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Interpretive Structural Modeling of Functional Objectives (Criteria’s) of Assembly Line Balancing Problem

by Pallavi Sharma, G. Thakar, R. C. Gupta
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 83 - Number 13
Year of Publication: 2013
Authors: Pallavi Sharma, G. Thakar, R. C. Gupta
10.5120/14508-2883

Pallavi Sharma, G. Thakar, R. C. Gupta . Interpretive Structural Modeling of Functional Objectives (Criteria’s) of Assembly Line Balancing Problem. International Journal of Computer Applications. 83, 13 ( December 2013), 14-22. DOI=10.5120/14508-2883

@article{ 10.5120/14508-2883,
author = { Pallavi Sharma, G. Thakar, R. C. Gupta },
title = { Interpretive Structural Modeling of Functional Objectives (Criteria’s) of Assembly Line Balancing Problem },
journal = { International Journal of Computer Applications },
issue_date = { December 2013 },
volume = { 83 },
number = { 13 },
month = { December },
year = { 2013 },
issn = { 0975-8887 },
pages = { 14-22 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume83/number13/14508-2883/ },
doi = { 10.5120/14508-2883 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:59:16.644581+05:30
%A Pallavi Sharma
%A G. Thakar
%A R. C. Gupta
%T Interpretive Structural Modeling of Functional Objectives (Criteria’s) of Assembly Line Balancing Problem
%J International Journal of Computer Applications
%@ 0975-8887
%V 83
%N 13
%P 14-22
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Use of interpretative structural modeling (ISM) is inspired by the versatility displayed by this method, as reported by researchers, across a wide spectrum of economic and competitive complexities affecting businesses. The aim of this paper is to develop and analyze the relationship among the identified various functional /technical objectives (criteria's) of assembly line balancing problem using interpretative structural modeling (ISM) and classify these objectives (criteria's) depending upon their driving and dependence power. A Criteria Survey Sheet of objectives (criteria's) of assembly line balancing problem was prepared on the basis of literature review. A total of ten functional/technical objectives (criteria's) of assembly line balancing problem were identified on the basis of industrial survey. And a structured structural- self interaction and reach ability matrices were formed and iterated to yield levels of hierarchical influence of each objectives (criteria's). MICMAC analysis was also performed to determine dependency and driving power of these objectives (criteria's). Finally, ISM model is constructed. The present study is a hitherto unexplored attempt, using interpretative structural modeling to determine the level of influence of these objectives (criteria's) on the efficiency of assembly line of manufacturing industries.

