Skip to main content

Advertisement

Log in

Design and implementation of an integrated Taguchi method for continuous assessment and improvement of manufacturing systems

  • ORIGINAL ARTICLE
  • Published:
The International Journal of Advanced Manufacturing Technology Aims and scope Submit manuscript

Abstract

The aim of this paper is to propose an integrated modeling framework that would help manufacturing managers for assessment, ranking, and analysis of the manufacturing systems. The proposed framework is based on Taguchi method that ranks and analyzes the manufacturing sectors by consolidating a set of management and organization productivity indicators. Sixty-one indicators were identified and classified in five categories, namely (1) financial, (2) customer satisfaction, (3) process innovation, (4) production process, and (5) organizational learning and growth. The mentioned indicators are related to organizational and managerial productivity and efficiency. Next, a test problem and a random sample of 12 indicators have been carried out for the two-digit International Standard Industrial Classification sectors of manufacturing systems. Principal component analysis (PCA), numerical taxonomy, and clustering analysis approach have been used to demonstrate and validate the results of the integrated Taguchi method. Also, Spearman and Kendall tau correlation experiments should show high level of correlation between the findings of Taguchi, PCA, and taxonomy. In addition, normality test has been applied to show the superiority of integrated method over previous approaches. The proposed method has been provided with respect to management and organizational performance indicators to decide the best actions for continuous improvement. The results indicated that the structure and modeling approach of this paper could be easily utilized for managerial and organizational ranking and analysis of other sectors.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. Azadeh MA (2000) Creating highly reliable manufacturing systems: an integrated approach. Int J Reliab Qual Saf Eng 7(3)

  2. MA Azadeh (1999) Creating high reliable manufacturing systems: an integrated approach. In: Proceedings of the Fourth International Conference on Reliability, Maintainability and Safety (ICRMS’99). Shanghai, China

  3. Tompkins JA, Bozer W, Frazelle EH, Tanchoco JMA, Trevino J (1996) Facilities planning. Wiley, New York

    Google Scholar 

  4. Barber KD, Hollier RH (1986) The use of numerical analysis to classify companies according to production control complexity. Int J Prod Res 24(1)

  5. Bolden R, Waterson P, Warr P, Clegg C (1997) A new taxonomy of modern manufacturing practices. Int J Oper Prod Manage 17(11)

  6. Jonsson P (2000) An empirical taxonomy of advanced manufacturing technology. Int J Oper Prod Manage 20(12)

  7. McCarthy I (1995) Manufacturing classification: lessons from organizational systematic and biological taxonomy. Int Manu Sys 6(6):37–48

    Article  Google Scholar 

  8. Schmitt TG, Klastorin T, Shtub A (1985) Production classification system: concepts, models and strategies. Int J Prod Res 23(3)

  9. Harris TJ, Seppala CT, Desborough LD (1999) A review of performance monitoring and assessment techniques for univariate and multivariate control systems. J Proc Cont 9:1–17

    Article  Google Scholar 

  10. Shaw A (1999) A guide to performance measurement and non-financial indicators. The Foundation for Performance Measurement, Surrey, UK

    Google Scholar 

  11. Hitchens D, Birnie JE, Wagner K (1996) A matched plant comparison of productivity in East and West Germany: transition to the market economy. Omega 24(3)

  12. Azadeh MA, Ghaderi SF, Ebrahimipour V (2007) An integrated PCA DEA framework for assessment and ranking of manufacturing systems based on equipment performance. Eng Comp 24(4):347–372

    Article  MATH  Google Scholar 

  13. Azadeh MA, Ghaderi SF, Partovi Miran Y, Ebrahimipour V, Suzuki K (2007) An integrated framework for continuous assessment and improvement of manufacturing systems. Appl Math Comput 186:1216–1233

    Article  MATH  Google Scholar 

  14. Zhang G, He J, Zhu H, Chen X (2007) Manufacturing system modeling and performance evaluation based on improved stochastic state chart. Front Mec Eng China 2:453–458

    Article  Google Scholar 

  15. Oztemel E, Tekez EK (2009) Integrating manufacturing systems through knowledge exchange protocols within an agent-based knowledge network. Robot Comp Int Manu 25:235–245

    Article  Google Scholar 

  16. Singh V, Agrawal VP (2008) Structural modelling and integrative analysis of manufacturing systems using graph theoretic approach. Management 19:844–870

    Google Scholar 

  17. Lin TY, Tseng CH (2000) Optimum design for artificial neural networks: an example in a bicycle derailleur system. Eng Appl Artif Intell 13:3–14

    Article  Google Scholar 

  18. Wang TY, Huang CY (2007) Improving forecasting performance by employing the Taguchi method. Eur J Oper Res 176:1052–1065

    Article  MATH  Google Scholar 

  19. Mohamed H, Lee MH, Sarahintu M, Salleh S, Sanugi B (2008) The use of Taguchi method to determine factors affecting the performance of destination sequence distance vector routing protocol in mobile ad hoc networks. J Math Stat 4:194–198

