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Failure rate
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==Measuring failure rate== Failure rate data can be obtained in several ways. The most common means are: ;Estimation:From field failure rate reports, statistical analysis techniques can be used to estimate failure rates. For accurate failure rates the analyst must have a good understanding of equipment operation, procedures for data collection, the key environmental variables impacting failure rates, how the equipment is used at the system level, and how the failure data will be used by system designers. ;Historical data about the device or system under consideration: Many organizations maintain internal databases of failure information on the devices or systems that they produce, which can be used to calculate failure rates for those devices or systems. For new devices or systems, the historical data for similar devices or systems can serve as a useful estimate. ;Government and commercial failure rate data: Handbooks of failure rate data for various components are available from government and commercial sources. MIL-HDBK-217F, ''Reliability Prediction of Electronic Equipment'', is a [[United States Military Standard|military standard]] that provides failure rate data for many military electronic components. Several failure rate data sources are available commercially that focus on commercial components, including some non-electronic components. ;Prediction: Time lag is one of the serious drawbacks of all failure rate estimations. Often by the time the failure rate data are available, the devices under study have become obsolete. Due to this drawback, failure-rate prediction methods have been developed. These methods may be used on newly designed devices to predict the device's failure rates and failure modes. Two approaches have become well known, Cycle Testing and FMEDA. ; Life Testing: The most accurate source of data is to test samples of the actual devices or systems in order to generate failure data. This is often prohibitively expensive or impractical, so that the previous data sources are often used instead. ;Cycle Testing: Mechanical movement is the predominant failure mechanism causing mechanical and electromechanical devices to wear out. For many devices, the wear-out failure point is measured by the number of cycles performed before the device fails, and can be discovered by cycle testing. In cycle testing, a device is cycled as rapidly as practical until it fails. When a collection of these devices are tested, the test will run until 10% of the units fail dangerously. ;FMEDA: [[Failure modes, effects, and diagnostic analysis]] (FMEDA) is a systematic analysis technique to obtain subsystem / product level failure rates, failure modes and design strength. The FMEDA technique considers: * All components of a design, * The functionality of each component, * The failure modes of each component, * The effect of each component failure mode on the product functionality, * The ability of any automatic diagnostics to detect the failure, * The design strength (de-rating, safety factors) and * The operational profile (environmental stress factors). Given a component database calibrated with field failure data that is reasonably accurate,<ref>{{cite book | title = Electrical & Mechanical Component Reliability Handbook | publisher = exida | year = 2006 | url = http://www.exida.com }}</ref> the method can predict product level failure rate and failure mode data for a given application. The predictions have been shown to be more accurate<ref>{{cite book | last = Goble | first = William M. |author2= Iwan van Beurden | title = Combining field failure data with new instrument design margins to predict failure rates for SIS Verification | publisher = Proceedings of the 2014 International Symposium - BEYOND REGULATORY COMPLIANCE, MAKING SAFETY SECOND NATURE, Hilton College Station-Conference Center, College Station, Texas | year = 2014 }}</ref> than field warranty return analysis or even typical field failure analysis given that these methods depend on reports that typically do not have sufficient detail information in failure records.<ref>W. M. Goble, "Field Failure Data β the Good, the Bad and the Ugly," exida, Sellersville, PA [http://www.exida.com/resources/whitepapers.asp]</ref>
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