Customer Value-Driven Product Planning Approach

Product planning is the first and most important step in the product development process and has a significant impact on the future product development and market performance.However,product planning is a complex and difficult system engineering,which is difficult to integrate complex factors into consideration,difficult to organize complex processes effectively,and difficult to make complex decisions and trade-offs.Therefore,it is difficult for enterprises to make product planning scientific and reasonable.As China's economy enters the stage of "new normal",China's manufacturing industry aims to realize the transformation and upgrading from "opening up" to "expanding domestic demand" and from "made in China" to "created in China".However,Chinese manufacturing enterprises always use the idea of product development based on reverse design and lack the ability of forward design.Especially at the beginning of product development,it is difficult to make product planning based on customer needs.Lacking of scientific and effective theoretical guidance and method support has become an obstacle to the transformation and upgrading of China's manufacturing industry.Therefore,this paper systematically studies the method of product planning driven by customer value,in which customer value is taken as the core,the factors of product life cycle are comprehensively considered,and the composition,acquisition,transformation and optimization of product planning and other technologies of customer value are studied,so as to provide theoretical guidance for the practice of enterprise product planning.Mainly studies of this paper are carried out from the following aspects:(1)Considering the difficulties in organizational process and decision-making caused by multiple and complex factors in product planning practice,this paper proposes a systematic approach of product planning driven by customer value.The customer value factors(vertical axis),product life cycle factors(horizontal axis),relevant tools and business activities(points)that need to be considered in the product planning stage are clearly expressed in the form of "coordinate diagram",and the product planning process is organized effectively based on forward mapping and reverse feedback.On this basis,the product planning optimization decision is realized,in which the customer value quantization model is regarded as the core and the multi-factors and bidirectional process are integrated.(2)A hierarchical approach to acquire customer value element is presented by using online comment mining in order to improve the accuracy of comment mining and acquire customer value element intelligently and accurately.A semi-supervisory method based on hierarchical theme model is proposed to mine online comments and obtain the product attribute hierarchy tree.Emotional polarity words were extracted and quantified based on dependency syntactic analysis,and the missing emotional polarity values were supplemented based on the weighted hierarchical relationship between product attributes.Based on the statistically emotional polarity value,the customer value element is determined.The effectiveness of the method is illustrated by the case of mining the word-of-mouth data of house of automobile.(3)For the inaccuracy and even the occurrence of singular value in the calculation of the importance of engineering characteristics due to lack of asymmetry and negative correlation of the autocorrelation between engineering characteristics in the traditional Quality Function Deployment(QFD),a normalization method is proposed based on the correlation matrix of improved QFD.The triangular "roof" used in the traditional QFD matrix to express the symmetric relation is extended to a number of rectangular "roofs"that can express the asymmetric relation.Then,several rectangular "roofs" are aggregated to obtain the normalized correlation matrix based on a vector expression method that can avoid the occurrence of singular values.The effectiveness of the proposed method is illustrated by comparing with the existing normalization methods.(4)Aiming to solve the product planning problem where the basic functional principles remain unchanged,an optimized decision-making method oriented to product planning is proposed.The product planning and optimization model based on QFD is built in which the optimization objective is to maximize the customer perceived value,and the current capability,cost and resources of the enterprise are taken as the constraint condition.For the hybrid integer nonlinear programming optimization model,an improved algorithm by combining genetic algorithm and imperialist competition algorithm is proposed to solve the optimization model.Numerical examples and washing machine product planning examples are solved and the results illustrate that the improved algorithm shows obvious time advantage in solving large-scale problems.(5)Aiming to solve the product planning problem where the basic functional principles are changed,a master-slave optimization decision-making method oriented to product planning and conceptual design is proposed.The master-slave hierarchical decision-making process between product planning and conceptual design is analyzed and the master-slave optimization model is constructed.The product planning process of the main decision maker is based on QFD,and the goal is to maximize the customer perceived value.As the subordinate maker,the conceptual design process is implemented based on morphological matrix and conceptual Failure Mode and Effect Analysis(FMEA),in which the optimization objective is to maximize the reduced Risk Priority Number(RPN)value in the product concept.The nested genetic algorithm is used to solve the model.(6)In view of the problems existing in the practice of product planning of washing machine enterprises,the product planning process of machine integrated washing and drying is taken as an example to illustrate the applicability of the systematic method of customer-driven product planning proposed in this paper.