Generation And Evaluation Of Product Design Alternatives Based On Computational Methods

In order to realize the automation,objectivity and efficiency of the product conceptual design process,a methodology of generation and evaluation of product design alternatives based on computational methods is proposed.The quantification and identification of customer preference,the generation of design alternative based on multivariate criteria,the weight determination of product performance criteria and data-driven performance evaluation of design alternatives are conducted in-depth study.The above methods and techniques are applied to the generation and evaluation of design alternatives of the blow molding machine,and then validated.The main contents of the dessertation are as follows:In the first chapter,the background and significance of this research were presented.The research status of the generation and evaluation of product design alternatives was reviewed.Based on the research status,the problems to be studied were presented.Finally,the research contents and framework were introduced.In the second chapter,an improved continuous fuzzy Kano model is proposed.At the early stage of product design,fuzzy customer needs are not easy to be quantified,resulting in the deviation of understanding the needs and affecting the quality of design.The customer needs were extracted by fuzzy Kano model,and then quantified based on the improved requirement classification table.According to the analysis result,the weight of each requriement was determined by information entropy.The feasibility and effectiveness of the proposed method were validated by the application of the quantification and identification of customer preference of a blow molding machine.In the third chapter,the generation of design alternatives based on multivariate criteria is proposed.The multiple coupling problem in the process of transforming customer needs to quality characteristics and the combinatorial explosion problem during the generation of design alternatives are focused on.Firstly,the evidence reasoning theory was implemented to realize the mapping of customer needs to quality characteristics,and the importance degree of each quality characteristic is obtained.Then,based on the quality characteristic and the structural compatibility,the multi-objective optimization model to generate design alternatives was established.The improved non-dominated sorting genetic algorithm(NSGA-II)was utilized to solve this model,and obtain the non-dominated solutions of the model,namely the candidate design alternative set.The feasibility and effectiveness of the proposed method were validated by the application of the design alternative generation of a blow molding machine.In the fourth chapter,rough number-based Decision Making Trial and Evaluation Laboratory(DEMATEL)method is proposed.In the process of determining the weights of the performance criteria,the uncertain and vague decision information of the association relationships between the criteria need to be analyzed.Rough number was applied to quantify the decision information,and the association relationships between the criteria were analyzed by DEMATEL.Finally,the weight of each performance criterion was obtained.Taking the performance criteria of a blow molding machine as an example,the effectiveness of the proposed method was described in detail.In the fifth chapter,the data-driven performance evaluation of design alternatives is proposed.The problem of over-reliance on experts' domain knowledge and experience in the process of design alternative evaluation results in time consuming and subjectivity during obtaining the optimal design alternative.Based on the design data of products,the prediction model of the performance criterion was constructed by Particle Swarm Optimization(PSO)-based Support Vector Machine(SVM).Based on the obtained model,the values of performance criteria of each candidate design alternaitve were predicted.According to the weight of each performance criterion and the predictive performance values of each design alternative,the alternaitves were sorted by Vlsekriterijumska Optimizacija I Kompromis Resenie(VIKOR),and the optimal design alternave is acuquried.Finally,the effectiveness of the proposed method was verified by the case study of a blow molding machine.In the last chapter,the research contents and prospects of the future research were summarized.