Up Time Magazine - December 2008/January 2009 - (Page 49) cellent guides for building RAM models. For Weibull analysis of components: MTBF or MTTF = h * G(1+1/b) Here, h is the characteristic life (i.e., the life at 63.2% of the cumulative distribution function, as this is a mathematical property of the distribution—in short, it’s the single point representation of durability that you discuss without all of the if/and/buts). The b is the shape factor. For components, b tells you how things died (i.e., b 1 infers wear-out failure modes)—it is important to let the data speak rather than pontificating about how things died. The term G(1+1/b) is called the Gamma function. For b = 0.5 the Gamma function is 2, for b = 1 the Gamma function is 1, and for b>1 it may be as small as 0.87 or as large as 1, so as a rough rule of thumb, the MTTF is roughly equal to h. You need to know the beta values to get the correct medicine because everyone will tell you things wear out, although, unfortunately, we kill more things than ever live long enough to wear out. (Note: On another website2, Dr. Robert Abernethy provides additional insight into the differences between MTBF and MTTF. Consulting his website may be important for students of the Weibull method.) MIL-HDBK-338 on page 46 gives you a simple and clear definition of failure: “The event, or inoperable state, in which any item or part of an item does not, or would not, perform as previously specified.” Reliability (lack of failures) always terminates in a failure (loss of the function when you needed it). Many other details about failures are also included in pages 46-47. Finally, download the technical paper #2 from Paul Barringer’s website at the bottom of the page called: Where Is My Data For Making Reliability Improvements. It gives other source documents and shows how to make the calculations. essential library3. John believes a meaningful comparison of MTBF must consider the service. Some, because of the fluid and/or operating conditions, will have shorter life expectancies than others. Mitchell uses the analogy of a coal miner who smokes; the miner probably has a shorter lifetime than a non-smoker office worker. John Mitchell has been trying -- without success so far -- to find a parameter that will, with one number, describe the distribution around an average. Distribution around an average might be the percentage or number of the total population more than 20% below the average MTBF. As an example, suppose a plant reports an MTBF of 48 months. This would be showing performance a bit below best in class in Table 1, from “Pump User’s Handbook: Life Extension” (ISBN 0-88173-517-5), but doesn’t say much beyond that. Knowing also that 2% of the total population was below 36 months would be useful information because it would tell us that the plant was aware of certain pumps that failed more often than others. (In many refineries that number is somewhere between 7 and 10 percent). However, suppose one found out that the MTBF of 25% 30% of the population was below 36 months, our diagnosis might be quite different and the opportunities for improvement would be shifting to a new focus. MTBF based on actual operating time. Yet, industry soon decided that the numbers looked better when the calculation encompassed all installed pumps, irrespective of running or not running. Moreover, we have always advocated picking first the ripe, low-hanging fruit and hasten to note that not everyone has heeded this advice. We are where we are and the picture is not rosy. Repeat failures abound and continue to be tolerated. Repeat failures are warning signs; they are the inevitable precursors to extreme failures which very often kill people. To this day, we see CMMS (computerized Maintenance Management Systems) software that allows log entries in words such as “bearing replaced.” To be of use to devotees of equipment uptime, a system must recognize that accurate failure analysis is required for failure avoidance. The entries must properly identify why a bearing failed and diligent failure analysis is absolutely necessary. Failure avoidance should be the ultimate goal because it means asset preservation and curtailment of money wasted on repeat repairs, not to mention costly remedial action after an extreme failure. All too often, persistent repeat failures are evidence of seriously flawed reasoning. The engineering student employed as an intern at that refinery probably would not wish to lose the opportunity for easy tracking of pump failures. He was probably searching for answers to tasks assigned to him by others. We can only speculate that “persons MTBF Equipment Location unknown” are often looking for ways to (years) bury the unacceptable performance of ANSI Pumps, AVG USA 2.5 their refinery pumps. They would be ANSI/ISO Pumps, AVG Scandanavian P&P Plants 3.5 delighted to obfuscate the issue by arAPI Pumps, AVG USA 5.5 guing over the most precise numerical API Pumps, AVG Western Europe 6.1 evaluation. We, for our part, believe the most productive choice to reduce pump API Pumps, repairDeveloping Country 1.6 failures is to compare one’s pump MTBF focused refinery against other refineries and to itemize API Pumps Caribbean Region 3.9 and comprehend what “others” do differAPI Pumps, best-of-class U.S Refinery, CA 9.2 ently. Note that we are not advocating All Pumps, best-of-class USA, Texas that you compare your refinery against 10.1 Petrochemical Plant any non-refineries, but you could make All Pumps, Major USA, Texas a relevant comparison between a given 7.5 Petrochemical Co. process unit at your refinery against a like process unit at another refinery. Table 1 - Pump Mean-TImes-Between-Failures Source: Pump User’s Handbook: Life Extension Consider Feedback from an Asset Management Expert Several comments were also obtained from John S. Mitchell, a self-described “advocate of change” whose “Asset Management Handbook” (ISBN 0-971-7945-1-0) is listed in our www.uptimemagazine.com More Experience-based Advice You Can Use Today The explanations offered by Paul Barringer and John Mitchell will have to be weighed by serious reliability professionals. Some of their suggestions were certainly considered in the mid1970’s when we wrote about calculating pump Although such comparisons are usually made on the basis of MTBF, they are still more useful than anything else. They lead to the next and most important step towards implementing the necessary changes, i.e. intelligently upgrading pumps or systems that fail frequently. Typically, and with few exceptions, these changes must be made on pumps with low MTBF. The simple MTBF roadmap has been followed for the past 35 years; its 49 http://www.uptimemagazine.com
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