Oil analysis provides a huge payback when deployed through a proper strategy. While an extremely valuable tool in today\u2019s reliability programs, it is sometimes applied in an ad-hoc manner. This is a dangerous approach, as the program can quickly become quite costly due to overtesting or even show little value due to inadequate testing. Let\u2019s take a look at both situations.<\/p>\n
Overtesting<\/strong> Taking this approach would have meant that the mill would run hundreds of oil samples on at least a quarterly basis. Adding to this, when following proper sampling procedures, we understand that the sampling hardware must first be flushed. When sampling small reservoirs, such as those in small centrifugal pumps, following the flush portion and then sampling, a complete oil change would have occurred on every pump each quarter. Considering the increased lubricant consumption coupled with the additional cost of testing the oil samples, you can see how the overall costs would add up quickly.<\/p>\n Although the maintenance manager should be commended for his aggressive drive toward equipment reliability, moving forward with the initially desired approach would have been costly, significantly reducing the program\u2019s overall return on investment (ROI).\u00a0<\/p>\n Inadequate Testing<\/strong> This plant was experiencing a significant number of failures that could have been avoided had the program been put together properly in the first place. By taking this approach, the total cost of program development and optimization was incredibly high once the costs of missed opportunities were included into the equation.<\/p>\n Moving Forward<\/strong> Each of the basic types of oil analysis has an intended function and can offer significant benefit to the end user if deployed properly. For companies with a large number of lubricated components included in the oil analysis program, it is vital to incorporate some level of each of these categories for a well-rounded program.<\/p>\n Utilizing the criticality of machines that has been assigned through a documented method provides the best starting point in the decision-making process regarding which form, or combination of forms, is best for each component.<\/p>\n A plant with a well-developed criticality system already has the foundation for establishing an equally well-developed oil analysis program. Some of the primary decisions related to oil analysis that criticality can assist with include:<\/p>\n
\nA recently visited paper mill had a rather robust oil analysis program. This program was further optimized by the corporate reliability manager. The maintenance manager had a positive feeling about the benefits of predictive technologies and was supportive of the oil analysis program. While this was all seemingly positive data, the drawback was that the manager decided he wanted all equipment to be incorporated in the oil analysis program, including small centrifugal pumps containing less than even a quart of oil.<\/p>\n
\nDuring a recent oil analysis program benchmarking exercise, it was asked how machines were selected for inclusion in the testing program. The initial response was, \u201cWe use criticality.\u201d When the process used for criticality assessment was investigated, it was revealed that there was no real process. The machines were selected based on what I like to call \u201cperceived criticality.\u201d This resulted in a very small group of components initially being tested, although the program was growing in a methodical manner. When a machine component failed that was not part of the analysis program, the replacement component was then put on the program. So there was no real methodology at all.<\/p>\n
\nOil analysis comes in three basic forms:<\/p>\n\n
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