The FMEA Paradoxes Dream Team: Thoughts on Maintenance Technicians and Equipment Failure As I reflect on the ongoing FMEA discussions, I can't help but notice a few paradoxes that have been on my mind. Let's delve into these paradoxes in a lighthearted manner and see how they may impact our maintenance processes. Paradox #1: It seems counterintuitive, but our top maintenance technicians are tasked with predicting equipment failures in a scenario where no maintenance is performed. These technicians excel at maintaining assets diligently, so it's intriguing to consider how they approach hypothetical failure scenarios. Paradox #2: The landscape of materials, equipment, engineering methods, and maintenance requirements is evolving rapidly. Despite this, we sometimes overlook manufacturer-recommended maintenance procedures in favor of technicians' intuitive guesses. This raises questions about the scientific rigor of our maintenance practices. Paradox #3: In the midst of it all, we label this process as a scientific method. How can we ensure that our FMEA methodology aligns with best practices and industry standards? Introducing the FMEA Dream Team: - Best Technician (BT): A skilled tech with a knack for maintaining and troubleshooting equipment effectively. - Worst Technician (WT): Surprisingly, the worst tech may have insights on equipment failure timelines due to neglect, offering a unique perspective. - Lazy Technician (LT): Despite his lazy tendencies, this tech's ability to estimate outcomes could prove valuable in predicting equipment failures. - Best Operator (BO): An operator who understands the optimal way to run equipment. - Worst Operator (WO): This operator knows the ins and outs of pushing equipment to its limits, potentially leading to premature failures. - Engineer Tech (ET): While the real ET couldn't make it, our engineer tech brings technical expertise and a passion for discussing equipment intricacies to the table. Having a diverse team with different perspectives can enrich FMEA discussions and lead to more comprehensive risk assessments. Let's strive to leverage these paradoxes to improve our maintenance strategies and enhance equipment reliability.
As other discussions continue, it is important to consider how an in-house RCM/Maintenance Engineering team can approach the maintenance review issue. I will focus on my own area of expertise, as the alternative seems to be more like a difficult situation. Let's begin by asking, "How has business been lately?" It's clear that while some industries are shielded from economic downturns, everyone is seeking ways to reduce expenses. However, cost-cutting measures need to impact the budget cycle quickly in order to be effective. Without a functioning business, conducting a site-wide FMEA or PMO will not be beneficial. As previously mentioned, the key to making swift decisions lies in analyzing similar data in a project-oriented manner. Our analysis has demonstrated that by examining PM work order data to potentially extend PM frequencies, maintenance costs can be reduced safely and efficiently, with immediate returns. I will need to provide further updates in the future as I balance this discussion with my primary responsibilities.
For an in-house team to succeed, two crucial elements are needed: quality data and formal processes. Quality data is essential as it allows your team to understand both the strengths and weaknesses of your data. Your data team should be highly involved and focused on improving the quality of the data. Having a team member skilled in developing database queries and spreadsheets is key to organizing the data in a way that is both reviewable and actionable. This person should be encouraged to be creative and come up with innovative solutions. Poor data quality can lead to inefficiencies in labor and parts management. Labor inefficiencies, such as planners chasing parts instead of planning or technicians spending time hunting for parts when they should be working, can be directly linked to data issues. Additionally, data plays a crucial role in making decisions about extending preventative maintenance schedules. Formal processes are also critical for the success of a maintenance program. These processes should be documented and formalized to ensure consistency and clarity for all team members. Standardizing job plans and language is essential for efficiency. By compartmentalizing standard verbiage based on equipment types, anyone can easily create a job plan using the established language. While there may be custom steps for specific tasks, having a solid base of standardized job plans can greatly improve efficiency. It is recommended to gather a group of team members to brainstorm and formalize processes. Once these processes are in place, they can be used and refined over time. By implementing and consistently using formal processes, improvements in job plan verbiage can be achieved through revisions and enhancements.
