. The following four-step workflow is designed to guide manufacturers through the process of developing effective predictive maintenance:
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