This paper deals with an enhanced robust design optimization (RDO) method and its application to the strength design problem of seat belt anchorage, related to the front crash safety of multi-purpose vehicles. In order to determine the rational design safety of the newly developed automotive part, such as the seat, in which the reliability of the evaluation data is not sufficient at the design stage, it is necessary to implement a probabilistic design considering uncertainties. Thickness size variables of the seat frame structure’s members were considered random design variables, including uncertainties such as manufacturing tolerance, which are an inevitable hazard in the design of automotive parts. Probabilistic constraints were selected from the strength performances of the seat belt anchorage test, which are regulated in Economic Commission for Europe (ECE) and Federal Motor Vehicle Safety Standard (FMVSS), and the strength performances were evaluated by finite element analyses. The RDO problem was formulated such that the random design variables were determined by minimizing the seat frame weight subject to the probabilistic strength performance constraints evaluated from the reliability analyses. Three sigma level quality was considered for robustness in side constraints. The mean value reliability method (MVRM) and adaptive importance sampling method (AISM) were used for the reliability analyses in the RDO, and reliability probabilities from the MVRM and the AISM on the probabilistic optimum design were assessed by Monte Carlo simulation (MCS). The RDO results according to the reliability analysis methods were compared to determine the optimum design results. In the case of the RDO with the AISM, the structure reliability was fully satisfied for all the constraint functions, so the most reliable structural safety was guaranteed for the seat frame design.
Enhanced Robust Design Optimization in Seat Belt Anchorage Strength for Front Crash Safety of Multi-Purpose Vehicle