Yardstick

by Brian Baldwin

One of the more common challenges for any predictive maintenance (PdM) program is to come up with definable and measurable parameters that tangibly identify the value of the program.

During this pursuit for the ultimate yardstick, we as reliability practitioners sometimes lose sight of the ultimate goal, which is to improve equipment reliability and subsequently reduce operations and maintenance costs. Unfortunately, for the sake of justifying our programs, we commonly turn to the abstract measurement of “soft” dollar savings associated with cost avoidance.

For those of us who are intimately involved with a vibration analysis program, we objectively know there is great value in routinely monitoring and analyzing vibration data on our rotating equipment. However, we find it difficult to communicate this value in meaningful terms that our leadership can use to manage resources and justify maintenance expenses. The “What if…” cost avoidance approach mentioned above is difficult to defend when maintenance budgets are scrutinized and trimmed during the annual budget preparation cycle. This is especially true for an established vibration analysis program that has been successful at minimizing or eliminating the high profile, costly failures that were once commonplace, but are now merely a faint memory.

So how do we successfully communicate to our management team the value of our vibration analysis program? The approach described below is one that uses the functionality of a computerized maintenance management system (CMMS) to identify the impact our program has on the utilization of resources in a reactive maintenance mode. In order to accomplish this, we must ensure the work order and asset modules of our CMMS are properly configured with specific attributes that can be queried to help identify assets included in the vibration analysis program, corrective work types, emergent/breakdown work, labor and material costs, and lost production costs. In doing so, our CMMS provides the ability to query all emergent work orders and filter on those assets that are monitored within the scope of the vibration analysis program for a given date range. Additionally, fault codes can be utilized within the CMMS to provide more granularity in the identification of vibration related anomalies as opposed to the more general blanket of emergent work cast over the assets within the program scope.

Query results displaying totals for labor hours on repair work orders are then used in the calculation that follows to determine the effectiveness of a vibration analysis program in reducing reactive maintenance activities.

equation

For example:

In the month of December, we spent a total of 80 man-hours on data collection, analysis and reporting. During that same time period, the plant experienced 10 anomalies out of the 250 machines we routinely monitor during the month that either resulted in a breakdown or emergent repairs. The 10 anomalies resulted in a total of 100 man-hours to reactively repair and restore affected equipment to normal operation. The vibration monitoring program’s effectiveness based on labor utilization can be calculated as:

Equation

Trending vibration program effectiveness on a monthly basis provides a focused performance measure that gives greater insight into the traditional percent reactive work key performance indicator (KPI) used to indicate the general mode of maintenance efforts. Deeper analysis of specific contributors to the effectiveness of the vibration analysis program can help identify areas for improvement and implement targeted corrective actions that will enhance existing maintenance strategies for our rotating equipment.

Another valuable performance measure that complements the labor-based effectiveness indicator described above is the monthly Pareto analysis of the total cost of failure for those same vibration related emergent/breakdown type of work orders. This includes all costs associated with labor, materials, contractors and lost production. Modifying or utilizing an existing user-defined field in the CMMS work order module to capture lost production/ missed opportunity cost is an efficient way to tie equipment related financial losses to work orders and accurately document the total impact of equipment anomalies when reporting on the total cost of failure.

By leveraging the functionality of a CMMS to document and measure maintenance reliability performance, in this case vibration analysis, we have an efficient method to measure and communicate the tangible value of our program. Paramount to the success of any vibration analysis program, accurate root cause identification and effective corrective actions are necessary to drive improvements in rotating equipment performance. However, without a meaningful measurement that makes a compelling statement for the positive impact on equipment reliability, even the best vibration analysis programs will struggle to justify any further investment.

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