Multi-objective optimisation of the passenger car seat frame using grey relational analysis and grey entropy measurement

At present, more attention has been paid to the performance and lightweight design for passenger car seats. The optimisation design for seat frame is performed in this research. The innovation is that a particular method of lightweight optimisation is proposed according to the characteristics of seat frame. The best thickness-material scheme of the parts that needs to be optimised (opti-parts) is obtained by applying the method of grey relational analysis (GRA), grey entropy measurement, and average strain indices (GRA & GEM(ASI)). Moreover, in order to verify the advantages of GRA & GEM(ASI), a comparison is made among several different techniques. The results show that, not only the gross cost and gross mass of opti-parts are reduced by yen 3.13 (16.68%) and 0.67kg (16.88%), respectively, but also the performance and reliability of seat frame is well guaranteed. The method of GRA & GEM(ASI) proposed makes significant contributions effectively performed in multi-objective optimisation design for passenger car seat frames.