Multi criteria quality assessment of products by integrated DEA-PCA approach

International Journal of Reliability, Quality and Safety Engineering

Volumn 14, Issue 3, 2007, Pages 201-218

  Azadeh, A ^a   Ghaderi, S F ^a   Ahmadabad, M Fazli ^a  

^a UNIVERSITY OF TEHRAN   (Iran)

Author keywords

Assessment; DEA; Multi criteria; Numerical taxonomy; PCA; Product quality

Indexed keywords

MULTIVARIABLE CONTROL SYSTEMS; NUMERICAL METHODS; PRINCIPAL COMPONENT ANALYSIS; PRODUCT DEVELOPMENT; RANDOM PROCESSES; TAXONOMIES;

DATA ENVELOPMENT ANALYSIS (DEA); NUMERICAL TAXONOMY (NT); PRODUCT QUALITY; QUALITY ASSESSMENT;

QUALITY FUNCTION DEPLOYMENT;

EID: 34547479903     PISSN: 02185393     EISSN: None     Source Type: Journal    
DOI: 10.1142/S0218539307002593     Document Type: Conference Paper

References (39)

1. R. Agarwala, On the approximability of numerical taxonomy (fitting distances by tree metrics), SIAM Journal on Computing 28(3) (1999) 1073-1085.
2. M. A. Azadeh, Creating highly reliable manufacturing systems: An integrated approach, International Journal of Reliability, Quality and Safety Engineering 7(3) (2000).
3. M. A. Azadeh and S. Jala l, Identifying the economic importance of industrial sectors by multivariate analysis, Journal of the Faculty of Engineering, University of Tehran, Iran (2001).
4. M. A. Azadeh and V. Ebrahimipour, An integrated approach for assessment of manufacturing sectors based on machine performance: The cases of automotive and food and beverages industries, Proceedings of the 2nd Manufacturing Complexity Conference, University of Cambridge, England (2002).
5. M. A. Azadeh and V. Ebrahimipour, A multivariate approach for assessment and improvement of machinery and equipment manufacturers based on machine performance, The 6th International Conference on Engineering Design and Automation, Maui, Hawaii (2002).
6. M. A. Azadeh and A. Ebrahimipour, An integrated approach for assessment and ranking of manufacturing systems based on machine performance, International Journal of Industrial Engineering 11(4) (2004).
7. K. D. Barber and R. H. Hollier, The use of numerical analysis to classify companies according to production control complexity, International Journal of Production Research 24(1) (1986).
8. R. Bolden, P. Waterson, P. Warr and C. Clegg, A new taxonomy of modern manufacturing practices, International Journal of Operations and Production Management 17(11) (1997).
9. L. H. Chen, C. Kao, S. Kuo, T. Y. Wang and Y. C. Jang, Productivity diagnosis via fuzzy clustering and classification: An application to machinery industry, Omega 24(3) (1996).
10. T. H. Davenport, Process innovation, reengineering wok through information technology, Harvard Business School Press (1993).
11. S. Gamesalingam and K. Kumar, Detection of financial distress via multivariate statistical analysis, Managerial Finance 27(4) (2001).
12. T. Guimaraes, N. Matensson, J. Stahre and M. Igbaria, Empirically testing the impact of manufacturing complexity on performance, International Journal of Operations and Production Management 19(12) (1999).
13. T. J. Harris, C. T. Seppala and L. D. Desborough, A review of performance monitoring and assessment techniques for univariate and multivariate control systems, Journal of Process Control 9 (1999).
14. A. C. Hax and N. S. Majluf, The Strategy Approach and Process: A Pragmatic Approach (New York: Prentice Hall, 1996).
15. D. Hitchens, J. E. Birnie and K. Wagner, A matched plant comparison of productivity in east and west germany: Transition to the market economy, Omega 24(3) (1996).
16. H. K. Hong, S. H. Ha, C. K. Shin, S. C. Park and S. H. Kim, Evaluating the efficiency of integration projects using DEA and machine learning, Expert Systems with Applications 16 (1999).
17. C. R. Hulten, Total factor productivity: A short biography, In C. R. Hulten, E. R. Dean and M. J. Harper (eds.), New Developments in Productivity Analysis, Chicago: University of Chicago Press for the National Bureau of Economic Research (2001).
18. P. Jonsson, An empirical taxonomy of advanced manufacturing technology, International Journal of Operations and Production Management 20(12) (2000).
19. R. S. Kaplan and P. P. Norton, Balanced Score Card: Translating Strategy into Action (Harvard Business S.P., 1996).
20. R. S. Kaplan and D. P. Norton, Putting Balanced Score Card to Work (Harvard Business Review, January-February, 1993).
21. C. Madu, Reliability and quality interface, International Journal of Quality & Reliability Management 16(7) (1999).
22. E. B. Martin, A. J. Morris and C. Kiparissides, Manufacturing performance enhancement through multivariate statistical process control, Annual Reviews in Control 23 (1999).
23. I. McCarthy, Manufacturing classification: Lessons from organizational systematic and biological taxonomy, Integrated Manufacturing Systems 6(6) (1995).
24. N. Meade, Strategic positioning in UK car market, European Journal of Marketing 21(5) (1987).
25. A. Mehrez, H. Hu and F. Offodile, Multivariate economic analysis of robot performance repeatability and accuracy, Journal of Manufacturing Systems 15(4) (1996).
26. E. Nagai and T. C. E. Cheng, Identifying potential barriers to total quality management using principal component analysis and correspondence analysis, International Journal of Quality and Reliability Management 14(4) (1997) 391-408.
27. O. Port and G. Smith, Quality: Small and midsize companies seize the challenge-not a moment too soon, Business Week 30 (1992).
28. C. S. Sarrico, S. M. Hogan, R. G. Dyson and A. D. Athanassopoulos, Data envelopment analysis and university selection, Journal of the Operational Research Society 48 (1997) 1163-1177.
29. T. G. Schmitt, T. Klastorin and A. Shtub, Production classification system: Concepts, models and strategies, International Journal of Production Research 23(3) (1985).
30. A. M. Schneiderman, Why balanced score card failed, Journal of Strategic Performance Measurement, Special Edition (1999).
31. A. M. Schneiderman, Measurement: The bridge between the hard and soft sides, Journal of Strategic Performance Measurement (1998).
32. S. Sharma, Applied Multivariate Techniques (New York: John Wiley & Sons, 1996).
33. R. Simons, Performance Measurement and Control Systems for Implementing Strategy (New York: Prentice Hall, 2000).
34. D. S. Sink, Productivity Management, 1st edn. (New York: John Wiley & Sons, 1985).
35. F. K. Wang and T. C. T. Du, Using principal component analysis in process performance for multivariate data, Omega 28 (2000) 185-194.
36. J. Zhu, Data envelopment analysis vs. principal component analysis: An illustrative study of economic performance of Chinese cities, European Journal of Operation Research 111 (1998) 50-61.
37. A. Charnes, W. W. Cooper and E. Rhodes, Measuring the efficiency of decision making units, European Journal of Operational Research 2(6) (1978) 429-444.
38. A. Charnes, W. W. Cooper, A. Y. Lewin and L. M. Seiford, Data Envelopment Analysis: Theory, Methodology and Applications (Kluwer Academic Publishers, Massachusetts, 1994).
39. R. D. Banker, A. Charnes and W. W. Cooper, Some models for estimating technical and scale inefficiencies in DEA, Management Science 32 (1984) 1078-1092.