Theories And Methodologies For Product Family Reconfigurable Design And Application In Large Scale Air Separation Systems

To deal with the conflict between scale economies with batch production while meeting customers' individual requirements in Mass Customization,aiming at the development of scale-based product family,the theories and methodologies for product family reconfigurable design are investigated and illustrated in the development of air separation system.The theory model for product family reconfigurable design is put forward.The technologies and methodologies including the analysis and prediction for dynamic requirements,two-stage programming reconfiguration for scalable product family,product family commonality and performance optimizing reconfiguration and product family robust reconfiguration with fuzzy clustering are deeply studied.With the actual project,an integrating product family reconfigurable design system is developed and applied in the design process of air separation. system.The organization structure of the full text is as follows:Chapter 1 gives the reviews of product family design and reconfigurable design.The requirements of large scale air separation system for product family reconfiguration are analyzed,and the shortage of present research for product family reconfigurable design is proposed.Then the research content and architecture of the dissertation is presented.Chapter 2 puts forward the theory framework for reconfigurable design of product family. The platform based product development mode is discussed firstly.Then the differences between scale-based product family and other family models in definitions,characteristics and applications are analyzed.The theory model,optimization model and design process model of scale-based product family reconflgurable design are proposed,and the methods system for reconfigurable design of product family is constructed.Chapter 3 proposes the analysis and prediction for dynamic requirements in House of Quality(HOQ) based on grey theory.Applying grey relational analysis,the real customer preferences and levels are analyzed through the fuzzy,unclear and non-quantitative customer requirements.Based on the GM(1,1 ) grey prediction model,the importance trend prediction for customer requirements and technical measures are conducted.They are able to exclude the instable factors during the multi-criteria decision making process in HOQ,and propose the improvement direction for product series design.The instance of requirement analysis for deep cooling air separation system illustrates the robustness and effectiveness of the methods.Chapter 4 studies the product family programming reconfiguration method based on new multi-objective evolutionary algorithms.The multi-objective particle swarm optimization algorithm based on crowding distance sorting is put forward.With the elitism strategy, evolution to disperse region and small probability mutation,the algorithm guarantees the convergence and diversity of the Pareto front.The process for the reconfiguration of single platform product family using multi-objective optimization is proposed.The platform common variables programming and the scaling variable setting of instance product are achieved in two following stages.Moreover,a typical instance is given related with the family design of large scale row material air compression machinery.Chapter 5 puts forward the commonality and performance optimizing reconfiguration method using hybrid co-evolutionary algorithms.Based on the two-dimensional chromosome representation scheme of multi-platform design space,the evolutions of commonality and design variable populations are run in relevant master-slave process.The improved non-dominated sorting genetic algorithm and particle swarm optimization are executed respectively so as to avoid the data disturbance in synchronous evolution.The feasibility and effectiveness of proposed approach are demonstrated by a case of optimizing a family of turbo expanders.Chapter 6 proposes a robust reconfiguration method for scale-based product family using sensitivity analysis and fuzzy clustering analysis.During the platform design stage,sensitivity analysis is performed firstly to help select the candidate platform common variables and scaling variables.Then,in order to construct the reasonable platform sharing strategy,the changes of performance,deviation and constraint satisfaction among instance products caused by the sharing of design variables are clustered using fuzzy c-means algorithm.The efficiency and effectiveness of the method are illustrated through the reconfiguration of an existing plate-fin heat exchanger family.Chapter 7 develops the integrating product family reconfigurable design system(HYFD) with the practical project.The application and implementation in the design of air separation system have proved the validity and feasibility of the proposed methods in this dissertation.Chapter 8 summarizes the dissertation and prospects the future research work.