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    reliability

    Rates Can be Deceiving

    Wednesday, July 2nd, 2008

    This article recently brought up an excellent point on how some rates can be deceiving, and even reduce the likelihood that we will make the right decision. The example involved comparing impressions of fuel efficiency in miles per gallon versus gallons per mile, or gallons per ten thousand miles. While identifying the better of two […]

    Reliability is Not a Constant

    Tuesday, June 10th, 2008

    Often as a reliability engineer, or anyone responsible for researching the reliability of an item, or calculating it, you will find oversimplified published data giving you the impression that reliability is an unchanging physical property like mass or volume, something intrinsic to the materials included in it. This is actually the common sense approach; we […]

    Zero-Failure Reliability Testing

    Wednesday, June 4th, 2008

    So, you’ve got a design that you want to prove is better than the existing design from your own or another company. What’s the most efficient, fastest way to get to that answer with a very small sample size? Whle there may be several options you have, including accelerated testing, they each can have their […]

    Calculating Reliability with Partial Test Results

    Wednesday, May 14th, 2008

    Getting answers before you are finished. Why are people always so impatient? Why can’t they just wait until testing is complete before they ask for answers? I suppose it is just human nature, as I have heard that question any time I have been involved in reliability testing programs. And, although we would know much […]

    Convert B10 or L10 Bearing Life to MTBF (Mean Time Between Failures)

    Thursday, May 8th, 2008

    As a reliability analyst, sometimes none of your data matches the form you are interested in. It all comes in different collections of units, statistical distribution parameters, failure rates, environments, MTBF, MTTF, and on and on. In this article, let’s consider one common conversion for which my research found too little information available […]