References
  1. Agarwal, A. , Shankar, R. , and Tiwari, M. K. , 2007. Modeling agility of supply chain. Industrial Marketing Management, 36 (4), 443–457.
  2. Anderson, J. and Narus, J. (1990). A model of distributor firm and manufacturer firm working partnerships. Journal of Marketing, 54(1):42–58.
  3. Cachon, G. and Lariviere, M. (2005). Supply chain coordination with revenue sharing Contracts: strengths and limitations. Management Science, 51(1):30–44.
  4. Chan, F. T. S. , 2003. Interactive selection model for supplier selection process: an analytical hierarchy process approach. International Journal of Production Research, 41 (15), 3549–3579.
  5. Charan, P. , Shankar, R. , and Baisya, R. (2008). Analysis of interactions among the variables of supply chain performance measurement system implementation. Business Process Management Journal, 14(4):512–529.
  6. Chellappan, C. and Natarajan, M. (2010). Fuzzy rule based model for the perishable collection-production-inventory system. International Journal of Management Science and Engineering Management, 6(3):183–190,
  7. Dar-El, E. , (1973) MALB – A heuristic technique for balancing large single model assembly lines. AIIE Transactions, 5, 343-356.
  8. Dar-El, E. M. , 1975, Solving large single model assembly line balancing problems-A comparative study. AIIE Transactions, 7(3).
  9. Driscoll, J. , (1999), Users guide to the A Line software package. Unpublished working paper, University of Surrey.
  10. Driscoll, J. , Thilakawardana, D. , (2001), The definition of assembly line balancing difficulty and evaluation of balance solution quality. Robotics and Computer Integrated Manufacturing 17, S81–S86.
  11. F. Jolai ,M. Jahangoshai Rezaee , A. Vazifeh, (2009), Multi-criteria decision making for assembly line balancing, J Intell Manuf . 20:113–121.
  12. Farris, D. and Sage, A. (1975). On the use of interpretive structural modelling for worth assessment. Computers & Electrical Engineering, 2, 149–174.
  13. Ghosh, S. , Gagnon, R. J. , (1989), A comprehensive literature review and analysis of the design, balancing and scheduling of assembly systems. International Journal of Production Research 27, 637–670.
  14. H. D. Sharma, A. D. Gupta, and S. Sushil, "The objectives of waste management in India: a futures inquiry",Technological Forecasting and Social Change, Vol. 48, pp. 285-309. 1995.
  15. Hami Farkhondeh ,Reza Hassanzadeh, Iraj Mahdavi &Nezam Mahdavi-Amiri,(2012), A DEA approach for comparing solution efficiency in U-line balancing problem using goal programming Int J Adv Manuf Technol ,61:1161–1172
  16. Kannan, G. and Haq, A. N. , 2007. Analysis of interactions of criteria and sub-criteria for the selection of supplier in the built-inorder supply chain environment. International Journal of Production Research, 45 (17), 3831–3852.
  17. Kilbridge, M. and Wester, L. (1961), The balance delay problem, Management Science, 8, 69-84.
  18. Kiran Banga Chhokar,(2010), "Higher education and curriculum innovation for sustainable development in India", International Journal of Sustainability in Higher Education Vol. 11 No. 2, pp. 141-152.
  19. Lee, Y. -C. , Chao, Y. H. , and Lin, S. -B. , 2010. Structural approach to design user interface. Computers in Industry, 61, 613–623.
  20. Li, W. L. , et al. , 2003. Predicting purchasing performance: the role of supplier development programs. Journal of Materials Processing Technology, 138 (1–3), 243–249.
  21. Liao, C. H. and Tseng, M. L. , 2009. Using interpretive structural modeling and AHP to evaluate the worker productivity criteria in uncertainty. WSEAS Transaction on Business and Economics, 6 (8), 435–445.
  22. Malakooti,B. ,A, 1994,assembly line balancing problem with buffers by multiple criteria optimization, International journal of production 32,(9),2159-2178.
  23. Mandal, A. and Deshmukh, S. G. , 1994. Vendor selection using interpretive structural modeling. International Journal of Operations and Production Management, 14 (6), 52–59.
  24. Manuel Chica , Óscar Cordón ,Sergio Damas, (2011), An advanced multi objective genetic algorithm design for the time and space assembly line balancing problem. Computers & Industrial Engineering 61 (2011) 103–117.
  25. Md. Alamgir Kabir, Mario T. Tabucanon, (1995), Multi Attribute Decision Making Approach, Int. J. Production Economics 41, 193-201.
  26. Moodie, C. L. and Young, H. H. , (1965), A heuristic method of assembly line balancing for assumptions of constant or variable work element times. Journal of Industrial Engineering, 16, 23-29.
  27. Nima Hamta, S. M. T. Fatemi Ghomi, F. Jolai, Unes Bahalke (2011), "Bi-criteria assembly line balancing by considering flexible operation times". Applied Mathematical Modelling Vol. 35, pp. 5592–5608.
  28. Nuchsara Kriengkorakot, et. al. (2007), The Assembly Line Balancing Problem: Review articles, KKU Engineering Journal Vol. 34 No . 2 ,133 – 140.
  29. Pandey, V. C. , Suresh, G. , and Ravi, S. , 2005. An interpretive structural modeling of enabler variables for integration in supply chain management. Productivity, 46 (1), 93–108.
  30. Raj, T. , Shankar, R. , and Suhaib, M. , 2008. An ISM approach for modelling the enablers of flexible manufacturing system: the case for India. International Journal of Production Research, 46 (24), 6883–69.
  31. Rajesh, K. S. , Suresh, K. G. , and Deshmukh, S. G. , 2007. Interpretive structural modeling of factors for improving competitiveness of SMEs. International Journal of Productivity and Quality Management, 2 (4), 423–440
  32. Sage, A. (1977). Interpretive Structural Modelling: Methodology for Large-scale Systems. McGraw-Hill, New York, NY.
  33. Scholl, A. , 1999. Balancing and sequencing assembly lines, 2nd ed. Physica, Heidelberg.
  34. Sharma, H. , Gupta, A. , and Sushil. (1995). The objectives of waste management in India: a future inquiry. Techology Forecast & Social Change, 48, 285–309.
  35. Warfield, J. (1974). Developing interconnected matrices in structural modelling. IEEE Transcript on Systems, Men and Cybernetics, 4(1):51–81.
  36. Warfield, J. N. , 1974. Toward interpretation of complex structural modeling. IEEE Transactions on Systems, Man, and Cybernetics, 4 (5), 405–417.
  37. Watson, R. (1978), Interpretive structural modeling: a useful tool for technology assessment. Technology Forecast & Social Change, 11, 165–185.
Index Terms

Computer Science
Information Sciences

Keywords

Objective (Criteria) Assembly Line Balancing problem (ALBP) Dependence Power Driving Power Interpretive Structural Modeling

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