Up Time Magazine - December 2008/January 2009 - (Page 48) reliability upload Research Brings Results Defining Mean Time Between Pump Failures by Heinz P. Bloch, PE I n September 2008, we were contacted by a Mechanical Engineering student. He was close to completing an internship with a major U.S. oil refinery and had been asked to set up a system allowing the refinery to monitor its pump mean-time-between-failures (MTBF). possible for failed pumps, the specialist using them will give up the straightforward comparison with others that use MTBF. That should be a concern for us. Since being given the assignment, the young man had encountered serious roadblocks. His first question was how MTBF was being calculated in the oil refining industry. He advised that some people just take the number of months in service and divide by the number of repairs during that time; while others apparently perform a Weibull analysis. The Weibull analysis sounded much more accurate to him, but he wanted to stay with industry standards. He ran into a second roadblock when attempting to define what a failure is. The refinery was currently contemplating a definition of “anything costing over $1,000”, but he wanted to know what the standard was. Using the all-pervasive and now rather customary (and generally inadequate!) Internet search method, he found many articles that talked about MTBF studies. He did not, however, uncover any articles that shed useful light on how such studies were to be set up. Finally, he asked for help in finding some of the answers. More About Weibull For definitions of failures/metrics, etc., go to Paul Barringer’s reading list for reliability1. Select an old document, MIL-STD-721. This is one of many military documents Paul has accumulated on his website. Specifically, go to page 11 for the words, which he has reduced to the equations below: MTBF for repairable units = ∑ life / ∑ failures (Please note: Life does NOT include life of dormant units which are NOT running) MTTF for non-repairable units = ∑ life / ∑ failures (Please note: Life does NOT include life of dormant units NOT running. MTTF is a more difficult metric because you have to accumulate the life of each failed unit that was in service up to its failure). No Standard, Just Choices There is no written standard on MTBF, but McKenna and Oliverson’s “Glossary of Reliability and Maintenance Terms” (ISBN 0-88415-360-6) neatly defines it as: “A basic measure of reliability for repairable items; the mean life during which all parts perform within their specified limits, during a particular measurement interval under stated conditions; an index of reliability calculated by dividing the total number of stoppages (outages) by operating time; the number of hours or cycles an item or items operated divided by the number of failures that occurred; commonly expressed as a six or 12 month rolling average; also expressed as one over the failure rate.” That pretty much explains what is common practice. By deviating from common practice, perhaps doing a Weibull plot, one achieves another benchmark. A Weibull plot is a reliability prediction technique used to evaluate the reliability parameters of components (e.g. bearings), and the data from it is more precise than MTBF calculations. These plots are also valuable during the development phase of a component. While Weibull plots are The MIL-STD-721 document reaches way back to the 1970’s, and has now become obsolete. Better modern documents such as MIL-HDBK-338 are available today. Go to pages 52 and 53 of MIL-HDBK-338 for the words and definitions. The complicated math follows on page 86-87 for those who want to know more information. Page 126 gives a comparison of reliability/availability/ maintainability (RAM) metrics. Quoting Paul Barringer, “The practice of summing the life of active units plus dormant units is a poor (lazy) engineering practice in calculating MTBF & MTTF metrics. It is poor because it overstates the results by including so-called life of dormant units. This sets a trap for naive people building RAM models of system performance because the flawed metrics will overstate system performance.” The military documents, such as DoD Ram Guide, RAM primer, MIL-STD-785, NASA-Std-8729.1, and other documents listed on the Barringer website, provide some exdecember/january 2009 48
For optimal viewing of this digital publication, please enable JavaScript and then refresh the page. If you would like to try to load the digital publication without using Flash Player detection, please click here.