Robust parameters determination for ergonomical product design via computer musculoskeletal modeling and multi-objective optimization

This research aims to determine the optimum parameter values for ergonomic product designs via computer musculoskeletal modeling (CMM) and multi-objective optimization (MOO). The multiple-muscle activities measured by the AnyBody (AB) Modeling System are used to develop the functional relationships with product design parameters via a statistical method, such as design of experiment (DOE). One DOE, Response Surface Methodology (RSM), is adopted in the present approach. Such functional relationships are considered as objective functions which will be further formulated via compromise programming (CP) for multi-objective optimization MOO) problems. A bike-frame design problem is chosen herein as an example to demonstrate the proposed method; it includes determining the lengths of the stem, head tube, fork, top tube, seat post, seat tube and pedal crank. Two cases related to the proposed approach are also introduced: one is a deterministic product design under certain conditions, and the other is a robust product design under uncertain conditions. Because the combination of computer musculoskeletal modeling, statistical method, and multi-objective optimization technique is realized in the proposed approach, ergonomic product designs for safety and efficiency under uncertainty can be achieved in the early stage of other product designs.