At the Emerson Exchange conference in Austin, Emerson’s Will Goetz presented, Best Practices for Using Condition Monitoring to Drive Maintenance Workflows. His abstract:
A well designed condition monitoring system can find the early warning signs of failures but what happens next is equally important. This session will explore real world failures to develop the best practice model for using condition information to drive maintenance work. It will use Doc Palmer’s time study analysis to illustrate the productivity potential of planning & scheduling and demonstrate the impact of these practices on the MRO supply chain. In addition, it will explore the use of criticality/risk models in prioritizing work and explore the business impact of the best practice model.
Will opened defining top quartile reliability performance and three key function these top performers perform. He showed a bar chart showing the companies with the highest availabilities in the top quartile have much lower maintenance costs than companies in the other quartiles. In fact, 4th quartile performers spend 3.5x what top quartile producers spend in maintenance. These numbers are based on a 2013 Solomon RAM study.
Just by cutting costs to reduce maintenance costs to top quartile levels without fundamental changes would likely result in undermanned, fire-fighting maintenance modes of operations with a fall into the 4th quartile.
Top quartile performers analyze asset health, plan repairs and optimize reliability performance in an ever-improving cycle. Broken down further, a full reliability strategy includes asset master data, maintenance procedures, process parameters, condition indicators, asset health analysis, work identification, planning/scheduling/work execution, supply chain management in a continuous cycle to improve overall safety, availability and profitability.
Asset failures have safety, environmental, quality, production, and/or maintenance cost impact. Moving to a proactive maintenance model requires rethinking the workflow and maintenance culture to make sure the early warnings are acted upon in a timely manner.
Time-based maintenance programs are typically ineffective because failures are largely random. Will showed a number of failure curves including bathtub curves, slow aging, best new, constant random and worst new. Time-based maintenance does not improve performance for the majority of these curves.
Once a failure is detected failure mode effects analysis (FMEAs) help identify the cause and plan the right corrective action. Best practice is failure analysis, detection method selection, failure detection, work identification, planning, and failure coding. For top quartile performers, nearly all maintenance resources should be executing planned work, instead of reactive work. Condition monitoring must drive 50% of this planned work.
Top quartile performers spend most of their maintenance time and effort performing planned activities. The results of these efforts is greater availability, less operational risk from time spent in unplanned shutdown and startup modes of operation, and lower maintenance dollar spend.
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