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This paper will focus on the process, as used at AC Rochester, of performing reliability analyses early in the design phase of automotive component development and the integration of specific techniques and methods. This methodology forms an effective tool that achieves the identification of component failure modes and mechanisms with greater confidence than any single technique and provides for the simple and direct communication of the results. In addition, our experience shows that this process provides the maximum preventive impact on the product during the design phase, thus yielding demonstrably improved reliability characteristics on the production part. Specifically, a four-step up-front analysis process can facilitate the usefulness of various analytical techniques to the identification of product reliability problems.

This paper discusses an analytical technique for computing the failure rate of steel springs used in automotive part applications. Preliminary computations may be performed and used to predict spring failure rates quickly at a very early stage of a product development cycle and to establish program reliability impact before commitment. The analytical method is essentially a combination of various existing procedures that are logically sequenced to compute a spring probability of failure under various operational conditions. Fatigue life of a mechanical component can be computed from its S-N curve. For steels, the S-N curve can be approximated by formulae which describe the fatigue life as a function of its endurance limit and its alternating stress. Most springs in service are preloaded and the actual stress fluctuates about a mean level. In order to compute an equivalent alternating stress with zero mean, an analytical method based on the Goodman Diagram is used.