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Modern fatigue analysis techniques, that can provide reliable estimates of the service performance of components and structures, are finding increasing use in vehicle development programs. A major objective of such efforts is the prediction of the field performance of a fleet of vehicles as influenced by the host of design, manufacturing, and performance variables. An approach to this complex problem, based on the incorporation of probability theory in established life prediction methods, is presented. In this way, quantitative estimates of the lifetime distribution of a population are obtained based on anticipated, or specified, variations in component geometry, material processing sequences, and service loading. The application of this approach is demonstrated through a case study of an automotive transmission component.

The incorporation of reliability theory into a fatigue analysis algorithm is studied. This probabilistic approach gives designers the ability to quantify “real world” variations existing in the material properties, geometry, and loading of engineering components. Such information would serve to enhance the speed and accuracy of current design techniques. An automobile wheel assembly is then introduced as an example of the applications of this durability/reliability design package.

Procedures are developed for assessing the influence of various material and processing factors on the fatigue performance of leaf springs. Cyclic material properties, determined from smooth axial specimens of spring steel, are used to determine the level and cyclic stability of residual stresses resulting from mechanical processing as well as the amount of permanent deformation associated with presetting operations. A damage parameter, incorporating material properties, residual stress effects and applied stressing conditions, is used to predict failure location, i.e. surface or subsurface, and lifetime as a function of processing sequence. Predictions are found to be in good agreement with experimental bending results.