Failure Rate Adjustments
The premise of a calculation model is that the failure rate of a system is primarily determined by the failure rates of the components that comprise the system. As a result, the equations for calculating component failure rates are commonly referred to as component models. The failure rate calculated by a component model is known as an inherent, seed, or base failure rate. This failure rate represents only the physical attributes of the hardware components that make up the assembly or system, subject to the environmental conditions and operating profile characteristics associated with its application.
The failure rate that an assembly or system actually experiences in the field can be better or worse than the base failure rate. You can adjust the base failure rates calculated by component models by taking additional failure information into account. The use of multiplicative and additive adjustment factors, Telcordia calculation methods, and 217Plus and PRISM techniques such as process grades, Bayesian analysis, and predecessor analysis all provide for adjusting the base failure rates calculated by component models.
You can use multiplicative and additive adjustment factors with any model. When feasible, you can also use the failure rate adjustment techniques provided by one calculation model to adjust the base failures calculated by another model. For example, you can use the various Telcordia calculation methods to use burn-in, laboratory, and/or field data to adjust base failure rates calculated by a MIL-HDBK-217 model.
The use of process grades, Bayesian analysis, and predecessor analysis methods, which are provided by the 217Plus and PRISM models, can be used to make failure rate adjustment to predictions computed by any model but IEC TR 62380 or RDF 2000. The following table provides references to topics that supply additional information about how these various techniques for adjusting base failure rates are used.
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Adjustment Technique
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Reference
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Multiplicative and Additive Adjustment Factors
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Telcordia Calculation Methods
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Process Grades
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Bayesian Analysis
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Predecessor Analysis
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When you use failure data to adjust base failure rates, it is critical that you do not account for this data more than once. Many ways exist for inadvertently doing this. For example, assume that an assembly consists of parts with specified failure rates and parts with calculated failure rates. If you enable a Prediction Bayesian file for the assembly, the field data in this file is used to adjust both the specified and calculated failure rates for the parts in the assembly. If the parts with specified failure rates already include failure data adjustments, then field failure data would be accounted for twice. Now assume that you selected a Telcordia calculation method for the assembly that supports field failure data and that you have entered data in the Method Data panes for the assembly and its parts. If you enter multiplicative or additive failure rate adjustment factors for the assembly or a part, it is possible that field failure data would be accounted for twice.
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