Sharma, J., Rawani, A. (2008). Quality function deployment: Integrating comprehensive matrix and SWOT analysis for effective decision making. Journal of Industrial Engineering, International, 4(6), 19-31.
J.R Sharma; A,M Rawani. "Quality function deployment: Integrating comprehensive matrix and SWOT analysis for effective decision making". Journal of Industrial Engineering, International, 4, 6, 2008, 19-31.
Sharma, J., Rawani, A. (2008). 'Quality function deployment: Integrating comprehensive matrix and SWOT analysis for effective decision making', Journal of Industrial Engineering, International, 4(6), pp. 19-31.
Sharma, J., Rawani, A. Quality function deployment: Integrating comprehensive matrix and SWOT analysis for effective decision making. Journal of Industrial Engineering, International, 2008; 4(6): 19-31.
Quality function deployment: Integrating comprehensive matrix and SWOT analysis for effective decision making
1Assistant Professor, Institute of Management Technology (IMT), Nagpur, India
2Professor, Head of Mechanical Engineering Department, National Institute of Technology, Raipur, India
Abstract
In this ever-changing business scenario, the manufacturing product industries have to be in position to rec-ognize the ever changing pulse and demands of the market. Customer satisfaction and quality management has become a strategic issue for companies in the new millennium. Quality Function Deployment (QFD) lit-erature suggests that building up the House of Quality (HoQ) is not a difficult task, however to analyze and in-terpret the information available is replete with a lot of uncertainty and presents less than optimal solutions. This paper attempts to address these twin issues of the Post-HoQ analysis and its interpretation through SWOT. The development and mechanics of QFD model is presumed to be known to the followers and the paper deals specifically with post-HoQ model through a well-defined and structured approach to comprehen-sive matrix analysis. The paper contributes a method for evaluating and analyzing the customer data and tech-nical data in QFD as a function of the generation of useful information resulting in a better decision making process. The outcome of the study is a comprehensive solution which discusses post-matrix analysis through underlying concepts; requisite steps; information needed; and the computations involved. The applicability of the proposed model is demonstrated with an illustrative hypothetical example of a medical-care product - dis-posable syringe and needle.
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