Application of multi-dimensional grouping to building steel stiffened shell structures

• Autorzy: Iwańkowicz R.
• Języki publikacji: EN

Abstrakty

EN

In this paper the present state of grouping technology theory is discussed. Attention is paid to lack of publications on grouping methods based on linear operators instead of classical incidence matrices. A computation algorithm for generating three-dimensional groups has been proposed. Every group contains joined structures, working cells and final (output) structures. Operation of the algorithm has been compared with results gained from literature sources dealing with binary grouping. And, calculations based on real assembly sequencing of a set of ship hull sections, have been performed.

Słowa kluczowe

EN

group technology; assembly sequencing; steel structures manufacturing

• Wydawca: Gdańsk University of Technology, Faculty of Ocean Engineering & Ship Technology
• Czasopismo: Polish Maritime Research
• Rocznik: 2013
• Tom: nr 1
• Strony: 48--58
• Opis fizyczny: Bibliogr. 19 poz., rys., tab.

Twórcy

autor

Iwańkowicz R.

• West Pomeranian University of Technology, Szczecin Faculty of Marine Technology and Transport Al. Piastów 41 71-065 Szczecin, POLAND

Bibliografia

• 1. Ballakur A., Steudel H.J.: A within-cell utilization based heuristic for designing cellular manufacturing systems. International Journal of Production Research, 25, 1987, 639–665.
• 2. Ben-Arieh D., Sreenivasav R.: Information analysis in a distributed dynamic group technology method. International Journal of Production Economics 60–61, 1999, 427–432.
• 3. Bhat M.V., Haupt A.: An efficient clustering algorithm. IEEE transactions on systems. Man and Cybernetics SMC-6 (1), 1976, 61–64.
• 4. Boctor F.F.: A linear formulation of the machine-part cell formation problem. International Journal of Production Research, 29 (2), 1991, 343–356.
• 5. Boe W.J., Cheng C.H.: A close neighbor algorithm for designing a cellular manufacturing system. International Journal of Production Research, 29 (10), 1991, 2097–2116.
• 6. Chan H.M., Milner D.A.: Direct clustering algorithm for group formation in cellular manufacture. Journal of Manufacturing Systems,1 (1), 1982, 65–75.
• 7. Chandrasekharan M.P., Rajagopalan R.: An ideal seed nonhierarchical clustering algorithm for cellular manufacturing. International Journal of Production Research, 24 (2), 1986,451-464
• 8. Cho K.-K., Sun J.-G., Oh J.-S.: An automated welding operation planning system for block assembly in shipbuilding. International Journal of Production Economics 60-61 (1), 1999, 203-209.
• 9. Groover M.P.: Fundamentals of modern manufacturing: materials, processes and systems. 4th ed., John Wiley&Sons, 2010
• 10. Hartigan J. A.: Clustering Algorithms. John Wiley & Sons Inc., 1975.
• 11. Hassan M.M.D.: Layout design in group technology manufacturing. International Journal of Production Economics, 38, 1995. 173-188.
• 12. Iwańkowicz R.: Object-matrix model of complex manufacturing technology. Industrial Management & Data Systems, 108 (8), 2008, 1131-1148.
• 13. Kitaoka M., Nakamura, R., Serizawa, S., Usuki, J.: Multivariate analysis model for machine-part cell formation problem in group technology. International Journal of Production Economics, 60–61, 1999, 433–438.
• 14. Li M.-L.: The algorithm for integrating all incidence matrices in multi-dimensional group technology. International Journal of Production Economics, 86, 2003, 121-131.
• 15. Li M.-L.: Efficiency measurement for multi-dimensional group technology. International Journal of Advanced Manufacturing Technology, 35, 2007, 621-632.
• 16. Li M.-L., Parkin R.E.: Group technology revisited: a simple and robust algorithm with enhanced capability. International Journal of Production Research, 35 (7), 1997, 1969-1992.
• 17. Min H., Shin D.: Simultaneous formation of machine and human cells in group technology: A multiple objective approach. International Journal of Production Research, 31 (1), 1993, 2307–2318.
• 18. Parkin R.E., Li M.-L.: The multi-dimensional aspects of a group technology algorithm. International Journal of Production Research, 35 (8), 1997, 2345–2358.
• 19. Tan P.-N., Steinbach M., Kumar V.: Introduction to Data Mining. Addison Wesley, 2005, 496-515.