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Integration of part classification, cell formation and capacity adjustment

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Języki publikacji
EN
Abstrakty
EN
Purpose: Improving the productivity of a large manufacturing firm through development and implementation of a group technology model in a real manufacturing environment. This incorporates classification of parts, coding of parts and par families, formation of machine cells, and minimization of machine idle times through machine cell capacity adjustment. Design/methodology/approach: An algorithm has been developed for classification of all the parts into part families on the basis of manufacturing similarities. This formed 144 par families for more than 7500 different parts in production. The algorithm assigned group technology code to each part and a part family code to each part family. The former represents manufacturing characteristics of the part and the latter simplifies determination of part families. A number of machine cells were developed to produce all of the part families. After classification the system automatically directs each part to the appropriate machine cell for manufacturing. A computer software has been developed that automated the functions of classification of parts and assigning a group technology code to each part, determination of part families and assigning part family codes, and directing part families to appropriate machine cells for production. Findings: Introducing part family codes in addition to group technology codes considerably simplified the task of part family determination. Application of the system immediately resulted in an increased productivity of about 50%. This was due to the reduced setup times, less flow of parts in the workshop, production of similar parts due to parts classification, etc. Yet a productivity improvement of 100% or more is anticipated in near future. Research limitations/implications: As the manufacturing firm was producing a wide range of products at the time of implementation of this work, it was difficult to implement the project without affecting the production flow significantly. There has also been some resistance from technical people opposing a change in traditional production methods. Originality/value: Integration of machine cell formation with capacity adjustment is of great value that resulted in significant productivity improvements. Also some issues regarding actual implementation of group technology and associated problems and issues, coding of parts and part families, formation of machine cells, and capacity adjustment of machine cells have been dealt with and discussed in this paper.
Rocznik
Strony
197--203
Opis fizyczny
Bibliogr. 24 poz., rys., tabl.
Twórcy
  • School of Engineering, Edith Cowan University, Joondalup WA 6027, Australia, m.rad@ecu.edu.au
Bibliografia
  • [1] M. Spilka, A. Kania, R. Nowosielski, Integration of management systems on the chosen example, Journal of Achievements in Materials and Manufacturing Engineering 35/2 (2009) 204-210.
  • [2] M. A. Karim, A conceptual model for manufacturing performance improvement, Journal of Achievements in Materials and Manufacturing Engineering 35/1 (2009) 87-94.
  • [3] I. B. Silva, G. F. Batalha, M. Stipkovik Filho, F. Z. Ceccarelli, J. B. Anjos, M. Fesz, Integrated product and process system with continuous improvement in the auto parts industry, Journal of Achievements in Materials and Manufacturing Engineering 34/2 (2009) 204-210.
  • [4] J. Michalska-Ćwiek, Enterprise’s evaluation according to the Polish Quality Award’s criteria, Journal of Achievements in Materials and Manufacturing Engineering 36/2 (2009) 199-206.
  • [5] M. Dudek-Burlikowska, D. Szewieczek, The Poka-Yoke method as an improving quality tool of operations in the process, Journal of Achievements in Materials and Manufacturing Engineering 36/1 (2009) 95-102.
  • [6] M. Tolouei-Rad, An approach towards fully integration of CAD and CAM technologies, Journal of Achievements in Materials and Manufacturing Engineering 18 (2006) 31-36.
  • [7] T. Karkoszka, J. Honorowicz, Kaizen philosophy a manner of continuous improvement of processes and products, Journal of Achievements in Materials and Manufacturing Engineering 35/2 (2009) 197-203.
  • [8] M. Tolouei-Rad, An efficient algorithm for automatic machining sequence planning in milling operations, International Journal of Production Research 41/17 (2003) 4115-4131.
  • [9] N. Ismail, F. Musharavati, A. S. M. Hamouda, A. R. Ramli, Manufacturing process planning optimisation in reconfigurable multiple parts flow lines, Journal of Achievements in Materials and Manufacturing Engineering 31/2 (2008) 671-677.
  • [10] S. S. Heragu, Y. P Gupta, A heuristic for designing cellular manufacturing facilities, International Journal of Production Research 32/1 (1994) 125-140.
  • [11] M. Kazerooni, L. Loung, K. Abhary, A. Kazerooni, Fluency Quality: A new performance measure for evaluation of clustering techniques in cellular manufacturing system design, Proceedings of the 9th International Conference “Flexible Automation and Intelligent Manufacturing”, Tilburg, Netherlands, 1999, 357-362.
  • [12] L. Luong, J. He, K. Abhary, L. Qiu, A decision support system for cellular manufacturing system design, Computers and Industrial Engineering 42/2-4 (2002) 457-470.
  • [13] M. P. Groover, Automation, Production Systems and Computer-Integrated Manufacturing, Third Edition, Prentice Hall, 2008.
  • [14] J. L. Burbidge, J. Halsall, Group technology and growth at Shalibane, International Journal of Production Planning and Control 5/2 (1994) 213-218.
  • [15] S. Kalpakjian, S. R. Schmid, Manufaturing Enginnering and Technology, Sixth Edition, Prentice Hall, 2010.
  • [16] R. Galan, J. Racero, I. Eguia, J. M. Garcia, A systematic approach for product families formation in Reconfigurable Manufacturing Systems, Robotics and Computer-Integrated Manufacturing 23/5 (2007) 489-502.
  • [17] L. C. Guerrero, S. Lozano, D. Canca, F. Guerrero, J. Larrañeta, L. Onieva, Cell formation using sequence information and neural networks, Proceedings of the 10th International Conference “Flexible Automation and Intelligent Manufacturing”, Maryland, USA, 2000, 566-575.
  • [18] S. K. Mukhopadhyay, K. Ramesh Babu, K. V. Vijai Sai, Modified Hamiltonian chain: A graph theoretic approach to group technology, International Journal of Production Research 38/11 (2000) 2459-2470.
  • [19] E. G. John, A. Davies, A. J. Thomas, A note on 'Modified Hamiltonian chain: a graph theoretic approach to group technology' after S. K. Mukhopadhyay, K. Ramesh Babu and K. V. Vijai Sai', International Journal of Production Research 47/1 (2009) 289-298.
  • [20] S. Irani, Handbook of cellular manufacturing systems, John Wiley & Sons, New York, 1999.
  • [21] G. Jeon, H. R. Leep, Forming part families by using genetic algorithm and designing machine cells under demand change, Computers and Operations Research 33/1 (2006) 263-283.
  • [22] S. Lozano, B Adenso-Diaz, I Eguia, L Onieva, A one-step tabu search algorithm for manufacturing cell design, Journal of the Operational Research Society 50/5 (1999) 509-516.
  • [23] H. Opitz, A Classification to Describe Workpieces, Pergamon Press, Oxford, 1970.
  • [24] S. W. Lin, K. C. Ying, Z. J. Lee, Part-machine cell formation in group technology using a simulated annealing-based meta-heuristic, International Journal of Production Research 47/1 (2009) 1-13.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-article-BOS2-0022-0049
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