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Abstract:
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Manufacturers are continually faced with customer expectations to deliver products faster while assuring high reliability. Companies must diligently plan and execute accelerated life tests in order to insure future reliability performance is met. In many industrial applications, accelerated life testing involves censoring, design and cost constraints, and binary responses that hinder the ability of the analyst to easily define a suitable test plan. A methodology for defining efficient, yet discerning, tests could insure that corporate investments in reliability testing are properly selected to mitigate risk while minimizing cost. This presentation extends classical design of experiment methods to multi-stress accelerated life test plans. In addition, an alternate technique for determining an optimal set of stress test levels is introduced using a generalized linear model framework.
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