FUZZY MULTI-OBJECTIVE OPTIMIZATION OF AN AUTOMOTIVE SEAT USING RESPONSE SURFACE MODEL AND RELIABILITY METHOD

摘要

The statistical technique based on design of experiments and response surface model is one of the emerging ways to solve the multi-objective optimization and multidisciplinary design optimization. A procedure for a multi-objective optimization based on response surface model and fuzzy decision-making algorithm is proposed. The fuzzy product operator, the so-called geometric mean in fuzzy set theory, is proposed for the fuzzy decision-making algorithm. Design of experiments is utilized for exploring the design space and for constructing the regression models to facilitate the effective solution of multi-objective optimization problems. Response surface models provide an efficient measure to rapidly model the trade-off among many conflicting goals within given probabilistic constraints. Among the MPP (Most Probable failure Point) based probabilistic methods, FORM (First-Order Reliability Method) is used to accurately calculate the value and sensitivity of probabilistic constraints for the multi-objective optimization of an automotive seat. The SQP (sequential quadratic programming) algorithm with fuzzy product operator is successfully integrated for reliability-based multi-objective optimization of an automotive seat. Finally, the results from deterministic, MVFO (Mean Value First Order Second Moment) and FORM reliability method are provided.