Multi-Indicators Decision for Product Design Solutions: A TOPSIS-MOGA Integrated Model

Zeyuan Yu,Xin Guo,Ying Liu,Huicong Hu,Chuan Fu,Wu Zhao

doi:10.3390/pr10020303

Abstract

Design decisions occur in all phases of product design and largely affect the merits of the final solution, which will ultimately determine the success or failure of the product in the market. Product design is a continuous process, and a large number of existing studies have proposed decision methods and decision indicators for the characteristics of different stages of design. These methods and indicators can meet the requirements of one of the phases: demand analysis, conceptual design, or detailed design. However, further research can still be conducted on the integration of methods throughout the design phase, using intelligent design methods, and improving the design continuity and efficiency. To address this problem, a TOPSIS-MOGA-based multi-indicators decision model for product design solutions is proposed, including its product design process, decision algorithm, and selection method. First, a TOPSIS-MOGA integrated model for conceptual design and detailed design process is established, the continuity of decision-making methods is achieved by integrating decision indicators. Second, conceptual design solutions are selected through the technique for order of preference by similarity to ideal solution (TOPSIS), based on hesitant fuzzy linguistic term sets and entropy weight method. Finally, detailed design solutions are selected through a multiobjective genetic algorithm (MOGA), based on a polynomial-based response surface model and central combination experimental design method. A case study of the decision-making in the design of high-voltage electric power fittings is presented, the conceptual design phase and the detailed design phase are connected through the indicators, which demonstrates that the proposed approach is helpful in the decision-making of the product design solutions.

Highlights

Studies show that the product design phase accounts for only 12% of the total cost of product development but can affect 75% of the final cost [? ]
In the conceptual design stage, a TOPSIS-based product solution decision method is constructed to assist designers in solution decision-making, through evaluation statement identification based on hesitant fuzzy linguistic term sets, evaluation matrix construction based on TOPSIS, and decision calculation based on entropy weight method
We propose a multiobjective genetic algorithm (MOGA) algorithm-based decision-making method for product detailed design solutions, constructing decision indicators for product detailed design solutions, constructing a sample set of detailed design solutions based on the central combination test method, and MOGA multiobjective optimization to achieve solution decision-making

Summary

Introduction

Studies show that the product design phase accounts for only 12% of the total cost of product development but can affect 75% of the final cost [? ]. ], in this process, workflow, knowledge flow, and information flow interact with each other, many design solutions are generated at each stage [? ], and the design continuity needs to be noticed [? ]. As researchers continue to study the field of product design, intelligent design methods are becoming increasingly important [? ]. These methods focus on design process models [? ], the product design solution methods [? These methods will further promote the development of product design, improve the continuity and efficiency of design [?

Methods

Results

Conclusion