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What Is Preventive Maintenance Optimization?
Preventative Maintenance Optimization (PMO) is the practice of continuously improving the efficiency of preventative maintenance (PM) activities by regularly reviewing failure modes and frequencies. PMO evaluates existing PM activities and ensures that all maintenance tasks are adding true value to the operation. The idea is to ensure time and resources are not wasted on maintenance activities that do little to prevent breakdown or increase operational uptime.
Why Optimize And Improve A Preventive Maintenance Program?
As opposed to reactive maintenance that reacts to equipment failure which often cause an outage, work orders for preventive maintenance activities are introduced to eliminate unplanned downtime. A maintenance strategy is developed with the intention of preventing failures and making improvements to the operation as a means of cutting down costs in the long run.
Unfortunately, many organizations fail to include followup actions to failures in their preventative maintenance strategy. An effective PM program is about responding to failures with solutions that ensure continuous improvement. By optimizing the frequency per failure mode, downtime can be minimized further and each individual PM task can be tweaked to increase the efficiency of the entire operation.
In a nutshell, PM optimization aims to improve production reliability, reduce production downtime, and increase the cost-effectiveness of maintenance. This should be an ongoing process to ensure the program maintains currency with technological advances, asset updates, and asset deterioration.
Approaches To PM Optimization
There are three approaches that are considered to be the best practice when it comes to PM optimization. They are as follows:
- Failure Reporting and Corrective Action System (FRACAS)
- Reliability Centered Maintenance (RCM)
- Judgment and Analysis Based Approach
In the next section, we will explain how each strategy works to improve PM across the operation.
Failure Reporting Analysis and Corrective Action System (FRACAS)
The first approach is the failure reporting analysis and corrective action system (FRACAS). This is a system that analyzes the root causes of breakdowns. Organizations can then use this data to adapt their strategy and prevent repeat failures.
The first stage of the process is failure reporting (FR). System failures are reported through an EAM (Enterprise Asset Management) system or CMMS (Computerized Maintenance Management System). This data allows organizations to identify where and when breakdowns are occurring.
Next, analysis (A) is performed in order to identify the root cause and failure mode of the failure. Once these have been identified, corrective actions (CA) can be implemented as part of the overall maintenance management plan. At this stage, changes to maintenance plans are made with the intention of preventing recurring failure. This is a data-based response to failure prevention.
Reliability Centered Maintenance (RCM)
The second approach is reliability centered maintenance (RCM). As the name suggests, this strategy is focused on improving the reliability of the asset. It is about ensuring that all systems do what they are supposed to do so that operations can be carried out without any unexpected hiccups. This approach also relies on EAM / CMMS failure data as a means of analyzing the assets breakdown history.
There have been numerous discussions among sources about what quantifies “true RCM”. Generally, for a process to qualify as RCM, the program must be structured to preserve system function, then identify and address failure modes by risk priority. Maintenance tasks are then established in terms of effectiveness in response to the most important failure modes. Asking questions that examine the impact of asset failure on the operation is what drives the data analysis.
This method is time-consuming, but when each stage is implemented properly, RCM is a proven way to optimize the maintenance work on your most critical assets.
The judgment-based approach to PM optimization takes a more technician experience oriented stance when it comes to practical problem-solving. The process requires communication between the maintenance team, operators, and process engineers. so that they can develop a corrective plan based on the current maintenance schedule.
Unlike FRACAS or RCM, this method does not rely on the EAM / CMMS to provide data that translates into failure analysis. Instead, this method relies on the judgment of maintenance and asset experts to identify the common failures and their frequencies in order to develop practical PM tasks.
While this strategy is less precise than EAM / CMMS data analysis, for equipment that is not operationally critical, expert judgment is a way to quickly improve your maintenance strategy.
Once you have chosen which approach is the best fit for your organization, you will need to lay out an organized approach in order to generate the greatest benefit.
- Begin with gathering all assets for which you want to optimize the PMs.
- Group them by class so that you can leverage commonality and therefore repeatability in tasks.
- For each class, group the PMs by frequency as this will be a key driver for task grouping.
- Next, determine if any tasks require the asset to be down, and if so, should that be a separate PM from the non-downtime required tasks.
- With the final PM list in place, assign the frequency, trades, skills, certifications required, and duration for execution. Don’t forget to add in the failure modes mitigated for future analysis and optimization improvements.
With an optimized preventative maintenance program and the right data on your plans, scheduling to have the right people available at the right time becomes much easier and therefore creating an overall more efficient maintenance management program.