Influence factor analysis and reliability based design optimization of a cab suspension using principal component analysis

The objective of reliability-based design is to consider the performance and reliability of uncertain systems, simultaneously. This is expected to guarantee that a minimum level of reliability is maintained and to improve ride comfort and tilting convenience in a commercial vehicle cab suspension system. In this paper, we propose the principal component analysis to explain the covariance structure through linear combinations of multi-response problems. The analysis of variance and quality loss function is used to investigate the effects of combined multiple performance constraints. We determine the rank of each factor to reduce these design variables. In this work, fifteen control factors, two noise factors and two multi-responses are used for the analysis of a cab suspension, and a total of 81 Taguchi experiments are performed.