Quality & Quantity

, Volume 43, Issue 6, pp 999–1009 | Cite as

Using OWA aggregation technique in QFD: a case study in education in a textile engineering department

  • Ayşe Okur
  • Efendi N. Nasibov
  • Musa Kiliç
  • Murat Yavuz
Research Note


Quality Function Deployment (QFD) is a systematic approach that considers customer needs through design, production, marketing, and support stages. Customer needs are the main input for QFD, so voice of customer must be understood well and changes, innovations, and treatments must be held in this view. In QFD applications, determining the priorities of customer needs is a fairly important stage. This is mostly held by Analytic Hierarchy Process (AHP) a multicriteria decision making technique. Nonetheless, Ordered Weighted Averaging (OWA) is an aggregation technique mostly used in decision making for multicriteria decision problems. So, combining these two techniques will give a different viewpoint for prioritizing the customer needs in QFD applications. The aim of this study is to show the use of Ordered Weighted Averaging (OWA) aggregation technique in QFD applications. For this purpose a case study in Dokuz Eylül University Textile Engineering Department was held. It was aimed to support the efforts on increasing the education quality by determining the students’ needs and opinions using QFD with OWA.


Quality function deployment (QFD) Ordered weighted averaging (OWA) Education Textile engineering 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. Akao, Y.: Quality Function Deployment QFD, Integrating Customer Requirements into Product Design. Productivity Press, Cambridge (1990)Google Scholar
  2. American Supplier Institute: http://www.amsup.com/qfd/index.htm. (2006)
  3. Anderson, D.R., Sweeney, D.J., Williams, T.A.: An Introduction to Management Science: Quantitative Approaches to Decision Making, 11th edn. South-Western College Pub., Cincinnati (2005)Google Scholar
  4. Bier, I.D., Cornesky, R.: Using QFD to construct a higher education curriculum. Quality progress. 34(4), 64–68 (2001)Google Scholar
  5. Bolt, A., Mazur, G.H.: Jurassic QFD integrating service and product quality function deployment. In: The Eleventh Symposium on Quality Function Deployment. Novi, Michigan (1999)Google Scholar
  6. Calvo, T., Mesiar, R.: Generalized medians. Fuzzy Sets Syst. 124, 59–64 (2001)CrossRefGoogle Scholar
  7. Das, S., Islam, R., Chattopadhyay, A.B.: A simple approach for on-line tool wear monitoring using the analytic hierarchy process. Proceedings of the I MECH E Part B Journal of Engineering Manufacture 211(1), 19–27 (1997)CrossRefGoogle Scholar
  8. Göksen, Y., Abasov, V.: Quality function deployment and application in a textile firm. In: 1st National Quality Function Deployment Symposium. Izmir, Turkey (2002)Google Scholar
  9. Hermann, C., Yim, H.: Eco-voice of customer (VOC) on QFD. In: Proceedings of EcoDesign 2003 Third International Symposium on Environmentally Conscious Design and Inverse Manufacturing. Tokyo, Japan, pp. 618–625 (2003)Google Scholar
  10. Jaraiedi, M., Ritz, D.: Total quality management applied to engineering education. Quality Assur. Edu. 2(1), 32–40 (1994)CrossRefGoogle Scholar
  11. Nasibov, E.N., Nasibova, R.A.: OWA and MIN aggregation methods in fuzzy bin-packing problem, transac. of the national academy of sciences of azerbaijan. Phus. Tech. Math. (2), 45–50 (2003)Google Scholar
  12. Nasibov, E.N., Nasibova, R.A.: Information aggregation for resolving the fuzzy bin packing problem. Automat. Control Comp. Sci. 39(3), 29–36 (2005)Google Scholar
  13. Pitman, G., Motwani, J., Kumar, A., Cheng, C.H.: QFD Application in an educational setting: a pilot field study. Int. J. Quality Reliabil. Manage. 12(6), 63–72 (1995)CrossRefGoogle Scholar
  14. Pitman, G., Motwani, J., Kumar, A., Cheng, C.H.: QFD Application in an educational setting: a pilot field study. Int. J. Quality Reliabil. Manage. 13(4), 99–108 (1996)CrossRefGoogle Scholar
  15. Saaty, T.L.: The Analytic Hierarchy Process. Mc-Graw Hill, New York (1980)Google Scholar
  16. Shaffer, M.K., Pfeiffer, I.L.: A blueprint for training. Training Develop. 49(3), 31–33 (1995)Google Scholar
  17. Tetsuichi, A., Kazuo, O.: Handbook of Quality Tools—The Japanese Approach. Productivity Press, Cambridge (1990)Google Scholar
  18. Yager, R.R.: On ordered weighted averaging aggregation operators in multicriteria decisionmaking. IEEE Trans. Syst., Man Cybernet. 18(1), 183–190 (1988)CrossRefGoogle Scholar
  19. Yager, R.R.: Families of OWA Operators. Fuzzy Sets Syst. 59(2), 125–148 (1993)CrossRefGoogle Scholar
  20. Yager, R.R.: Interpreting linguistically quantified propositions. Int. J. Intell. Syst. 9(6), 541–569 (1994)CrossRefGoogle Scholar
  21. Yager, R.R.: Multicriteria decision making using fuzzy quantifiers. In: IEEE/IAFE Conference on Computational Intelligence for Financial Engineering, Proceedings (CIFEr), 42–46 (1995)Google Scholar
  22. Yenginol, F.: A method which converts customers needs and requirements into technical characteristics: quality function deployment. PhD. Thesis, Dokuz Eylül University Institute of Social Sciences, Izmir, Turkey (2000)Google Scholar

Copyright information

© Springer Science+Business Media B.V. 2008

Authors and Affiliations

  • Ayşe Okur
    • 1
  • Efendi N. Nasibov
    • 2
  • Musa Kiliç
    • 1
  • Murat Yavuz
    • 1
  1. 1.Faculty of Engineering, Department of Textile EngineeringDokuz Eylül UniversityBornovaTurkey
  2. 2.Faculty of Science, Department of StatisticsDokuz Eylül UniversityBucaTurkey

Personalised recommendations