Use of Analytic Hierarchy Process (AHP) to Support the Decision-Making About Destination of a Batch of Defective Products with Alternatives of Rework and Discard

  • João Cláudio Ferreira Soares
  • Anabela Pereira Tereso
  • Sérgio Dinis Teixeira Sousa
Conference paper
Part of the Springer Proceedings in Mathematics & Statistics book series (PROMS, volume 223)

Abstract

This study discusses the application of Analytic Hierarchy Process (AHP) to support the decision-making regarding the destination of a batch of defective products. The alternatives of destination are rework or discard. Six criteria of analysis and comparison were used. The mathematical development of the model was performed in Excel, which allowed several interactions and simulations, giving greater reliability to its application. The study was developed in a Brazilian plant of a Japanese auto parts industry which supplies a world-renowned Japanese motorcycle manufacturer. The defective product is the steering column of one of the models that presented the weld bead displaced from the correct position. From a flow of analysis of quality problems, the AHP method was adapted and applied in this case study, using evaluation questions to establish the criteria for comparison. The evidence generated by the problem analysis promotes answers and determination of criteria weights according to the influences of the answers on the cost and the quality of the product in case of rework or disposal. The AHP method assisted the systematization of the decision process, allowing the developed system to be used in other quality problems involving the destination of defective products. The contribution of this work is the adaptation of the AHP method to the application of problems of this type, using questions and answers (information already existent in the analysis of quality problems). In continuation of this specific application, the format can be adapted to the reality of other companies with inclusion or exclusion of criteria and weightings as necessary, justified, either by the characteristic of the problem or by internal policies. The applied method assisted in the decision to discard the parts of the study.

