Proactive maintenance is subdivided in preventive time based (calendar or running time) and asset condition-based maintenance. Condition based maintenance (CBM) involves monitoring the condition of assets in order to predict failures before they occur. It is a proactive maintenance strategy based on equipment reliability characteristics.
The vast majority of asset failures (89%) shows no evidence of wear out and cannot be covered effectively by time-based maintenance strategies. This has led to the introduction of condition-based strategies to maximize the useful life of the assets. The goal of CBM is to detect potential failures in due time and take action before the actual failure happens.
The question now is what is the best CBM strategy to choose: condition monitoring (offline), continuous condition monitoring (online) or asset performance management (APM) 4.0 using artificial intelligence and machine learning. Choosing the right approach will depend on the lead time to detect the failure, the criticality and complexity of the asset, data availability and quality, and last but not least, your business goals. With this approach we can ensure not only following the hype of big data, machine learning, but to choose the optimal solution to find the perfect balance between risk and cost.
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