Selection of the optimal scheme for the conceptual design of a polisher considering multi-source uncertainties

Conceptual design plays an important role in determining the basic characteristics and final product performances. However, there are many uncertainties in the conceptual design, such as the vagueness of customer requirements, uncertainty of design parameters, and diversity of the decision-making, which will lead to fluctuations in the performance or even failure of the scheme in many cases. To solve this problem, a conceptual design model was constructed by considering multi-uncertainties. First, taking satisfaction, performance, and production cost as design objectives, a conceptual design optimization model was established. Secondly, an improved non-dominated sorting genetic algorithm-II (NSGA-II) based on the expectation-possibility-probability hybrid model was proposed to search the Pareto solutions of conceptual design. Finally, the optimal conceptual design scheme was selected from the Pareto set by using the intuitionistic fuzzy λ-Shapely Choquet integral method. The effectiveness and efficiency of the proposed method were validated by the polishing machine conceptual design.