Dealing with subjectivity in early product design phase: A systematic approach to exploit Quality Function Deployment potentials

  • Authors:

  • Hendry Raharjo;Aarnout C. Brombacher;Min Xie

  • Affiliations:

  • Department of Industrial and Systems Engineering, National University of Singapore, 10 Kent Ridge Crescent, Singapore 119260, Singapore and Centre for Design Technology, National University of Sin ...;Centre for Design Technology, National University of Singapore, Singapore 119260, Singapore and Technische Universiteit Eindhoven, Eindhoven, The Netherlands;Department of Industrial and Systems Engineering, National University of Singapore, 10 Kent Ridge Crescent, Singapore 119260, Singapore

  • Venue:
  • Computers and Industrial Engineering
  • Year:
  • 2008

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Abstract

Quality Function Deployment (QFD), as a customer-driven tool, is generally used in the early phase of new or improved products/services design process, and therefore most of the input parameters are highly subjective in nature. The five major input components of the QFD, which are laid in the House of Quality (HOQ), namely, the customer requirement, the technical attribute, the relationship matrix, the correlation matrix, and the benchmarking information, play a central role in determining the success of QFD team. Accurate numerical judgment representations are of high importance for the QFD team to fill in the values of each of those components. In this paper, a generic network model, based on Analytic Network Process (ANP) framework, will be proposed to systematically take into account the interrelationship between and within those components simultaneously and finally derive their relative contribution. In particular, with respect to a rapidly changing market, the incorporation of the new product development risk, the competitors' benchmarking information, and the feedback information into the network model may be considered as a novel contribution in QFD literature. Not only does this network model improve the QFD results' accuracy, but it also serves as a generalized model of the use of ANP in QFD with respect to the previous research. A simple illustrative example of the proposed network model will be provided to give some practical insights.