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Fretting fatigue crack nucleation in Ti−6Al−4V when fretted against itself is investigated to determine the influence of contact pressure, stress amplitude, stress ratio, and contact geometry on the degradation process. For the test parameters considered in this investigation, a partial slip condition generally prevails. The resulting fatigue modifying factors are 0.53 or less. Cycles to crack nucleation, frictional force evolution, crack orientations and their relationship to the microstructure are reported. The crack nucleation process volume is of the same order as the microstructural length scales with several non‐dominant cracks penetrating 50 μm or less. The effective coefficient of friction increases during early part of fretting. Observations suggest that cyclic plastic deformation is extensive in the surface layers and that cyclic ratchetting of plastic strain may play a key role in nucleation of the fretting cracks. A Kitagawa–Takahashi diagram is used to relate the depth of fretting damage to the modifying factor on fatigue life.

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System quality and reliability are becoming increasingly more important for maintaining market place competitiveness and customer satisfaction. The objective of this paper is to demonstrate the application of the Taguchi Method as a straightforward means of improving product quality using simulation based predictions of the operating life of a critical gas turbine component. The method is applied to statistically select a set of creep life simulations that will illuminate a bucket design which is least sensitive to component and operating environment variation. Implications of this method to improving turbine component quality at the design level are discussed. The results of the Taguchi Method are compared to a robust design solution found using the more time consuming, yet more accurate Response Surface Monte Carlo method. Apparent advantages and limitations of the Taguchi method as applied to turbine component design are discussed.

A method is demonstrated that utilizes covariate theory to generate a multi-response component failure distribution as a function of pertinent operational parameters. Where traditional covariate theory uses actual measured life data, a modified approach is used herein to utilize life values generated by computer simulation models. The result is a simulation-based component life distribution function in terms of time and covariate parameters for each failure response. A multivariate joint probability covariate model is proposed by combining the covariate marginal failure distributions with the Nataf transformation approach. Evaluation of the joint probability model produced significant improvement in joint probability predictions as compared to the independent series event approach. The proposed methods are executed for a nominal aircraft engine system to demonstrate the assessment of multi-response system reliability driven by a dual mode turbine blade component failure scenario as a function of operational parameters.