Abstract
Determining the proper performance specifications of a complex product under design is the first key step and prerequisite for a successful product design, which determines the length of the design cycle and the success or failure of the design. Usually, a set of design parameters can contribute to a set of complex product performance specifications in a complex and conflicting way, resulting in a set of conflicting performance specifications, coupled with a set of conflicting design parameters. Therefore, to properly determine a set of performance specifications' values, and how to coordinate conflicting design parameters' values to have well-balanced performance specifications' values is a challenging problem in complex product design. This article proposes a conflict coordination method for determining performance specifications' values based on game theory. The method has a novel way to identify the conflicts among design parameters against performance specifications based on the constraint satisfaction problem solving and sensitivity analysis. Among identified conflicting design parameters, a game theory-based coordination model for best reasonably setting up the conflicting design parameters is developed for obtaining well-balanced performance specifications. This coordination model incorporates non-cooperative and master–slave gaming mechanisms, and it is solved by a hybrid game balanced solving algorithm based on the elite information exchange strategy and non-dominated sorting genetic algorithm-II. The feasibility and effectiveness of the proposed method are verified with a case study.
| Original language | English |
|---|---|
| Article number | 091705 |
| Pages (from-to) | 1-14 |
| Number of pages | 14 |
| Journal | Journal of Mechanical Design |
| Volume | 147 |
| Issue number | 9 |
| Early online date | 22 Jul 2025 |
| DOIs | |
| Publication status | Published - 1 Sept 2025 |
Keywords
- complex product design
- performance specifications
- conflict identification
- conflict coordination
- game theory
- data-driven design
- design optimization