Keywords

AHP Cost Decision-making Quality 

References

  1. 1.
    M.P. Amiri, Project selection for oil-fields development by using the AHP and fuzzy TOPSIS methods. Expert Syst. Appl. 9(37), 6218–6224 (2010).  https://doi.org/10.1016/j.eswa.2010.02.103
  2. 2.
    T. Arabian, M. Jourabchi, Z. Leman, M. Ismail, A research on the impact of cost of quality models and reporting system on managing cost of quality. Int. Proc. Econ. Dev. Res. 36(55), 178–183 (2013).  https://doi.org/10.7763/IPEDR
  3. 3.
    A.V. Bentes, J. Carneiro, J.F. da Silva, H. Kimura, Multidimensional assessment of organizational performance: integrating BSC and AHP. J. Bus. Res. 12(65), 1790–1799 (2012).  https://doi.org/10.1016/j.jbusres.2011.10.039
  4. 4.
    E. Bulut, O. Duru, T. Keçeci, S. Yoshida, Use of consistency index, expert prioritization and direct numerical inputs for generic fuzzy-AHP modeling: a process model for shipping asset management. Expert Syst. Appl. 2(32), 1911–1923 (2012).  https://doi.org/10.1016/j.eswa.2011.08.056
  5. 5.
    G. Büyüközkan, G. Çifçi, A combined fuzzy AHP and fuzzy TOPSIS based strategic analysis of electronic service quality in healthcare industry. Expert Syst. Appl. 3(39), 2341–2354 (2012).  https://doi.org/10.1016/j.eswa.2011.08.061
  6. 6.
    U. Cebeci, Fuzzy AHP-based decision support system for selecting ERP systems in textile industry by using balanced scorecard. Expert Syst. Appl. 5(36), 8900–8909 (2009).  https://doi.org/10.1016/j.eswa.2008.11.046
  7. 7.
    D.-Y. Chang, Applications of the extent analysis method on fuzzy AHP. Eur. J. Oper. Res. 3(95), 649–655 (1996).  https://doi.org/10.1016/0377-2217(95)00300-2
  8. 8.
    N.N. Cheek, B. Schwartz, On the meaning and measurement of maximization. Judgm. Decis. Mak. 2(11), 126–146 (2016).  https://doi.org/10.1007/BF02722112
  9. 9.
    A. Chopra, D. Garg, A research on the impact of cost of quality models and reporting system on managing cost of quality. TQM J. 5(23), 510–515 (2011).  https://doi.org/10.1108/17542731111157617
  10. 10.
    P.B. Crosby, Quality is Free: The Art of Making Quality Certain (New American Library Edition, New York, 1979).  https://doi.org/10.2172/1025774
  11. 11.
    M. Daǧdeviren, S. Yavuz, N. Kilinç, Weapon selection using the AHP and TOPSIS methods under fuzzy environment. Expert Syst. Appl. 4(36), 8143–8151 (2009).  https://doi.org/10.1016/j.eswa.2008.10.016
  12. 12.
    M.C. Das, B. Sarkar, S. Ray, A framework to measure relative performance of Indian technical institutions using integrated fuzzy AHP and COPRAS methodology. Socio-Econ. Plan. Sci. 3(46), 230–241 (2012).  https://doi.org/10.1016/j.seps.2011.12.001
  13. 13.
    M.A.P. Davies, A multicriteria decision model application for managing group decisions. J. Oper. Res. Soc. 45(1), 47–58 (1994), http://www.jstor.org/stable/2583950
  14. 14.
    F. Dweiri, S. Kumar, S.A. Khan, V. Jain, Designing an integrated AHP based decision support system for supplier selection in automotive industry. Expert Syst. Appl. 62, 273–283 (2016).  https://doi.org/10.1016/j.eswa.2016.06.030
  15. 15.
    F.S. Fogliatto, S.L. Albin, An AHP-based procedure for sensory data collection and analysis in quality and reliability applications. Food Qual. Prefer. 5–6(14), 375–385 (2003).  https://doi.org/10.1016/S0950-3293(03)00006-5
  16. 16.
    E. Forman, K. Peniwati, Aggregating individual judgments and priorities with the analytic hierarchy process. Eur. J. Oper. Res. 1(108), 165–169 (1998).  https://doi.org/10.1016/S0377-2217(97)00244-0
  17. 17.
    R. Gopalan, Sreekumar, B. Satpathy, Evaluation of retail service quality – a fuzzy AHP approach. Benchmarking Int. J. 6(22), 1058–1080 (2015).  https://doi.org/10.1108/BIJ-05-2013-0052
  18. 18.
    J.M. Juran, A.B. Godfrey, Juran’s quality handbook. Deutsche medizinische Wochenschrift 1 (1946) (1999).  https://doi.org/10.1055/s-0031-1280544
  19. 19.
    T. Kaya, C. Kahraman, An integrated fuzzy AHP-ELECTRE methodology for environmental impact assessment. Expert Syst. Appl. 7(38), 8553–8562 (2011).  https://doi.org/10.1016/j.eswa.2011.01.057
  20. 20.
    T. Kaya, C. Kahraman, Fuzzy multiple criteria forestry decision making based on an integrated VIKOR and AHP approach. Expert Syst. Appl. 6(38), 7326–7333 (2011).  https://doi.org/10.1016/j.eswa.2010.12.003
  21. 21.
    O. Kilincci, S.A. Onal, Fuzzy AHP approach for supplier selection in a washing machine company. Expert Syst. Appl. 8(38), 9656–9664 (2011).  https://doi.org/10.1016/j.eswa.2011.01.159
  22. 22.
    S. Kumar, O.S. Vaidya, Analytic hierarchy process: an overview of applications. Eur. J. Oper. Res. 1(169), 1–29 (2006).  https://doi.org/10.1016/j.ejor.2004.04.028
  23. 23.
    H. Mintzberg, D. Raisinghani, A. Thérêt, The structure of “unstructured” decision processes. Adm. Sci. Q. 2(21), 246–275 (1976).  https://doi.org/10.2307/2392045
  24. 24.