    Article  MATH  Google Scholar 

  20. Jiao JR, Helo PT (2008) Optimization design of a CUSUM control chart based on Taguchi’s loss function. Int J Adv Manuf Tech 35:1234–1243

    Article  Google Scholar 

  21. Abdolshah M, Yusuff RM, Ismail MY, Hong TS (2009) A new technique to measure process capability with Taguchi loss functions. International Conference on Information Management and Engineering, 186–190

  22. Al-Refaie A, Al-Tahat MD (2009) Solving the multi-response problem in Taguchi method by benevolent formulation in DEA. J Int Manu 22(4):505–521

    Article  Google Scholar 

  23. Chen WC, Hsu YY, Hsieh LF, Tai PH (2010) A systematic optimization approach for assembly sequence planning using Taguchi method, DOE, and BPNN. Exp Sys App 37(1):716–726

    Article  Google Scholar 

  24. Ordoobadi S (2009) Evaluation of advanced manufacturing technologies using Taguchi’s loss functions. Management 20:367–384

    Google Scholar 

  25. Altan M (2009) Reducing shrinkage in injection moldings via the Taguchi, ANOVA and neural network methods. Mater Des 31(1):599–604

    Article  Google Scholar 

  26. Hitomi K (2003) Analysis of manufacturing efficiency: efficiency analysis of Japan’s manufacturing. Center for Manufacturing Systems Engineering, Kyoto, Japan

    Google Scholar 

  27. Hong HK, Ha SH, Shin CK, Park SC, Kim SH (1999) Evaluating the efficiency of integration projects using DEA and machine learning. Exp Sys App 16(3):283–296

    Article  Google Scholar 

  28. Guimaraes T, Matensson N, Stahre J, Igbaria M (1999) Empirically testing the impact of manufacturing complexity on performance. Int J Oper Prod Man 19(12):1254–1269

    Article  Google Scholar 

  29. Terziovski M (2002) Achieving performance excellence through integrated strategy of radical innovation and continuous improvement. Meas Bus Excel 6(2):5–14

    Article  Google Scholar 

  30. Taguchi G (1986) Introduction to quality engineering: designing quality into products and processes. Asian Productivity Organization, Tokyo

    Google Scholar 

  31. Tan KK, Tang KZ (2001) Vehicle dispatching system based on Taguchi-tuned fuzzy rules. Eur J Oper Res 128:545–557

    Article  MATH  Google Scholar 

  32. Phadke MS (1989) Quality engineering using robust design. Prentice Hall, Englewood Cliffs, NJ

    Google Scholar 

  33. Azadeh MA, Jalal S (2001) Identifying the economic importance of industrial sectors by multivariate analysis. J Fac Eng 35(3):437–449

    Google Scholar 

  34. MA Azadeh (2002) A multivariate model for assessment of industrial sectors based on machinery indicators. In: 30th International Conference on Computers & Industrial Engineering, 29 June–2 July 2002. Tinos Island, Greece.

  35. M.A. Azadeh, V. Ebrahimipour, G.R. Ataei (2003) A total machine productivity model for assessment and improvement of electrical manufacturing systems. In: 32nd International Conference in Computers and Industrial Engineering, Limerick, Ireland, August

  36. Azadeh MA, Ebrahimipour V (2004) An integrated approach for assessment and ranking of manufacturing systems based on machine performance. Int J Ind Eng 11(4):349–363

    Google Scholar 

  37. A. Azadeh, V. Ebrahimipour (2002) An integrated approach for assessment of manufacturing sectors based on machine performance: the cases of automotive and food and beverages industries. In: Proceedings of the Manufacturing Complexity Conference. Cambridge University, UK

  38. Pradova V, Boucon CS, de Jong B, Walczak DL (2002) Three-way principal component analysis applied to food analysis: an example. Analytica Chimica Acta 462:133–148

    Article  Google Scholar 

  39. Sharma S (1996) Applied multivariate techniques. Wiley, New York

    Google Scholar 

  40. Zhu J (1998) Data envelopment analysis vs. principal component analysis: an illustrative study of economic performance of Chinese cities. Euro J Oper Res 111:50–61

    Article  MATH  Google Scholar 

  41. Minhas R, Jacobs E (1996) Benefit segmentation by factor analysis: an improved method of targeting customers for financial services. Int J Bank Mark 14(3):3–13

    Article  Google Scholar 

  42. Nagai E, Cheng TCE (1997) Identifying potential barriers to total quality management using principal component analysis and correspondence analysis. Int J Qual Relia Manage 14(4):391–408

    Article  Google Scholar 

  43. Agarwala R (1999) On the approximability of numerical taxonomy (fitting distances by tree metrics). SIAM J Comput 28(3):1073–1085

    Article  MathSciNet  MATH  Google Scholar 

  44. Cohen J, Farach M (1997) Numerical taxonomy on data: experimental results. Department of Computer Science, Rutgers University, New Jersey, USA

