Comparison of Fuzzy AnalyticHierarchy Process and Analytic Hierarchy Process Based Decision Support for a Lean Performance Measurement System
Abstract
A performance measurement framework for a company that adopted lean manufacturing is needed to measure their achievement in the implementation of lean manufacturing system.A comprehensive design of the performance measurement framework requires an understanding of all the elements including performance of perspectives and key indicators of measurements, anddecision support methods such asFuzzy Analytic Hierarchy Process (FAHP) and Analytic Hierarchy Process (AHP).The comparison of original AHP and FAHP methods in term of decision making for lean manufacturing performance measurement system was performed in this paper. A benchmarking to compute performance based on weight between FAHP and AHP was done as a case study in automotive company. The result of the weight values of AHP and FAHP methods indicatedalmost similar among performances of lean perspectives and indicators for the company’s case study.
##Keywords:##
Lean manufacturing PMS, AHP, FAHP.
Published
Mar 30, 2016
How to Cite
SUSILAWATI, Anita; TAN, John.
Comparison of Fuzzy AnalyticHierarchy Process and Analytic Hierarchy Process Based Decision Support for a Lean Performance Measurement System.
Journal of Ocean, Mechanical and Aerospace -science and engineering-, [S.l.], v. 29, n. 1, p. 8-15, mar. 2016.
ISSN 2527-6085.
Available at: <https://isomase.org/Journals/index.php/jomase/article/view/418>. Date accessed: 25 apr. 2026.
doi: http://dx.doi.org/10.36842/jomase.v29i1.418.
References
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24. Kabir, G. and Hasin, M.A.A. (2011). Evaluation of Customer Oriented Success Factors in Mobile Commerce Using Fuzzy AHP, Journal of Industrial Engineering and Management, Vol. 4, No. 2, pp: 361-386. 25. Jaskowski, P., Biruk, S. and Bucon, R. (2010). Assessing Contractor Selection Criteria Weights with Fuzzy AHP Method Application in Group Decision Environment, Automation in Construction, Vol. 19, pp: 120-126.
26. Tang, Y. C. and Beynon, M. J. (2009). Group Decision-Making Within Capital Investment: a Fuzzy Analytic Hierarchy Process Approach with Developments, International Journal of Operational Research, Vol. 4, pp: 75-96.
27. Lee, A.H.I., Chen, W.C. and Chang, C.J. (2008). A Fuzzy AHP and BSC Approach for Evaluating Performance of IT Department in the Manufacturing Industry in Taiwan, Expert Systems with Applications, Vol. 34, pp: 96-107.
28. Tan, R.R., Briones, L.M.A. and Culaba, A.B. (2007).Fuzzy Data Reconciliation in Reacting and Non-Reacting Process Data for Life Cycle Inventory Analysis, Journal of Cleaner Production Vol. 15, pp: 944-949.
29. Susilawati, A., Tan, J., Bell, D. and Sarwar, M. (2012). A multiple criteria decision making based performance measurement and improvement model for lean manufacturing activities, Proceeding of the International Conference on Mechanical, Automobile and Robotics Engineering (ICMAR), Singapore, 14-15 December 2012, pp: 171-177.
2. Anand, G. and Kodali, R. (2008). Performance Measurement System for Lean Manufacturing: a Perspective from SMEs’, International Journal of Globalisation and Small Business Vol. 2, No. 4, pp: 371-410.
3. Anand, G. and Kodali, R. (2009). Development of a Framework for Lean Manufacturing Systems, International Journal of Services and Operations Management, Vol. 5, No.5, pp: 687-716.
4. Wong, Y.C. and Wong, K.Y. (2011). A Lean Manufacturing Framework for the Malaysian Electrical and Electronics Industry, The 3rd International Conference on Information and Financial Engineering IPEDR, Vol. 12.
5. Agus, A. and Iteng, R. (2013). Lean Production and Business Performance: the Moderating Effect of the Length of Lean Adoption, Journal of Economics, Business and Management, Vol. 1, No. 4.
6. Kennerley, M. and Neely, A. (2002). A Framework of the Factors Affecting the Evolution of Performance Measurement Systems. International Journal of Operations and Production Management, Vol. 22, No.11, pp: 1222-1245.
7. Lynch, R.L. and Cross, K.F. (1991).Measure Up - the Essential Guide to Measuring Business Performance: London, Mandarin.
8. Fortuin, L. (1988). Performance Indicators - Why, Where and How?. European Journal of Operational Research, Vol. 34, No. 1, pp: 1-9.
