Study On The Theory And Methods Of Personalized Product Design Driven By Customer Value

With the intense competition and personalized customer requirement,the global economy has been developed rapidly.The unified and stable seller's market has been replaced by the difference and dynamic buyer's market,and customer participation in design has greatly increased.The manufacturing enterprises have to transform product-oriented mass customization into customer-oriented personalization to provide customer with personalized product.Although the competitive advantage of personalization has been recognized by industry and academy,the advanced manufacturing technology and the internet technology have provided support for personalization,the effective techniques and methods for personalized product design are still absent.Therefore,focusing on the key issues of personalized product design,this dissertation is intended to put efforts on the following research points.(1)A framework of personalized product design driven by customer value.Based on the concept definitions and basic characteristics analysis of personalized product design,a framework of personalized product design driven by customer value is proposed.At the same time,the design process is built to support the implementation of the framework.(2)Identification and analysis of customer value requirement for personalized product.The customer value hierarchy model is proposed to identify the customer value requirement from three layers and four dimensions.Considering the fuzziness and differentiation of customer value requirement,the 2-tuple linguistic fuzzy Kano's model is developed to classify the customer value requirement.Then,fuzzy logarithmic least squares method and maximizing deviation method are employed to make quantitative analysis of the 2-tuple linguistic fuzzy Kano's model to prioritize customer value requirement.(3)Prediction and transformation of customer value requirement for personalized product.The GM(1,1)model optimized by the improved fruit fly algorithm is proposed to predict the importance and frequency of customer value requirement.Based on the predicted importance and frequency,the IF model is developed to analysis the future category of customer value requirement.The IF model is integrated with QFD to transmit the dynamic change of customer value requirement to technical characteristic.Based on it,the optimization model determining the target value of engineering characteristic,category and target value of future customer value requirement is developed,which aims to achieve the best balance between enterprise satisfaction and customer satisfaction.To solve the proposed model,a multi-population adaptive genetic algorithm is designed.(4)Modularization of personalized product.The similarity of interval-valued intuitionistic fuzzy set is employed to integrate the fuzzy and various correlation information of product component.The module partition schemes are generated based on the interval-valued intuitionistic fuzzy clustering method.To obtain the optimal module partition scheme,the interval-valued intuitionistic fuzzy TOPSIS with integrated weights is designed based on unsupervised evaluation criteria.Then minimizing interval-valued intuitionistic fuzzy cross entropy is proposed to calculate the personalization degree of module.(5)Configuration optimization of personalized product.The situational characteristic is introduced into personalized configuration network,which is developed with GA-BPNN algorithm.Based on the personalized configuration network,a fuzzy multi-objective optimization model is proposed to obtain the optimal configuration solution.To solve the optimization model,the chance-constrained method and improved non-dominated sorting genetic algorithm-II based on fuzzy simulation are developed.The feasibility and effectiveness of the proposed methods and techniques are verified by real-world practices.This dissertation is motivated by the industry demands,and lays a basis to conduct personalized product design.