Zhenyu Liu, Zhinan Li, Guodong Sa, Hui Liu, Jianrong Tan
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引用次数: 0
Abstract
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.
期刊介绍:
The aim of the Journal of Mechanical Science and Technology is to provide an international forum for the publication and dissemination of original work that contributes to the understanding of the main and related disciplines of mechanical engineering, either empirical or theoretical. The Journal covers the whole spectrum of mechanical engineering, which includes, but is not limited to, Materials and Design Engineering, Production Engineering and Fusion Technology, Dynamics, Vibration and Control, Thermal Engineering and Fluids Engineering.
Manuscripts may fall into several categories including full articles, solicited reviews or commentary, and unsolicited reviews or commentary related to the core of mechanical engineering.