Preventive Maintenance OptimizationPM Optimization (PMO) is a structured process aimed at preserving and restoring the equipment condition. With PMO, we focus on identification of the failures (failure modes) and develop PM tasks to manage the failure. Preventive Maintenance Optimization helps in fulfilling the mission of maintenance. Maintenance, or more specifically, maintain, is defined in Webster’s online dictionary (Ref: http://www.merriam-webster.com/dictionary) as:
1: to keep in an existing state (as of repair, efficiency, or validity): preserve from failure or decline <maintain machinery>
2: to sustain against opposition or danger: uphold and defend<maintain a position>Each of these steps are significantly affected by our PM and Preventive Maintenance Optimization process. Without value-added PM, we will not identify all work, we cannot prioritize properly, and we cannot affect the kitting, scheduling, execution, and analysis of the work. With value-added PM, we will not only make the maintenance work more effective and value-added, we will reduce the downtime of the equipment (for PM and for repair).
What is PM Optimization?Preventive Maintenance Optimization is a process to improve the effectiveness and efficiency of the PM process. Effective PMs address and reduce the consequence of specific, probable failure modes. Efficient PMs are value-added tasks conducted using the least labor, downtime, and materials required to complete the task. How can we optimize our PMs? First let’s consider the origin of many PM programs. PMs are often hastily put in place to meet a requirement or project objective. They are often cut and pasted from other machine PMs or taken directly from the OEM manual. While these might be an okay starting point, there can be a significant issue if they are left unchanged over a period of time. PM Optimization is built upon a series of key concepts and structured processes. Some Preventive Maintenance Optimization processes are very rigid and closely follow Reliability-Centered Maintenance (RCM) process and principles, while others apply the principles of RCM, looking for application of the principles to the 20% of the problems causing the highest downtime, quality cost, or maintenance cost. All approaches use some common elements to arrive at the most value-added PM strategy for the equipment. When optimizing PMs, we will look at failure data, PMs, experience, and functional diagrams to develop a list of probable failure modes. We will then use the concepts of failure patterns, P to F curves, consequence, and operating context to develop an improved strategy. Using operating environment, failure patterns, and P to F, we can answer three basic questions:
- Will replacement of part on a known interval or usage reduce the probability of failure?
- Can we see it in the process of failure with sufficient time to respond?
- Is the impact of the failure high enough to warrant the cost of a PM strategy?
- What is to be done?
- How is it to be done?
- What is acceptable?
- Condition-based—what criteria or specification determines pass or fail?
- Interval-based—what criteria or equipment function must be ensured after task completion?
- What course of action should the craftsman take if the results are unacceptable?
- What do we do to ensure safety?
- What is the specific failure you are trying to stop (Failure Mode)?
- What is the history related to this failure?
- Is this the only task addressing this failure?
- Can you see the failure coming (P to F)?
- Can you predict when the failure is likely to occur (age)?
- How much impact would there be on Safety, Production, Cost… (Consequence) if this were to occur?
- Can you add more detail or pictures to the task to ensure higher quality of execution (What, how, criteria, what if fails)?
- How long would you feel comfortable letting this run without checking or changing (Frequency)?
- Who is the best resource to perform the task?