A Predictive Process for Spring Failure Rates in Automotive Parts Applications

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. The endurance limit of a mechanical component will usually differ from the endurance limit of the material determined from the laboratory tests conducted on a rotating-beam specimen. The endurance limit of the mechanical component will depend upon its surface finish, size, temperature, stress concentration and other factors. Having determined the fatigue life, the mean time between failure (MTBF) and the failure rate is computed based on the assumption of a constant failure rate. Once there is a reasonable correlation of the modeled spring failure rate to field test data, the information becomes very useful for early product development reliability assessment. Knowing the approximate failure rate of the spring for an assembly application provides valuable input for reliability predictions, fault tree analyses, and FMECA (failure modes, effect, and criticality analyses).