9. Kaplan, R.S. and Norton, D.P. (1996). Using the Balanced Score Card as a Strategic Management System, Harvard Business Review, Vol. 74, No. 1, pp: 75-85.
10. Bititci, U.S., Carrie, A.S. and Mcdevitt, L. (1997). Integrated Performance Measurement Systems: a Development Guide, International Journal of Operations and Production Management, Vol. 17, No. 1, pp: 522-534.
11. Neely, A., Richards, H. J., Mills, J.F., Platts, K. and Bourne, M. (1997). Designing Performance Measures: a Structured Approach, International Journal of Operation and Production Management, Vol. 17, No. 11, pp: 1131-1152.
12. Medori, D. and Steeple, D. (2000). A Framework for Auditing and Enhancing Performance Measurement Systems, International Journal of Operations and Production Management, Vol. 20, No. 5, pp: 520-533.
13. Tangen, S. (2005). Improving the Performance of a Performance Measures, Measuring Business Excellence, Vol. 9, No. 2, pp: 4-11.
14. Lea, R. and Parker, B. (1989). The JIT Spiral of Continuous Improvement, IMDS, Vol. 4, pp: 10-13.
15. Saaty, T.L., Peniwati and Kirti (2008). Group Decision Making: Drawing Out and Reconciling Differences: Pittsburgh, Pennsylvania, RWS Publications.
16. Saaty, T.L. (1980). The Analytic Hierarchy Process: New York, McGraw-Hill.
17. Forman, E.H. and Saul, I.G. (2001). The Analytical Hierarchy Process - an Exposition, Operations Research, Vol. 49, No. 4, pp: 469-487.
18. Partovi, F. (1994). Determining What to Benchmark: an AHP Approach, International Journal of Operations and Production Management, Vol. 14, No. 6, pp: 25-39.
19. Coyle, R.G. (1989). A Mission-Orientated Approach to Defense Planning, Defense Planning, Vol. 5, No. 4, pp: 353-367.
20. Boucher, T.O. and Stravic, M.E.L. (1991). Multi-Attribute Evaluation Within a Present Value Framework and Its Relation to the Analytic Hierarchy Process, The Engineering Economist, Vol. 37, pp: 55-71.
21. Hafeez, K., Zhang, Y. and Malak, N. (2002). Determining Key Capabilities of a Firm Using Analytic HierarchyProcess, International Journal of Production Economics, Vol. 76, pp: 39-51.
22. Vinodh, S., Shivraman, K.R. and Viswesh, S. (2012).AHP-Based Lean Concept Selection in a Manufacturing Organization, Journal of Manufacturing Technology Management, Vol. 23, No. 1, pp: 124-136.
23. Gupta, S.M. and Nukala, S. (2005). A Fuzzy AHP-Based Approach for Selecting Potential Recovery Facilities in a Closed Loop Supply Chain, In http://hdl.handle.net/2047/ d10009851, (Assessed 5th October 2014).
24. Kabir, G. and Hasin, M.A.A. (2011). Evaluation of Customer Oriented Success Factors in Mobile Commerce Using Fuzzy AHP, Journal of Industrial Engineering and Management, Vol. 4, No. 2, pp: 361-386. 25. Jaskowski, P., Biruk, S. and Bucon, R. (2010). Assessing Contractor Selection Criteria Weights with Fuzzy AHP Method Application in Group Decision Environment, Automation in Construction, Vol. 19, pp: 120-126.
26. Tang, Y. C. and Beynon, M. J. (2009). Group Decision-Making Within Capital Investment: a Fuzzy Analytic Hierarchy Process Approach with Developments, International Journal of Operational Research, Vol. 4, pp: 75-96.
27. Lee, A.H.I., Chen, W.C. and Chang, C.J. (2008). A Fuzzy AHP and BSC Approach for Evaluating Performance of IT Department in the Manufacturing Industry in Taiwan, Expert Systems with Applications, Vol. 34, pp: 96-107.
28. Tan, R.R., Briones, L.M.A. and Culaba, A.B. (2007).Fuzzy Data Reconciliation in Reacting and Non-Reacting Process Data for Life Cycle Inventory Analysis, Journal of Cleaner Production Vol. 15, pp: 944-949.
29. Susilawati, A., Tan, J., Bell, D. and Sarwar, M. (2012). A multiple criteria decision making based performance measurement and improvement model for lean manufacturing activities, Proceeding of the International Conference on Mechanical, Automobile and Robotics Engineering (ICMAR), Singapore, 14-15 December 2012, pp: 171-177.
