Predictive maintenance has a lot of benefits, from reducing unplanned downtime, lowering maintenance costs to extending equipment life. It is no wonder maintenance managers are looking to apply these technologies to their processes.
In this series, we started off by looking at What is Predictive Maintenance? and how it is different from other strategies such as reactive and preventive maintenance. We continued to consider How Using Condition Indicators can help you discriminate between healthy and faulty equipment operation. Lastly, How Estimating Remaining Useful Life can help you optimise your maintenance plans.
To conclude the series, this paper discusses four common obstacles that often stop companies from successfully implementing predictive maintenance. Common obstacles include:
- We do not have enough data to create a predictive maintenance system
- We lack the failure data needed for accurate results
- We understand the failures, but we cannot predict them
- We do not know how to do predictive maintenance
In this paper we see how each of these obstacles are solvable given the right tools, guidance, and motivation.
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