Robust Ergonomic Optimization of Car Packaging in Virtual Environment

Ergonomic design of automotive seat is a very challenging task whose results may directly influence driver’s comfort and safety. Seat comfort can be improved by identifying car-packaging solutions that allow an optimal driver’s posture. In order to reduce the time and cost for testing, ergonomic analysis is car- ried out in virtual reality (VR) environment with digital human models (DHM) that can be used to simulate the anthropometric variability of a target population of users and thus verify the robustness of design solutions with respect to the an- thropometrical noise factor. In this paper we illustrate a case study concerning the comfort improvement of a minicar packaging set up via robust ergonomic design (RED) with digital human models. The aim is the identification of the optimum levels for the seat control parameters that minimize the driver’s comfort loss with respect to a preferred posture. The approach adopted for the analysis of data ob- tained from the virtual experiments is based on the joint generalized linear model- ing of mean and dispersion of the driver’s postural comfort loss (i.e. the ergonom- ic response of interest).