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An integrated AHP-GTA approach for measuring effectiveness of quality tools and techniques

  • Vivek SharmaEmail author
  • Sandeep Grover
  • S. K. Sharma
Original Article
  • 14 Downloads

Abstract

Modern organizations that wish to be successful and to achieve world-class manufacturing must possess both effective and efficient use of Quality tools and techniques (QT&T) for enhancing their performance. A large number of tools, techniques and systematic methodologies are being used in industries for enhancing their performance. Different tools and techniques have different perceived effect on quality improvement. Implementation of QT&T in different manufacturing organizations is not an easy task and requires a methodology to evaluate the effectiveness and intensity of individual QT&T. In the present exertion, various QT&T are grouped into six different categories namely, new product development tools (NPDT), decision making tools, data collection and analysis tools, lean tools, performance measurement tools and software tools which have been analyzed by using integrated multi-criteria decision making approach based on graph theoretic approach and analytic hierarchy process to measure the effectiveness of QT&T. This paper addresses NPDT tools are having high effectiveness and impact on manufacturing organization as obtained in the analysis.

Keywords

Quality Tool Techniques Classification AHP GTA 

Notes

References

  1. Bam ford DR, Great banks RW (2005) The use of quality management tools and techniques: a study of application in everyday situations. Int J Qual Reliab Manag 22(4):376–392CrossRefGoogle Scholar
  2. Chen WK (1997) Digraph theory and its engineering applications, vol 5. World Scientific Publishing Company, SingaporeCrossRefGoogle Scholar
  3. Chin KS, Pun KF, Xu Y, Chan JSF (2002) An AHP based study of critical factors for TQM implementation in Shanghai manufacturing industries. Technovation 22(11):707–715CrossRefGoogle Scholar
  4. Dale B (2003) Managing quality, (vol 4). Blackwell Publishers, OxfordGoogle Scholar
  5. Forman E, Gass S (2001) the analytic hierarchy process—An exposition. Oper Res 49(4):469–486MathSciNetCrossRefGoogle Scholar
  6. Gambhir V, Wadhwa NC, Grover S (2016) Quality concerns in technical education in India. Qual Assur Edu 24(1):2–25CrossRefGoogle Scholar
  7. Grover S, Singh V (2007) A graph theoretic approach to the use of quality tools and techniques. Int J Oper Quantum Manag 13(3):199–209Google Scholar
  8. Grover S, Aggrawal VP, Khan IA (2004) A digraph approach to TQM evaluation of an industry. Int J Prod Res 42(19):4031–4053CrossRefGoogle Scholar
  9. Hellsten U, Klefsjö B (2000) TQM as a management system consisting of values, techniques and tools. TQM Mag 12(4):238–244CrossRefGoogle Scholar
  10. Jense JB, Gutin G (2000) Digraph theory, algorithms, and applications. Springer, LondonGoogle Scholar
  11. Jurkat WB, Ryser HJ (1966) Matrix factorization of determinants and permanents’. J Algebra 3(1):1–27MathSciNetCrossRefGoogle Scholar
  12. Kovach JV, Cudney EA, Elrod CC (2011) The use of continuous improvement techniques: a survey-based study of current practices. Int J Eng Sci Technol 3(7):89–100Google Scholar
  13. Mc Quarter RE, Scurr CH, Dale BG, Hillman PG (1995) Using quality tools and techniques successfully. TQM Mag 7(6):37–42CrossRefGoogle Scholar
  14. Mehra S, Holfman JM, Sirias D (2001) TQM as a management strategy for the next millennia. Int J Oper Prod Manag 21(5/6):855–876CrossRefGoogle Scholar
  15. Raj T, Attri R (2010) Quantifying barriers to implementing total quality management (TQM). Eur J Ind Eng 4(3):308–335CrossRefGoogle Scholar
  16. Rao RV, Padmanabhan KK (2006) Selection, identification and comparison of industrial robots using digraph and matrix methods. Robot Comput Integr Manuf 22(4):373–383CrossRefGoogle Scholar
  17. Saaty TL (1980) The analytic hierarchy process. McGraw- Hill publications, New YorkzbMATHGoogle Scholar
  18. Saaty TL (1985) Decision making for leaders (Belmont. Life Time Leaning Publications, California)Google Scholar
  19. Saaty TL (1990) How to make a decision: the analytic hierarchy process. Eur J Oper Res 48(1):9–26CrossRefGoogle Scholar
  20. Saaty TL, Kearns KP (1991) Analytical planning: the organization systems. The analytic hierarchy process series, vol 4. RWS Publications, PittsburghGoogle Scholar
  21. Sharma VK, Chandana P, Bhardwaj A (2015) Critical factors analysis and its ranking for implementation of GSCM in Indian dairy industry. J Manuf Technol Manag 26(6):911–922CrossRefGoogle Scholar
  22. Thia CW, Chai Kah-Hin, Bauly J, Yan X (2005) An exploratory study of the use of quality tools and techniques in product development. TQM Mag 17(5):406–424CrossRefGoogle Scholar
  23. Thiagaragan T, Zairi M, Dale BG (2001) A proposed model of TQM implementation based on an empirical study of Malaysian industry. Int J Qual Reliab Manag 18(3):289–306CrossRefGoogle Scholar

Copyright information

© The Society for Reliability Engineering, Quality and Operations Management (SREQOM), India and The Division of Operation and Maintenance, Lulea University of Technology, Sweden 2019

Authors and Affiliations

  1. 1.Department of Mechanical EngineeringJ.C. Bose University of Science and Technology, YMCAFaridabadIndia
  2. 2.Department of Mechanical EngineeringNIT KurukshetraKurukshetraIndia

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