For those seeking information on PM optimization, consider reading the article "A data driven path to PM optimization" published in MT, Feb 2011 (p.19-22). The article offers a method for determining inspection intervals based on desired availability and MTBF. It is vital to understand the statistical nature of such calculations, requiring data distribution including mean value and standard deviation if the distribution is normal. However, the author only provides MTBF and desired availability, leaving the formula for calculating failure finding interval (FFI) - inspection interval - questionable. This approach has two major flaws: 1. Failure causes are grouped together when calculating MTBF, making it unlikely to have a distribution. 2. Even if a distribution exists, standard deviation is not addressed. These shortcomings make the FFI formula unreliable and impractical for PM optimization. Instead of being a useful tool, it becomes a misleading academic exercise, diminishing the credibility of the reliability process.
It is important to consider that the assumption underlying the end result of extending frequencies is to ultimately save money. It is essential to differentiate between wear failures and random failures in order to effectively implement preventative maintenance strategies. While random failures may be difficult to predict and prevent, there are established wear failure modes that can be proactively managed through preventive maintenance measures.
Thanks for sharing the article - actually, I read it a while ago and shared some of your concerns. Emphasizing the lack of information on standard deviation hits the nail on the head. By ignoring the variability of data, we could be painting a false picture of system reliability. This would certainly make the FFI formula questionable. However, despite its limits, I still think the method could be a fair starting point, but it should definitely be supplemented with more robust statistical input and risk analysis to give more comprehensive optimization results.
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Answer: - The article provides a method for determining inspection intervals for preventive maintenance optimization based on desired availability and MTBF.
Answer: - The calculations require data distribution, including mean value and standard deviation if the distribution is normal.
Answer: - The approach has two major flaws: failure causes are grouped together when calculating MTBF, making it unlikely to have a distribution, and even if a distribution exists, standard deviation is not addressed.
Answer: - The shortcomings in the formula make it unreliable and impractical for PM optimization, turning it into a misleading academic exercise that diminishes the credibility of the reliability process.
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