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Intelligent Decision Making in Quality Management pp 327–362Cite as

Intelligent Quality Function Deployment

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Part of the book series: Intelligent Systems Reference Library ((ISRL,volume 97))

Abstract

Quality function deployment (QFD) is commonly used in the product planning stage to define the engineering characteristics and target value settings of new products. However, some QFD processes substantially involve human subjective judgment, thus adversely affecting the usefulness of QFD. In recent years, a few studies have been conducted to introduce various intelligent techniques into QFD to address the problems associated with subjective judgment. These studies contribute to the development of intelligent QFD. This chapter presents our recent research on introducing intelligent techniques into QFD with regard to four aspects, namely, determination of importance weights of customer requirements , modeling of functional relationship s in QFD, determination of importance weights of engineering characteristics and target value setting of engineering characteristics. In our research, a fuzzy analytic hierarchy process with an extent analysis approach is proposed to determine the importance weights for customer requirements to capture the vagueness of human judgment and a chaos-based fuzzy regression approach is proposed to model the relationships between customer satisfaction and engineering characteristics by which fuzziness and nonlinearity of the modeling can be addressed. To determine importance weights of engineering characteristics, we propose a novel fuzzy group decision-making method to address two types of uncertainties which integrates a fuzzy weighted average method with a consensus ordinal ranking technique. Regarding the target value setting of engineering characteristics, an inexact genetic algorithm is proposed to generate a family of inexact optimal solutions instead of determining one set of exact optimal target values. Possible future research on the development of intelligent QFD is provided in the conclusion section.

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Acknowledgments

The work described in this chapter was fully supported by a grant from the Research Grants Council of the Hong Kong Special Administrative Region, China (Project No. PolyU 517113).

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Authors and Affiliations

  1. Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Hong Kong, China

    Huimin Jiang & C. K. Kwong

  2. Department of Systems Engineering, State Key Laboratory of Synthetical Automation for Process Industries, Northeastern University, Shenyang, China

    X. G. Luo

Authors
  1. Huimin Jiang
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  2. C. K. Kwong
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  3. X. G. Luo
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Corresponding author

Correspondence to C. K. Kwong .

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Editors and Affiliations

  1. İşletme Fakültesi, Istanbul Technical University, Istanbul, Turkey

    Cengiz Kahraman

  2. Industrial Engg Dept, Istanbul Technical University, Istanbul, Turkey

    Seda Yanik

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Jiang, H., Kwong, C.K., Luo, X.G. (2016). Intelligent Quality Function Deployment. In: Kahraman, C., Yanik, S. (eds) Intelligent Decision Making in Quality Management. Intelligent Systems Reference Library, vol 97. Springer, Cham. https://doi.org/10.1007/978-3-319-24499-0_11

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  • DOI: https://doi.org/10.1007/978-3-319-24499-0_11

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-24497-6

  • Online ISBN: 978-3-319-24499-0

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