Improved Operational Testing and Evaluation and Methods of Combining Test Information for the Stryker Family of Vehicles and Related Army Systems Phase II Report (2004) / Chapter Skim
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3. Combining Information in Practice
3. Combining Information in Practice
Pages 40-52
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From page 40... ...
Although live, full-system test data are no longer available, there is a great deal of relevant information including results from computer simulations, historical test data, subsystem tests, and expert judgment available through a large and multidisciplinary community that includes engineers, physicists, materials scientists, statisticians, and computer scientists. Traditional reliability demonstrations would be very difficult, and traditional statistical methods must be significantly expanded to include the representational methods discussed above and the 40
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From page 41... ...
For example, all instances in which Stryker is found to be transportable on a C-130 aircraft, whether from a training exercise or in developmental or operational testing, provide valid information about transportability. The various methods described above for combining information for use in assessing reliability (and other related methods)
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From page 42... ...
The operational test can also provide data on sample attrition rates that can be used as input to aggregated models. In either case, the simulations and models could then be used to augment the limited number of situations considered in the operational test by simulating other operational situations to provide a larger base of information for evaluating the survivability and effectiveness of Stryker and the SECT.
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From page 43... ...
The major sources include operational testing, developmental and technical testing, contractor testing, data from previous tests of similar systems, training exercises, experience of foreign armies with vaiants of the Stryker (though these systems are not very similar, which
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From page 44... ...
Unfortunately, even in this case, minor differences will often be explained away if there is pressure for a certain interpretation of the results. Combining Test Data Operational testing for the Stryker will involve many vehicles over relatively short exposure periods.
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From page 45... ...
or for different categories of subsystems show significant variations, it may still be possible to determine whether those variations are due primarily to a single factor. For example, failure rates during developmental testing may differ from the rates under operational testing, but for a particular group of failure modes the ratios of failure rates under the operational test to those under the developmental
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From page 46... ...
(Note that although this example is presented, for ease of explication, in the context of exponential lifetime analysis, it applies as well to other lifetime models.) If data from several previous systems are available during the developmental and operational tests, and if one finds that for specific components a failure rate during the operational test is roughly a certain multiple of the corresponding failure rate under the developmental test, then such a factor could be used to analyze the data for a current system for the same type of component in a combined fashion.
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From page 47... ...
Here there is a trade-off between a larger data collective and a somewhat more uncertainly defined population, i.e., between a relatively large variance for the random effects and a relatively small variance. Combining Test Data: WeilDull Models A popular extension of the exponential model is the Weibull model, which not only describes the lifetimes of components and replaceable units that fail due to external causes, but also provides a framework for lifetimes that arise from wear-out failures or infant mortality.
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From page 48... ...
Here the case for combining information becomes even stronger than in the exponential situation. If the shape parameter ~ is approximately known from previous experience, the Weibull lifetime data individual values Xi can be transformed via Xi ~ Xi~ into exponentially distributed data, and all the methods discussed above carry over.
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From page 49... ...
structures, accelerated testing, robust design, computer modeling, importance sampling in fault tree analyses, increasing reliability through redundant system design, probabilistic design, and structured programs for design for reliability, such as design for six sigma. Reliability practices and procedures differ from industry to industry and from company to company within an industry, and often remain proprietary, especially with respect to the development of models that can be used to more effectively predict reliability without having to do expensive physical testing.
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From page 50... ...
Inputs to reliability models, including associated uncertainties, need to be determined. Assuming the same or similar environmental conditions, previous experience with particular materials and components can be used directly; examples include experiences codified in MIL-HDBK-5 and MILHDBK-17 (handbooks for metals and composite materials)
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From page 51... ...
Separate tests may have to be conducted to excite different failure modes; for example, in automobile engine testing there is a standard test using a continuous run protocol and another that uses a start-stop-start protocol. While it is feasible and effective to use up-front testing of components and subsystems to assess their reliability characteristics, the same is not usually true for major systems whose reliability goals and costs are very high.
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From page 52... ...
Similar cyclic dynamic tests examine a new aircraft frame for fatigue failures. Because such factors typically have no known associated reliability, a major analysis of them based on analytical probabilistic design models and experience in the field could have longrange benefits.
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