Herein, we have summarized the problems related to the uncertainties encountered in the product-development process in the manufacturing industry in recent years, and confirmed the importance of formulating product proposals and product-development processes equipped to cope effectively with uncertainty in the early design stage. The objective of this study was to derive the target performance and design priority order taking into account uncertainties in system design.The system-design process assumed in this study is based on the concept of set-based design. The approach adopted was to secure a set of solutions that satisfy the target variables demands, gradually narrowing the solution space as the design progresses, and finally extracting the solution space that is desirable.As it is likely that it can deal with the uncertainty and performance of a product would vary in each solution space, it is important to consider them simultaneously to determine the required value and range of the output target variables. In this study, three types of information were considered simultaneously: bivariate distribution concentration, which expresses the likelihood that design rework may occur, development risk, which can be assessed according to the values of the design and target variables, and preference, which can be determined according to the values of the target variables. Design rework occurs when the design variable can take be determined inassume only a limited number of combinations of levels. To address this drawback, we adopted the approach of dividing the design space into several subspaces and evaluating each of the subspaces.To derive the design priority order, the system design was partitioned into two separate stages, namely, determination of the target variables and an assessment of the design variables. By constructing the design process in this way, it is possible to discuss the degree of design freedom. Based on the strategy of increasing the degree of freedom of the back-end process, a priority order of design was developed using constraint, which is an indicator of the degree to which deciding on a certain design variable restricts the level of freedom of a design variable that is decided at a later stage.The effectiveness of the proposed method was verified using a model for planning and designing an actual plug-in hybrid vehicle. The solution space was divided by restricting target variables to continuous ranges , and each spaces divided was area was analyzed using indicators such as preference, development risk, and distribution concentration.From the results, we confirmed the existence of a trade-off between preference and development risk, and that it is possible to determine the extent to which the solution space can be narrowed. In addition, we confirmed that the shape of the solution space determines the design priorities, and we were able to derive a desirable design priority order according to the target performance.&nbsp;

System Design Priority Order Considering Uncertainty in Early Stages

Paper Proceedings: https://asmedigitalcollection.asme.org/IDETC-CIE/IDETC-CIE2021/volume/85369

ASME 2021 International Design Engineering Technical Conferences & Computers and Information in Engineering Conference (IDETC/CIE2021)

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