Transformation Of Customer Demand To Engineering Characteristics In Green Design Based On Data Mining

With the continuous development of global market economy,customer demand tends to be personalized and diversified,the key problem of the enterprise is to meet the customer’s needs and improve the quality of the product to the maximum extent,but in the process of product design,the transformation of customer demand has great subjectivity and fuzziness,and with the increasing diversification of customer demand,the demand of traditional transformation process is too complex and of low conversion efficiency,which directly leads to the low efficiency of product design.With the development of big data technology,data mining technology has been widely used,this paper uses data mining technology to excavate hidden design information from successful historical design cases,and uses the information to guide the design of new products to the greatest extent possible to meet the needs of customers,which can maximally meet customer needs,reduce subjectivity in the process of transformation of customer needs and improve the design efficiency of the product.The main contents of this paper are as follows:With the constant change of customer demand,current customer requirements acquisition methods are not sufficient to support access to Internet customers,this paper analyzes the characteristics of customer demand,and makes a comparative analysis of the existing ways of customer demand acquisition.On this basis,it proposes an internet based feedback customer demand acquisition mode.After,based on axiomatic design and environmental quality function deployment,fuzzy AHP is applied to analyze the importance degree of customer demand data and determine the importance of customer demand,the method of quality function deployment is used to transform customer requirements into engineering property weights,the customer requirements data and the transformed weight of the engineering properties constitute the historical design case data set,and then,according to the need of data mining,the training sample set of the customer needs to the transformation relationship of the engineering characteristics is extracted.Monitoring the learning data training samples by using a multilayer perceptron,the date mining based transformation method of customer demand data to engineering characteristics is established,and mapping analysis between customer demand and engineering characteristics based on historical design data is carried out,and mapping relationship between historical design data is determined.The multilayer perceptron is used to establish a model for the transformation of the customer’s needs to engineering properties to achieve the transform customer demand into engineering property weights fast,efficient and relatively objective transformation.