Leveraging Failure Data for Better Decision Making with John Reeve

Failure data is very important for leaders to make effective and efficient decisions. That’s why they are always looking for industry best practices and new implementation techniques to understand failure codes and failure modes in a better way. The organizations always focus on understanding failure codes so that they can design their CMMS. They always configure their CMMS to better analyze the failure data. They have a process in place that allows them to run failure data against different fields based on the failure codes. Failure data must be synchronized to hold RCM analysis results. CMMS can be built in way that it perfectly serves the purpose.

There can be embedded applications in the CMMS to do the job of storing RCM analysis data. Then, we can refine that data over time to make intelligent business decisions. This helps derive maintenance tactics that lead to work-order completion and capturing proper, validated failure mode data. Once we link the data with RCM analysis, we have synchronized failure data. Then the chronic failure analysis can be used to capture the failure mode correctly, run analysis against it, and extract information to help the reliability team in taking meaning actions. So, it gives you a step by step process to get to the root cause of the failure.

Then there is a need of PM job-completion plan that includes day-to-day jobs being carried out. This is something the reliability engineer can help with. It should also include safety measures and standard checks. The maintenance team must get together and ask themselves why the failure occurred after they had put maintenance tactics in place? Why is the work order failure mode missing from the failure mode application when they had already done the analysis? May be they should consider revising the maintenance tactics because it’s clearly not working.

Once the data is synchronized, the ongoing refinement with the process must be trended. This definitely takes some time. The reliability engineer can discuss this with the technicians to put the checks in place. Then it would only take minutes to carry out any compliance. So, the CMMS must be designed in a way that the failure data is synchronized at all time. Once the organizations have a properly designed failure analytic in place, they can choose different metrics to run the analysis to identify bad actors. After that, they can just run the data against failure code and take corrective actions.

This is a continuous process that can result into a live software that can actually help you perform data-based informed decisions on a routine basis. Any time you need to run analysis on a critical asset, it can be added to the work order and corrective actions can be taken in real time, live manner. This can be easily done but there are other ways to achieve this as well. The successful organizations understand the value of good data to reduce reactive maintenance and that leads to cost effective maintenance programs for your assets.

Eruditio Links:

• Eruditio
• HP Reliability
• James Kovacevic’s LinkedIn
• Reliability Report

John Reeve’s Links:

• Past episodes with John Reeve
• Failure Modes to Failure Codes
• EDI
• John Reeve LinkedIn

148 – Leveraging Failure Data for Better Decision Making with John ReeveJames Kovacevic

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