A new approach to quality function deployment planning with financial consideration
Computers and Operations Research
Computers and Industrial Engineering
International Journal of Intelligent Systems
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology
A methodology of determining aggregated importance of engineering characteristics in QFD
Computers and Industrial Engineering
Ranking of customer requirements in a competitive environment
Computers and Industrial Engineering
Computers and Industrial Engineering
Expert Systems with Applications: An International Journal
Robustness indices and robust prioritization in QFD
Expert Systems with Applications: An International Journal
Integration of environmental considerations in quality function deployment by using fuzzy logic
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
An evidential reasoning based approach for quality function deployment under uncertainty
Expert Systems with Applications: An International Journal
Advanced Engineering Informatics
A quantitative methodology for acquiring engineering characteristics in PPHOQ
Expert Systems with Applications: An International Journal
The Hybrid Fuzzy Least-Squares Regression Approach to Modeling Manufacturing Processes
IEEE Transactions on Fuzzy Systems
Hi-index | 12.05 |
Quality function deployment (QFD) has been widely used to translate customer requirements (CRs) into engineering characteristics (ECs) in product planning and improvement. Product planning house of quality (PPHOQ) is of fundamental and strategic importance in the QFD system. Correctly determining the final priority ratings of CRs is essential in the process of constructing PPHOQ, because it will largely affect the target value of ECs for product improvement. This paper present a systematic and operational method based on the integration of a minimal deviation based method (MDBM), balanced scorecard (BSC), analytic hierarchy process (AHP) and scale method to determine the final priority ratings of CRs. To exploit the competition and preference information of product improvement, the MDBM is developed to determine the CPRs of CRs. A concept of the total output of achieving the ITPE of a CR is introduced and analyzed by using the integration of BSC, AHP and scale method in a qualitative and quantitative way, and then the priority rating of achieving the ITPE of this CR is determined. Finally, a case study is provided to illustrate the effectiveness of the proposed method.