An Application of Fuzzy Data Envelopment Analytical Hierarchy Process for Reducing Defects in the Production of Liquid Medicine

  • Ketsarapong, Suphattra ;
  • Punyangarm, Varathorn
  • Received : 2010.03.31
  • Accepted : 2010.07.24
  • Published : 2010.09.01


This article demonstrated the application of the Fuzzy Data Envelopment Analytical Hierarchy Process (FDEAHP) to evaluate the root causes of critical defect problems occurring in the production of liquid medicine. The methodology of the research began by collecting the defect data by using Check Sheets, and ranking the significant problems by using a Pareto Diagram. Two types of major problems were found to occur, including glass fragments in the medicine and damaged lid threads. The causes of each problem were then analyzed by using Cause and Effect Diagrams. The significant causes were ranked by FDEAHP under three criteria, Severity (S), Occurrence (O) and Detection (D), followed by the framework of the FMEA Technique. Two causes with the highest Final Weight (FW) of each problem were selected to be improved, such as installing auxiliary equipment, using the Poka-Yoke system, setting the scale of the shaft and lathing the bushes of each bottle size. The results demonstrated a reduction in defects from 3.209% to 1.669% and showed that improving a few significant root causes, identified by an experienced decision maker, was sufficient to reduce the defect rate.


Analytical Hierarchy Process;Data Envelopment Analysis;Fuzzy Set;Possibility Approach;Quality Improvement;Liquid Medicine Process


  1. Bunney, H. S. and Dale, B. G. (1997), The implementation of quality management tools and techniques: A study, The TQM Magazine, 9(3), 183-189.
  2. Charnes, A., Cooper, W. W., and Rhodes, E. (1978), Measuring the efficiency of decision making units, European Journal of Operational Research, 2, 429-444.
  3. Crosby, P. B. (1979), Quality is Free, the Art of Making Quality Certain, Hodder and Stoughton, New York.
  4. Dale, B. G. and McQuater, R. (1998), Managing Business Improvement and Quality: Implementing Key Tools and Techniques, Blackwell Business, Oxford.
  5. Deming, W. E. (1982), Quality, Productivity and Competitive Position, MIT Center for Advanced Engineering, Cambridge, MA.
  6. Dubois, D. and Prade, H. (1980), Fuzzy sets and systems: Theory and applications, New York: Academic Press.
  7. Evans, J. R. and Lindsay, W. M. (1999), The Management and Control of Quality, South-Western College Publishing, Cincinnati, OH.
  8. Feigenbaum, A. V. (1991), Total Quality Control, Mc-Graw-Hill, New York.
  9. He, Z., Staples, G., Ross, M., and Court, I. (1996), Fourteen Japanese quality tools in software process improvement, The TQM Magazine, 8(4), 40-44.
  10. Ishikawa, K. (1985), What is Total Quality Control?, The Japanese Way, Prentice-Hall, London.
  11. Juran, J. M. (1988), On Planning for Quality, Collier Macmillan, London.
  12. Klir, G. J., Clair, U. S., and Yuan, B. (1997), Fuzzy Set Theory: Foundations and Application, Prentice-Hall PRT, USA.
  13. Lertworasirikul, S., Fang, S. C., Joines, J. A., and Nuttle, H. L. W. (2003), Fuzzy data envelopment analysis (DEA): A possibility approach, Fuzzy Sets and Systems, 139, 379-394.
  14. McQuater, R. E., Scurr, C. H., Dale, B. G., and Hillman, P. G. (1995), Using quality tools and techniques successfully, The TQM Magazine, 7(6), 37-42.
  15. Pavletic, D., Sokovic, M., and Paliska, G. (2008), Practical Application of Quality Tools, International Journal for Quality Research, 2(3), 199-205.
  16. Ramanathan, R. (2006), Data envelopment analysis for weight derivation and aggregation in the analytic hierarchy process, Computers and Operations Research, 33, 1289-1307.
  17. Saaty, T. (1980), The Analytic Hierarchy Process, Mc-Graw-Hill, New York.
  18. Seiford, L. (1996), Data envelopment analysis: The evolution of the state of the art, Journal of Productivity Analysis, 7, 99-137.
  19. Stephens, B. (1997), Implementation of ISO 9000 or Ford's Q1 award: Effects on organizational knowledge and application of TQM principles and quality tools, The TQM Magazine, 9(3), 190-200.
  20. Tari, J. J. and Sabater, V. (2004), Quality tools and techniques: Are they necessary for quality management?, International Journals of Production Economics, 92, 267-280.
  21. Vaidya O. S. and Kumar, S. (2006), Analytic hierarchy process: an overview of applications, European Journal of Operational Research, 169, 1-29.
  22. Wilkinson, A., Redman, T., Snape, E., and Marchington, M. (1998), Managing With Total Quality Management: Theory and Practice, MacMillan, London.
  23. Zadeh, L. A. (1978), Fuzzy sets as a basis for a theory of possibility, Fuzzy Sets and Systems, 1, 3-28.
  24. Zimmermann, H. J. (1996), Fuzzy Set Theory and Its Application, Kluwer Academic Publishers, London.