Electric Vehicle Product Planning Based On Improved QFD Methods

Due to the increasingly polluted environment and serious energy shortage,electric vehicles(EVs)are one of the possible future development directions of the automobile industry.To date,the global electric vehicle industry is in a rapid development,and efficient product planning process of EVs is a significant factor in product development of electric vehicles.During the phase of product design of EVs,some advanced technologies to improve the quality must be taken into account,and effective planning tools should be taken to achieve and exceed customer needs and expectations so that electric vehicle manufacturing enterprises could obtain competitive advantages in the global marketplace.Quality function deployment(QFD),as a planning and problem-solving tool,is available to achieve customer satisfaction,improve the quality of products obviously,and shorten product development cycle efficiently.It can recognize customer requirements(CRs)and translate them into engineering characteristics(ECs)through “house of quality(HOQ)” so that product experts are capable to list the ECs in order of priority and select which ones should be enhanced in planning new or improved products.To deal with the shortcomings and produce a noticeable performance of the conventional QFD in improving quality of EVs,this research develops two QFD models for electric vehicle product planning based on improved QFD methods.Specifically,this research:·presents an integrated analytical model to obtain the importance ratings of ECs in QFD by integrating Decision Making Trial and Evaluation Laboratory(DEMATEL)and VIse Kriterijumska Optimizacija I Kompromisno Resenje(VIKOR)under hesitant fuzzy context.The feasibility and practicality of the presented approach are verified by an example of sustainable product development of EVs while considering environmental consciousness and the entire life cycle.·develops a new model using cloud model theory and a modified Multi-Objective Optimization by Ratio Analysis plus the Full Multiplicative Form(MULTIMOORA)for solving QFD problems with incomplete weight information.Also,an illustrative example on the development of electric vehicles’photovoltaic technology is aimed at demonstrating and validating the presented improved QFD model.