The issue with FMEA lies in its overly optimistic view of cost avoidance, assuming that every potential cost-saving measure will actually be realized. However, the cost of conducting the analysis far outweighs the budgetary savings it delivers. Additionally, FMEA is a highly subjective method, as highlighted in a recent comparison with PMO2000. In this comparison, a FMEA expert challenged the perception of recommended maintenance schedules, using the example of differing experiences with a 2009 Honda Fit and a 2002 model. These contrasting experiences demonstrate the subjectivity of FMEA and the impact of individual perceptions on analysis outcomes. As someone experienced in analyzing data, I have found that people's perceptions often do not align with the actual data. This discrepancy is evident when comparing observed savings from our PM Extension Project, as shown in the attached charts. The project not only generated immediate cost savings but continued to provide benefits in subsequent years. By carefully calculating and allocating these savings, we were able to address pressing budgetary needs within the company. Interestingly, projections indicate that extending shorter maintenance intervals yielded greater overall savings compared to longer intervals over a 10-year period. In conclusion, while FMEA can be a valuable tool for risk assessment, its limitations in predicting actual cost savings and its reliance on subjective factors should be taken into consideration. Our experience with the PM Extension Project serves as a practical example of the importance of data-driven decision-making in generating sustainable financial benefits.
The PM Extension Project was initiated about a year before the global financial crisis, when our plant experienced a sudden 50% reduction in run rate. At that time, all of our PMs were scheduled based on calendars, which led to over PM’ing our equipment due to not being aligned with equipment usage. To address this issue, we launched the PM Extension Project, starting with drafting a project charter that outlined financial goals and the project scope, which was approved by management. Our plant faced budget cuts and needed to realign maintenance output with the new run rate reality. To optimize maintenance efforts, we implemented criteria for extending calibration frequencies for instruments based on performance history. Mechanical PMs were found to be more subjective than instrument PMs, so we established rules and guidelines for consistency. By analyzing plant run rate reduction and past PM performance, we were able to identify areas for improvement. Utilizing database queries and tracking spreadsheets, we developed metrics tracking tools to project budget savings. The success of the project allowed us to replicate the strategy at other sites with minimal effort and significant returns. By transitioning from calendar-based PMs to usage-based PMs, we aimed to align maintenance schedules with equipment usage for more efficient operations. The proactive approach taken by our maintenance team not only resulted in cost savings but also contributed to maintaining the company's stock price during challenging economic times.
Transitioning from calendar-based to usage-based preventive maintenance was a game-changer for us. We initially began by installing hour meters on our equipment and manually inputting the data into our Maximo system. However, things took a positive turn when we integrated OSI's PI Historian database into our maintenance process. This powerful tool has been quietly gathering detailed plant events for years, yet we only recently started utilizing it for PM tasks. PI Historian not only tracks run time, valve actuations, pressure, and temperature, but also allows us to program run-time totalizers for our meter-based PMs. With the ability to extract hour meter data from Excel queries and load it directly into Maximo, our maintenance process has become much more efficient. Furthermore, by leveraging PI Historian, we are able to predict maintenance triggers based on specific equipment parameters such as main pump run-time or number of valve actuations. Operators have even started using Historian proactively by setting up alerts for any deviations from normal behavior, enabling them to address issues promptly. The potential for PI Historian goes beyond just being a PM trigger tool - it also serves as an early warning system for equipment failures. By analyzing historical data, we can detect patterns and anomalies that indicate potential issues before they escalate. This technology integration has not only streamlined our maintenance process but also enhanced our ability to proactively manage equipment reliability.
Interesting paradoxes you've highlighted there, and the idea of the "FMEA Dream Team" really caught my eye. I agree that diversity of perspectives can add a lot of value to any FMEA discussion, and not just from our finest and most diligent technicians. Your point about often overlooking manufacturer-recommended procedures is a spot on; sometimes, we might fall into the trap of relying too heavily on the experiences and intuitions of our technicians. Clearly, we need to strike a balance between empirical knowledge and the evolving landscape of engineering and maintenance best practices. Your post certainly sparks a deeper dialogue about how we can better execute and understand our FMEA processes.
✅ Work Order Management
✅ Asset Tracking
✅ Preventive Maintenance
✅ Inspection Report
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Answer: - The thread discusses paradoxes such as technicians predicting equipment failures in scenarios with no maintenance, overlooking manufacturer-recommended procedures, and labeling the process as scientific despite potential gaps in scientific rigor.
Answer: - The FMEA Dream Team includes Best Technician (BT), Worst Technician (WT), Lazy Technician (LT), Best Operator (BO), Worst Operator (WO), and Engineer Tech (ET) who bring diverse perspectives on equipment maintenance and failure prediction.
Answer: - Having a diverse team with varied insights and experiences can lead to more comprehensive risk assessments, improve maintenance strategies, and enhance equipment reliability by considering different viewpoints on failure scenarios.
Answer: - Organizations can ensure alignment with best practices and industry standards by regularly reviewing and updating their FMEA methodology, incorporating feedback from team members, staying informed about evolving maintenance requirements, and emphasizing scientific rigor in maintenance practices.
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