Research On Key Technologies And Methodologies For Customization Products Intelligent Recombine Design And Application

The key technique and methodologies for customization products intelligent recombine design are investigated and illustrated in the course of customization products design. The modeling theories and technologies of customization products recombine design is describe. The requirement knowledge noumenon of customization products recombine design is expressed and analysed based on the Rough Set Theory. Multiscale module planning recombine method for customization products is presented. Then the multi-objective optimization intelligentl configuration recombine method of modularized product is put forward. The parametric customization products performances optimization method is carried out to optimize the individual product performances based on the recombined products platform with a feasible commonality level. With the actual project, an integrating customization products recombine design system is developed and applied in the design process of complicated machine equipment to prove the method's feasibility and validity.The organization structure of the full text is as follows:Chapter 1 gives the key technologies, methodologies and application reviews of customization products design methods. The shortage of present research for customization products recombine design is proposed. Then the research significance of customization products recombine design in this dissertation is presented. At last, the the research content and architecture of the dissertation is carried out.Chapter 2 studies the modeling theory and technologies of customization products recombine design. The design object, design platform and design flow of customization products recombine design is expatiated. Aim at universal module customization products, the customization products model based on three view model, generic-bill-of-materials model and tabular layouts of article characteristics model is gived out. Aim at universal module customization products, the parameter modeling technique is presented. At last, the customization products recombine design integration methods system is constructed.Chapter 3 proposes the requirement knowledge noumenon expression method, the requirement knowledge noumenon is decompound in multi-granularity and analysed based on the Rough Set Theory. As a result the requirement knowledge is appraised according to the importance to achieve the reduction. Which instruct the customization products recombine design course. At last, the technology is applied in the requirement knowledge expression and analysis of air separation to illustrate the flexibility and effectiveness of the methods.Chapter 4 puts forward the multiscale module planning recombine method for customization products based on SPEA2+. The multiscale module planning optimization model is constructed based on the multiscale module planning principles. Aiming at the problem of traditional objective weighted method, an improved strength Pareto evolutionary algorithm is employed to optimize the multiscale optimization model parallelly. As a result, a serial of module planning recombined schemas are presented in the form of Pareto optimal set. Moreover, an approach based on fuzzy set theory was developed to extract one of the Pareto-optimal solutions as the best compromise one. At last, an instance related with the project which was applied in the Expander is given to prove the method's feasibility and validity.Chapter 5 puts forward the multi-objective optimization intelligentl configuration recombine of modularized product based on NSGA-â…¡. Method based on the fuzzy evaluation theories and the least squares approximation is advanced to construct the objective functions, namely the performance,cost and term base on modular architecture of customization products. Consequently, An improved non-dominated sorting genetic algorithm method (NSGA-â…¡) is employed to optimize the performance-cost-term multi-objective optimization model of configuration parallelly. As a result, a serial of configuration recombined schemas are presented in the form of Pareto optimal set to satisfy the customers'different demands on the performance, cost and term of product. At last, an instance related with the project which was applied in the air compressor is given to prove the method's feasibility and validity.Chapter 6 proposes the parametric customization products performances collaborative optimization method. The mathematics optimization model of parametric customization products is constructed, the influence degree and difference degree of design parameter is analysed to optimize the constant and variable of platform which affect the product performances. Then the individual product performances is optimized with a feasible recombined platform commonality level based on the intelligent evolution arithmetic. Finally, the design of a family of electromotor is used as an example to illustrate the effectiveness and robust of the proposed approach against previous approachs.Chapter 7 develops the integrating customization products recombine design system (HY_CPRD) with the practical project. The background of system application, implementation scheme, the technical implementation and main functions of the system is elaborated. Chapter 8 summarizes the theory and methods of customization products recombine design. The key research achievements and novelties of this dissertation are concluded along with prospects for future research work.