    E.W.T. Ngai, E.W.C. Chan, Evaluation of knowledge management tools using AHP. Expert Syst. Appl. 4(29), 889–899 (2005).  https://doi.org/10.1016/j.eswa.2005.06.025
  25. 25.
    I. Ognjanović, D. Gaševć, E. Bagheri, A stratified framework for handling conditional preferences: an extension of the analytic hierarchy process. Expert Syst. Appl. 4(40), 1094–1115 (2013).  https://doi.org/10.1016/j.eswa.2012.08.026
  26. 26.
    S. Opricovic, G.H. Tzeng, Compromise solution by MCDM methods: a comparative analysis of VIKOR and TOPSIS. Eur. J. Oper. Res. 2(156), 445–455 (2004).  https://doi.org/10.1016/S0377-2217(03)00020-1
  27. 27.
    M. Plewa, G. Kaiser, E. Hartmann, Is quality still free?: empirical evidence on quality cost in modern manufacturing. Int. J. Qual. Reliab. Manag. 9(33), 1270–1285 (2016).  https://doi.org/10.1108/IJQRM-11-2014-0189
  28. 28.
    G.R. Pophali, A.B. Chelani, R.S. Dhodapkar, Optimal selection of full scale tannery effluent treatment alternative using integrated AHP and GRA approach. Expert Syst. Appl. 9(38), 10889–10895 (2011).  https://doi.org/10.1016/j.eswa.2011.02.129
  29. 29.
    R. Rostamzadeh, S. Sofian, Prioritizing effective 7ms to improve production systems performance using fuzzy AHP and fuzzy TOPSIS (case study). Expert Syst. Appl. 5(38), 5166–5177 (2011).  https://doi.org/10.1016/j.eswa.2010.045
  30. 30.
    R.D.F.S.M. Russo, R. Camanho, Criteria in AHP: a systematic review of literature. Procedia Comput. Sci. 55, 1123–1132 (2015).  https://doi.org/10.1016/j.procs.2015.07.081
  31. 31.
    T.L. Saaty, Decision making with the analytic hierarchy process. Int. J. Serv. Sci. 1(1) (2008), http://www.colorado.edu/geography/leyk/geog_5113/readings/saaty_2008.pdf
  32. 32.
    T.L. Saaty, L.T. Tran, On the invalidity of fuzzifying numerical judgments in the analytic hierarchy process. Math. Comput. Model. 7–8(46), 962–975 (2007).  https://doi.org/10.1016/j.mcm.2007.03.022
  33. 33.
    A. Sailaja, P. Basak, K. Viswanadhan, Hidden costs of quality: measurement and analysis. Int. J. Manag. Value Supply Chains 2(6), 13–25 (2015).  https://doi.org/10.5121/ijmvsc.2015.6202
  34. 34.
    D. Sandoval-Chávez, M. Beruvides, Using opportunity costs to determine the cost of quality: a case study in a continuous-process industry. Eng. Econ. 2(43), 107–124 (1998).  https://doi.org/10.1080/00137919808903192
  35. 35.
    A. Schiffauerova, V. Thomson, A review of research on cost of quality models and best practices. Int. J. Qual. Reliab. Manag. 6(23), 647–669 (2006).  https://doi.org/10.1108/02656710610672470
  36. 36.
    H.A. Simon, The New Science of Management Decision (Prentice Hall PTR, Upper Saddle River, 1977)Google Scholar
  37. 37.
    A.K. Singh, Competitive service quality benchmarking in airline industry using AHP. Benchmarking: Int. J. 4(23), 768–791 (2016).  https://doi.org/10.1108/BIJ-05-2013-0061
  38. 38.
    J.C. Soares, S.D. Sousa, E. Nunes, Application of the three realities approach to customer complaints analysis in the motorcycles industry. Int. Conf. Ind. Eng. Oper. Manag. 1–10 (2012), http://hdl.handle.net/1822/21749
  39. 39.
    C.C. Sun, A performance evaluation model by integrating fuzzy AHP and fuzzy TOPSIS methods. Expert Syst. Appl. 12(37), 7745–7754 (2010).  https://doi.org/10.1016/j.eswa.2010.04.066
  40. 40.
    F. Talib, Z. Rahman, Identification and prioritization of barriers to total quality management implementation in service industry. TQM J. 5(27), 591–615 (2015).  https://doi.org/10.1108/TQM-11-2013-0122
  41. 41.
    R.R. Tan, K.B. Aviso, A.P. Huelgas, M.A.B. Promentilla, Fuzzy AHP approach to selection problems in process engineering involving quantitative and qualitative aspects. Process Saf. Environ. Prot. 5(92), 467–475 (2014).  https://doi.org/10.1016/j.psep.2013.11.005
  42. 42.
    J. Wallenius, J.S. Dyer, P.C. Fishburn, R.E. Steuer, S. Zionts, K. Deb, R.E. Steuer, Multiple criteria decision making, multiattribute utility theory: recent accomplishments and what lies ahead. Manag. Sci. 54(7), 1–32 (2008).  https://doi.org/10.1287/mnsc.1070.0838
  43. 43.
    H. Water, J. Vries, Choosing a quality improvement project using the analytic hierarchy process. Int. J. Qual. Reliab. Manag. 4(23), 409–425 (2006).  https://doi.org/10.1108/02656710610657602
  44. 44.
    A. Weckenmann, G. Akkasoglu, T. Werner, Quality management – history and trends. TQM J. 3(23), 281–293 (2015), http://dx.doi.org/10.1108/TQM-11-2013-0125
  45. 45.
    X. Xi, Q. Qin, Product quality evaluation system based on AHP fuzzy comprehensive evaluation. J. Ind. Eng. Manag. 1(6), 356–366 (2013).  https://doi.org/10.3926/jiem.685

Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  • João Cláudio Ferreira Soares
    • 1
  • Anabela Pereira Tereso
    • 1
  • Sérgio Dinis Teixeira Sousa
    • 1
  1. 1.Centre ALGORITMIUniversity of MinhoGuimarãesPortugal

Personalised recommendations