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A fuzzy QFD approach to determine supply chain management strategies in the dairy industry

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Abstract

The aim of this study is to identify the crucial logistics requirements and supply chain management (SCM) strategies for the dairy industry. For product or service development, quality function deployment (QFD) is a useful approach to maximize customer satisfaction. The determination of design requirements and supply chain management strategies are important issues during QFD processes for product or service design. For this reason, a fuzzy QFD methodology is proposed in this study to determine these aspects and to improve customer satisfaction. Qualitative information is converted firstly into quantitative parameters, and then this data is combined with other quantitative data to parameterize two multi-objective mathematical programming models. In the first model, the most important logistic requirements for the company are determined based on total technical importance, total cost, total feasibility and total value increment objectives, and in the second model, based on these objectives, appropriate supply chain management strategies are determined. Finally, a case study from the Turkish dairy industry is given to illustrate the proposed approach.

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References

  • Akao Y. (1990) Quality function deployment: Integrating customer requirements into product design. Productivity Press, Cambridge, MA

    Google Scholar 

  • Ayag Z. (2005) A fuzzy AHP-based simulation approach to concept evaluation in a NPD environment. IIE Transactions 37: 827–842

    Article  Google Scholar 

  • Ayag Z., Ozdemir R. G. (2011) An intelligent approach to machine tool selection through fuzzy analytic network process. Journal of Intelligent Manufacturing 22: 163–177

    Article  Google Scholar 

  • Bech, A. C., Engelund, E., Juhl, H. J., Kristensen, K., & Poulsen, C. S. (1994). QFood: Optimal design of food products, MAPP working paper no. 19 Copenhagen: MAPP.

  • Bech, A. C., Kristensen, K., Juhl, H. J., & Poulsen, C. S. (1997). Development of farmed smoked eel in accordance with consumer demands. In J. B. Luten, T. Børresen, & J. Oehlenschläger (Eds.), Seafood from producer to consumer-integrated approach to quality (pp. 3–19). Amsterdam: Elsevier Science B.V.

  • Costa, A. I. A. (1996). Development of methodologies for quality modelling: An application on tomato ketchup, MSc Thesis, Wageningen: Wageningen University, Department of Agrotechnology and Food Sciences Inte-grated Food Technology.

  • Fung R. Y. K., Popplewell K., Xie J. (1998) An intelligent hybrid system for customer requirements analysis and product attribute targets determination. International Journal of Production Research 36: 13–34

    Article  Google Scholar 

  • Fung R. Y. K., Tang J., Tu Y. L., Wang D. (2002) Product design resource optimization using a non-linear fuzzy quality function deployment model. International Journal of Production Research 40: 585–599

    Article  Google Scholar 

  • Holmen, E., & Kristensen, P. S. (1996). Downstream and upstream extension of the house of quality, MAPP working paper no. 37 Copenhagen: MAPP.

  • Kaufmann A., Gupta M. M. (1985) Introduction to fuzzy arithmetic: Theory and applications. Van Nostrand Reinhold, New York

    Google Scholar 

  • Kim K. J., Moskowitz H., Dhingra A., Evans G. (2000) Fuzzy multicriteria models for quality function deployment. European Journal of Operation Research 121: 504–518

    Article  Google Scholar 

  • King B. (1987) Better designs in half the time: Implementing QFD in America. Goal/QPC, Methuen, MA

    Google Scholar 

  • Korsten, M. (2000). Technology-initiated, consumer-oriented product development, MSc Thesis, Wageningen: Wageningen University, Department of Agro-technology and Food Sciences-Integrated Food Technology.

  • Lee, A. R. (1999). Application of modified fuzzy AHP method to analyze bolting sequence of structural joints, UMI Dissertation Services, A Bell & Howell Company.

  • Miettinen, K. (1999). Nonlinear multiobjective optimization, Kluwer’s International Series.

  • Moskowitz H., Kim K. J. (1997) QFD optimizer: A novice friendly quality function deployment decision support system for optimizing product designs. Computers and Industrial Engineering 32: 641–655

    Article  Google Scholar 

  • Negoita C. V. (1985) Expert systems and fuzzy systems. The Benjamin/Cummings, Menlo Park, California

    Google Scholar 

  • Park T., Kim K. J. (1998) Determination of an optimal set of design requirements using house of quality. Journal of Operations Management 16: 569–581

    Article  Google Scholar 

  • Saaty T. L. (1981) The analytic hierarchy process. McGraw-Hill, New York

    Google Scholar 

  • Saaty T. L. (1989) Decision making, scaling, and number crunching. Decision Science 20: 404–409

    Article  Google Scholar 

  • Shen X. X., Tan K. C., Xie M. (2001) The implementation of quality function deployment based on linguistic data. Journal of Intelligent Manufacturing 12: 65–75

    Article  Google Scholar 

  • Trappey C. V., Trappey A. J., Hwang S.-J. (1996) A computerized quality function deployment approach for retail services. Computers & Industrial Engineering 30(4): 611–622

    Article  Google Scholar 

  • Vanegas L. V., Labib A. W. (2001) Application of new fuzzy-weighted average (NFWA) method to engineering design evaluation. International Journal of Production Research 39: 1147–1162

    Article  Google Scholar 

  • Viaene J., Januszewska R. (1999) Quality function deployment in the chocolate industry. Food Quality and Preference 10: 377–385

    Article  Google Scholar 

  • Wang J. (1999) Fuzzy outranking approach to prioritize design requirements in quality function deployment. International Journal of Production Research 37: 899–916

    Article  Google Scholar 

  • Wasserman G. S. (1993) On how to prioritize design requirements during the QFD planning process. IIE Transactions 25: 59–65

    Article  Google Scholar 

  • Zhou M. (1997) Fuzzy logic based models for quality planning and improvement. ASME Conference: Intelligent Engineering Systems through Artificial Neural Networks 7: 311–316

    Google Scholar 

  • Zimmermann H. J. (1996) Fuzzy set theory and its applications. Kluwer, Massachusetts

    Book  Google Scholar 

Download references

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Correspondence to Zeki Ayağ.

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Ayağ, Z., Samanlioglu, F. & Büyüközkan, G. A fuzzy QFD approach to determine supply chain management strategies in the dairy industry. J Intell Manuf 24, 1111–1122 (2013). https://doi.org/10.1007/s10845-012-0639-4

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  • DOI: https://doi.org/10.1007/s10845-012-0639-4

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