The Research On Quality Function Deployment Model Based On Grey Prediction And Fuzzy Programming

As scientific technology develops fast and the trend of economic globalization moves forwardquickly, the competition of product market becomes more and more fierce, and customer requirementfor products changes every now and then. Under this kind of situation, if enterprise wants to survivebetter in product market, it is necessary to improve its products continuously in order to satisfy thecustomer requirement that changes from time to time. As a produc t planning tool, Quality functiondeployment(QFD) is able to convert the customer requirement into product engineeringcharacteristics(technical requirement) so that it can guide the enterprise how to improve its productengineering characteristics reasonably and effectively.First of all, in the left wall of product planning House of Quality(HoQ) of QFD, that the actualcustomer requirement changes dynamically was considered, thus a HoQ model considering dynamiccustomer requirement was constructed, and also a kind of improved multi-variable MGM(1,m) modelwas established to predict the future importance degree of customer requirement during the process ofcalculating the importance degree of customer requirement. In order to enhance the simulationprecision and prediction precision of traditional multi-variable MGM(1,m) model, the initial valueand background value of traditional multi-variable MGM(1,m) model were both improved. Thereafter,the enhanced MGM(1,m) model was applied to dynamic HoQ model so as to predict the futureimportance degree of customer requirement.Second of all, with respect to the fact that in HoQ model the correlation information betweencustomer requirement and product engineering characteristics has the feature of "small data" and"poor information", the grey relational analysis was introduced into HoQ model to quantitativelymeasure the correlation relationship between customer requirement and product engineeringcharacteristics, and the final importance degree of product engineering characteristics was determinedby combining given importance degree of customer requirement.Furthermore, a fuzzy hybrid integer programming model was constructed. It takes theimprovement level of engineering characteristics as goal function, takes cos t budget, improvementdifficulties of engineering characteristics and competition requirement of product as restraintconditions. Meanwhile, the fuzziness of actual restraint conditions was taken into consideration.Besides, the lingo software was utilized to figure out the optimal solution, thus the optimalimprovement scheme for product engineering characteristics was gained. Finally, the proposed QFD framework was applied to the product improvement in an enterprisewhich undertakes the design and production of intelligent cellphone in order to verify theeffectiveness and practicability of proposed model. Based on its calculation result the suggestions onimproving the intelligent cellphone of the company was given by combining the qualitativelyanalysis.