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Forum: Reliability & Maintainability Questions and Answers

Topic: Reliability & Maintainability Questions and Answers

Topic Posted by: Reliability & Maintainability Forum ( )
Organization: System Reliability Center
Date Posted: Mon Aug 31 12:47:36 US/Eastern 1998

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Original Message:

Posted by: Tim Daniels (Tim.Daniels@Fernau.Com )
Date posted: Tue Oct 26 10:09:55 US/Eastern 2004
Subject: Spares level over set period of time
Sorry this may be a silly question but it's the first time I've done anything like this. I need to calculate the number of spare LRUs required for a product to have 95% confidence level (of having a spare available) when the repair time is 10 months. I have failures/million hours figures and thought the RAC Poisson calculator for sparing was the answer! But now I have to consider a mission time of 18 months and calculate spares for this time only. I cannot see what will change. Can anybody give me any clues? Any ideas will be very much appreciated. Tim

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Subject: Spreadsheet simulation of finite mission with repair
Reply Posted by: Larry George ( )
Organization: Problem Solving Tools
Date Posted: Sun Oct 31 20:16:55 US/Eastern 2004
Thank you for sharing your interesting problem of finding the minimum spares level for specified probability of no stockout, for a finite mission with repair. That is not covered by the usual Poisson spares solution. A spreadsheet simulates the probability of no stockout during a mission as a function of failure (demand) rate, repair time, mission horizon time, and spares level. In the spreadsheet, enter your failure (demand) rate, repair time, mission horizon time, and a trial spares value in the attached spreadsheet table 1. Hit F9 to recalculate. Table 1 reports P[No stockout|spares, etc.] for each simulation. If P[No stockout|spares, etc.] is greater than desired Hold down F9 and watch for P[No stockout|spares, etc.] to flicker. If it flickers, there are several values of P[No stockout|spares, etc.]. Press F9 repeatedly and do an eyeball analysis to see whether the eyeball average P[No stockout|spares, etc.] is sufficiently great and to see if any values of P[No stockout|spares, etc.] are scary or scarily frequent. Adjust the spares value to achieve a comfortable average P[No stockout|spares, etc.] without frequent, scary deviations. Please let me know whether the spreadsheet simulation suits your needs and the implementation is adequate. Alternatives are: 1. Replicate table 1 many times and take the average P[No stockout|spares, etc.] and manually optimize the spares value. 2. Program the simulation in VBA, with a search for the min. spares level that achieves at least a desired P[No stockout|spares, etc.]. 3. Question the constant failure rate assumption! Test that assumption. Send field data and I will send back nonparametric estimates of age-specific field failure rates, and modify the simulation to suit.

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