Research On Product Configuration And Assembly Line Optimal Scheduling For Mass Customization

The complex product markets of the twenty-first century will demand the ability to quickly and globally deliver a high variety of customized products. Mass customization (MC) is the key strategy to meet this challenge. MC does not only represent product development, but also represent product manufacturing. Based on several projects, the whole dissertation focuses on MC, chiefly including some key enabling technologies to support the implementation of MC effectively.Configuration-Oriented product model (COPK) is used to describe the composition and components'relationship in the product; it is the basis of product configuration. The characteristics of COPK are analyzed, several chief concepts are defined, and the process of product configuration based on COPK is provided. The multi-objective genetic algorithm is analyzed.Traditional CSP′s limitation of knowledge representation in product configuration is analyzed. A Type of Product Configuration Method Based on Dynamic Constraint Satisfaction Problem (PDCSP) is purposed. It has more capability for representing knowledge and less searching than traditional CSP.In order to solve the problem of multi-objective optimization of production configuration, a multi-objective genetic algorithm is developed, and then the coding and decoding representation of the solution as well as the calculation of the fitness function are designed. The performance comparison of the proposed genetic algorithm with three other genetic algorithms is made. It is shown that the proposed genetic algorithm outperforms the others.Following the idea of software reuse and taking a product of assembly type into consideration, this dissertation put forward the general principles of new product development based on component and architecture reuse, and describes their key techniques such as component/architecture relevance and assembly constraint check. In addition, a MC oriented product version management method is proposed.In order to solve the scheduling problems of automobile assembly line in the environment of mass customization, a multi-objective optimization scheduling method is described and its mathematical formulas are provided; a multi-objective genetic algorithm is designed for finding near-Pareto or Pareto optimal solutions of the problems. And then the coding and decoding representation of the solutions as well as the calculations of fit ness functions are designed. A new genetic evaluation and selection mechanism is proposed.Finally, this dissertation introduces the implantation of product configuration and assembly line scheduling in some projects, which testified the advancement and practicability of research achievements in this dissertation.