Hello everyone, I have a question regarding the use of reliability in determining maintenance intervals for equipment. Let's say I have a set of identical equipment experiencing a specific type of failure, such as hot electrode failure in spot welding guns, which has occurred 19 times over a three-year period. Can I calculate the reliability of these guns to establish a maintenance schedule? For instance, if I set the reliability threshold at 95%, meaning only 5% of the guns will fail over a given period, I can determine that maintenance should be performed every 147 days. Is it accurate to assume a constant failure rate, given that I only have interval censored data showing failures over time? Unfortunately, there is no information available on the time to failure for me to use a Weibull analysis. Thank you for your assistance.
Can you provide information on the failure mode and whether it is a consistent deterioration over time?
Could you compile a list of failures along with their corresponding time intervals?
If you are an industrial trainee from a university, consider reaching out to your lecturer for guidance. Check out this insightful article on the internet that discusses the limitations of MTBF: http://www.maintenancetechnolo...-frequency-is-wrong/.
If you are interested in a relevant article, be sure to check out the following link: http://www.weibull.com/hotwire...113/hottopics113.htm. Explore this resource for valuable insights on trending topics.
Thank you for your response. I have already reviewed the articles mentioned. In my situation, I do not have any cost records associated with the preventative maintenance (PM) actions. Instead, I have a dataset resembling interval censored data, as explained in this resource on reliawiki.org. I am only aware of the number of failures and their respective times within a specific timeframe, with no information available outside of that period. The root cause of the failures in this case seems to be bad welding points caused by overheating electrodes in the resistance spot welding gun. This issue can potentially be resolved by cleaning the cooling pipe that helps regulate the electrode's temperature. My current goal is to determine the frequency at which the pipe should be cleaned. Considering the limited data available, I am contemplating using reliability analysis to obtain a rough estimation. By setting a threshold for acceptable failure rates (e.g., 5% equipment failure or 95% reliability), I can calculate the estimated interval T within which no more than 5% of equipment should fail. I will then schedule pipe cleaning activities at regular T intervals based on this analysis.
In using reliability to set maintenance intervals, it's essential to consider that an assumption of a constant failure rate based only on an average of past failures might not be perfectly accurate. Equipment doesn't always fail strictly on a schedule - external factors could influence the reliability such as the usage rate, operating conditions, quality of parts, and whether any preventative maintenance has been done. Therefore, it's ideal to employ a more robust approach that encompasses all these variables. Relying solely on your interval censored data will give you an estimate, but not necessarily the most accurate one. A better way might be to incorporate condition-based maintenance, where you closely monitor the operating conditions and performance of your equipment and schedule maintenance when specific indicators show that a failure is imminent.
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Answer: - Reliability can be used to establish maintenance schedules by setting a reliability threshold, such as 95%, to determine how often maintenance should be performed based on the failure rate of the equipment.
Answer: - Assuming a constant failure rate may not be accurate when using interval censored data, as it does not provide information on the time to failure. Other methods, such as Weibull analysis, may be more suitable in such cases.
Answer: - Factors to consider include the specific type of failure experienced by the equipment, the reliability threshold set, the frequency of failures over a given period, and the availability of data on time to failure for more accurate analyses.
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