“Manage the program not the data” part two
When developing a PdM program, the tendency is to focus on the initial hardware or software required or the outsource provider.
The recommended steps prior to deciding how to run the program and with what resources are as followed:
Develop an asset list for items to be evaluated for inclusion into the PdM program
Implement a process for ranking/scoring the criticality of each asset and determine whether predictive maintenance tasks are required and/or cost justified based on risk
Evaluate the failure modes of these assets to determine the appropriate predictive task(s) and technology for mitigating these failure modes.
Establish the optimal monitoring frequencies to ensure advanced detection of developing faults while minimizing required resources.
Once the program scope has been developed, a careful evaluation should take place to determine the best path forward based upon all the requirement to deploy the entire scope.
A determination should be made whether the program is best suited for in-house personnel and their skill set or to outsource the function to a third party provider.
Regardless of the deployment model you chose, resources must be allocated to maintain proper data collection at the prescribed frequency, experienced analyst to review and predict problems from the data and a program manager to ensure the program goals are met and there is a return on the investment.
Value Added Solution: PdM data is design to predict impending problems and the recommended maintenance needed to bring the asset back to normal operating condition.
However, the same data we use to find and solve individual problems, can further be used for enhanced reliability analysis to find reoccurring trends or patterns. Determining these patterns is very useful for long term precision maintenance management and continual improvements.
Benefits: With Predictive Service’s Viewpoint PdM software and management tool, the ability to extract reliability information to search for bad actors, OEM and equipment type quality, and other condition-based information.
It also provides the ability to identify which PdM discipline gives you the highest rate of return. This information is available dynamically on a real-time basis, and thus will not require waiting for year-end data mining to justify budgets or analyze the program.