    Google Scholar 

  45. Gaibraith P, Haines C (2000) Conceptual misunderstandings of beginning undergraduates. Int J Math Educ Sci Technol 31:651–660

    Article  Google Scholar 

  46. Ricketts A, Taylor H (1999) Who’s where in North America? Bioscience 49:369–375

    Article  Google Scholar 

  47. Thomas S (1987) Dendogram and Celestial tree: numerical taxonomy and variants of the iroquoian creation myth. Can J Nat Stud 7:195–221

    Google Scholar 

  48. Buja A, Cook D (1996) Interactive high-dimensional data visualization. J Comput Graph Stat 5(1):78–99

    Article  Google Scholar 

  49. Chavent M (1998) A monothetic clustering method. Pat Recog Let 19:989–996

    Article  MATH  Google Scholar 

  50. He Q (1999) A review of clustering algorithms as applied in IR, graduate school of library and information science. University of Illinois at Urban–Champaign, USA

  51. Hulten CR (2001) Total factor productivity: a short biography. In: Hulten CR, Dean ER, Harper MJ (eds) New developments in productivity analysis. University of Chicago Press for the National Bureau of Economic Research, Chicago

    Google Scholar 

  52. Sarrico CS, Hogan SM, Dyson RG, Athanassopoulos AD (1997) Data envelopment analysis and university selection. J Oper Res Soc 48:1163–1177

    Article  MATH  Google Scholar 

  53. Tat Y, Raymond J (2000) Levels of satisfaction among Asian and Western travelers. Int J Qual Reliab Manage 17(2):116–132

    Article  Google Scholar 

  54. Davenport TH (1993) Process innovation: reengineering wok through information technology. Harvard Business School, Watertown, MA

    Google Scholar 

  55. Kaplan RS (1996) Balanced score card: translating strategy into action. Harvard Business School, Watertown, MA

    Google Scholar 

  56. Rucci AJ, Kirn SP, Quinn RT (1998) The employee–customer profit chain at sears. Harvard Business Review (September–October)

  57. Shingo S (1985) A revolution in manufacturing. Productivity Press, Portland, OR

    Google Scholar 

  58. Simons R (2000) Performance measurement and control systems for implementing strategy. Prentice Hall, New York

    Google Scholar 

  59. Hax AC, Majluf NS (1996) The strategy approach and process: a pragmatic approach. Prentice Hall, New York

    Google Scholar 

  60. Kaplan RS, Norton DP (1993) Putting balanced score card to work, Harvard Business Review (January–February)

  61. Proud JF (1999) Master scheduling: a practical guide to competitive manufacturing. Wiley, New York

    Google Scholar 

  62. M. Schneiderman (1999) Why balanced score card failed. J Strat Perf Meas: 6–11

  63. Schneiderman M (1998) Measurement: the bridge between the hard and soft sides. J Strat Perf Meas 2(2):14–21

    Google Scholar 

  64. Waller DL (1999) Operation management: a supply chain approach. International Business Press, London, UK

    Google Scholar 

  65. Zain Mohammed M, Rickards T (1996) Assessing and comparing the innovativeness and creative climate of firms. Scand J Manag 96(3–6):109–121

    Article  Google Scholar 

  66. World Bank (1995) World Bank World Development Report

  67. World Bank (1998) World Bank World Development Indicators (1998)

  68. UNIDO (1999) UNIDO International Year Book of Industrial Statistics

  69. US Department of Labor (2000) US department of labor multifactor productivity measures for three-digit SIC manufacturing industries. US Department of Labor, Bureau of Labor Statistics, Report 948.

  70. Ross PJ (1996) Taguchi techniques for quality engineering. McGraw Hill, Columbus, OH

    Google Scholar 

  71. Taguchi G (1990) An introduction to quality engineering. Asian Productivity Organisation, Tokyo

    Google Scholar 

  72. Fowlkes WY, Creveling CM (1995) Engineering methods for robust product design: using Taguchi methods in technology and product development. Addison-Wesley, Reading, MA

    Google Scholar 

  73. Koho M (2007) Streamlining the order-delivery process with a framework for improving manufacturing systems, IET International Conference on Agile Manufacturing, 2007. ICAM 2007:32–40

    Google Scholar 

  74. Hernandez-Matias JC, Vizan A, Perez-Garcia J, Rios J (2008) An integrated modelling framework to support manufacturing system diagnosis for continuous improvement. Robot Comp Int Manuf 24:187–199

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Ali Azadeh.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Azadeh, A., Miri-Nargesi, S.S., Goldansaz, S.M. et al. Design and implementation of an integrated Taguchi method for continuous assessment and improvement of manufacturing systems. Int J Adv Manuf Technol 59, 1073–1089 (2012). https://doi.org/10.1007/s00170-011-3549-2

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00170-011-3549-2

Keywords

Navigation