A Neuro-Fuzzy Based Approach to Modeling Affective Customer Satisfaction towards Car Seat Design

Today numerous car seat models are available in the market but no car seat is actually satisfying customer needs to satisfactorily level. In fact customers comprise with available car seats. By considering this factor this paper mainly concentrated on the human comfort. This research papers helps to understand the current seat problems and its recommended solutions. This paper proposes a neuro fuzzy rule-based approach to generate models relating car seat design variables to affective user satisfaction. Affective user satisfaction such as body contact, sweat and heat generation, shoulder support, head rest support, lumbar support and child safety were modeled for Car seat designs. The main objective is to generate a new car seat model in order to provide maximum human comfort. Maximum human comfort is estimated by an intelligence system called Neuro fuzzy system, where it gives the comfort of seat with respect to its influencing parameters. By adopting this neuro fuzzy logic eliminate the antiquity of modifications, whether they are correct or not and the results gives us an accurate decision to adopt the change or not. Developed model suits best whenever there is lot of vagueness in decision making using MATLAB M-code.