System reliability assessment using covariate theory

• Published in: Annual Symposium Reliability and Maintainability, 2004 - RAMS pp. 18 - 24
• Main Authors: Wallace, J.M., Mavris, D.N., Schrage, D.P.
• Format: Conference Proceeding
• Language: English
• Published: Piscataway NJ IEEE 2004
• Subjects: Applied sciences; Computational modeling; Computer simulation; Distribution functions; Exact sciences and technology; Hazards; Input variables; Life estimation; Life testing; Operational research and scientific management; Operational research. Management science; Predictive models; Reliability; Reliability theory. Replacement problems; System testing; Probabilistic approach; Computer simulation; Dependability; Turbojet; Rupture; Reliability theory; Software component; Maintainability; Conditional probability; Covariate; System reliability; Failures; Modeling; Marginal distribution; Distribution function; Turbine blade
• ISBN: 0780382153; 9780780382152
• DOI: 10.1109/RAMS.2004.1285417

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.