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Jayachitra, R.
- Design and Selection of Facility Layout Using Simulation and Design of Experiments
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1 Department of Mechanical Engineering, PSG College of Technology, Coimbatore-641004, IN
1 Department of Mechanical Engineering, PSG College of Technology, Coimbatore-641004, IN
Source
Indian Journal of Science and Technology, Vol 3, No 4 (2010), Pagination: 437-446Abstract
In the global industrial competition, layout design and planning is becoming more and more critical due to shorter product life cycles and highly dynamic demand conditions. In this context, traditional layouts such as product and process/functional layouts are considered inferior. Cellular layouts have been proposed as an alternative to these layouts but they need a complete reallocation of resources, which consumes time and money. Hence, it is necessary to verify the performance measures before the design and selection of a certain type of layout. In this context, this paper makes an attempt to study the suitability of a virtual cellular layout (VCL) along with an existing functional layout (FL) of an industry and a classical cellular layout (CL), if considered for implementation. A Genetic algorithm (GA) based intra-cell formation procedure is used in the cellular layout design. To identify the suitability of a particular layout in a given environment, a typical manufacturing system is modeled using the WITNESS 2006 simulation software. Design of experiments (DOE) is used to plan the simulation experiments. The performance of each of the three layouts is analyzed statistically by means of operational parameters such as machine utilization, throughput, average distance traveled by parts and average work-in-process. The results from the simulation experiments indicate that the performance of virtual cellular manufacturing falls between that of functional and cellular manufacturing. Also, we find that the performance of a virtual cellular layout is often relatively superior to that of a functional layout and marginally inferior to a cellular layout.Keywords
Functional Layout, Cellular Layout, Virtual Cellular Layout, Genetic Algorithm, SimulationReferences
- Adil GK and Rajamani D (2000) The trade-off between intra-cell and inter-cell moves in group technology cell formation. J. Manufac. Sys.19(5), 305-317.
- Ahi A, Aryanezhad MB, Ashtiani B and Makui A (2009) A novel approach to determine cell formation, intracellular machine layout and cell layout in the CMS problem based on Topsis method. Computers Opera. Res. 36(5), 1478-1496.
- Babu A, Nandurkar KN and Thomas A (2000) Development of virtual cellular manufacturing systems for SMEs. Int. J. Logistics Information Management. 13(4), 228-242.
- Balakrishnan J and Hung Cheng C (2007) Multi-period planning and uncertainty issues in cellular manufacturing: A review and future directions. European J Operational Res. 177(1), 281-309.
- Baykssoglu A and Gindy N (2000) MOCACEF 1.0: Multiple objective capability based approach to form part-machine groups for cellular manufacturing application. Int. J. Production Res. 38(5), pp1133–1161.
- Chandrasekharan MP and Rajagopalan R (1986a) An ideal seed non-hierarchical clustering algorithm for cellular manufacturing. Int. J. Production Res. 24(2), 451-464.
- Chandrasekharan MP and Rajagopalan R (1986b) MODROC: an extension of rank order clustering for group technology. Int. J. Production Res. 24(5), 1221-1233.
- Deb S and Bhattacharyya B (2005) Fuzzy decision support system for manufacturing facilities layout planning. Dec. Support Sys. 40(2), 305 –314.
- Drolet JR, Montreuil B and Moodie CL (1990) Virtual cellular manufacturing layout planning. Int. Industrial Engg. Conf. Proc. pp236–241.
- Drolet JR, Montreuil B and Moodie CL (1995) Scheduling framework for virtual cellular manufacturing. Int. J. Manufac. Sys. Design. 1( 4), 351–365.
- Drolet JR, Moodie CL and Montreuil B (1989) Scheduling factories of the future. Int. J. Mech. Work. Technol. 20, 183-194.
- Durán O, Rodriguez N and Consalter LA (2010) Collaborative particle swarm optimization with a data mining technique for manufacturing cell design. Int. J. Expert Sys. Appl. 37(2), 1563-1567.
- Flynn BB and Jacobs FR (1987) Applications and Implementation: An experimental comparison of cellular (group technology layout with process layout. Decision Sci. 18(4), 562- 581.
- Greene TJ and Sadowski PR (1984) A review of cellular manufacturing assumptions, advantages and design techniques. J. Operations Management. 4(2), 85–97.
- Harhalakis G, Proth JM and Xie XL (1990) Manufacturing cell design using simulated annealing: An industrial application. J. Intelligent Manufacturing. 1(3), 185-191.
- Hyer N and Wemmerlöv U (2002) Reorganizing the factory: Competing through cellular manufacturing. Productivity press, Portland, OR.
- Irani SA, Cavalier TM and Cohen PH (1993) Virtual manufacturing cells: exploiting layout design and inter-cellular flows for the machine sharing problem. Int. J. Production Res. 31(4), 791–810.
- Kanan VR and Ghosh S (1996) Cellular manufacturing using virtual cells. Int. J. Operations Production Management. 16(5), 99–112.
- Kaparthi S and Suresh NC (1994) Performance of selected part-machine grouping techniques for data sets of wide ranging sizes and imperfection. Decision Sci. 25(4), 515-539.
- Kesen SE, Toksari MD, Güngör Z and Güner E (2009) Analyzing the behaviors of virtual cells (VCs) and traditional manufacturing systems: Ant colony optimization (ACO)-based meta models. Computers Operations Res. arch. 36(7), 2275-2285.
- King JR (1980) Machine-component grouping in production flow analysis: an approach using a rank order clustering algorithm. Int. J. Production Res. 18(2), 213 – 232.
- Luong LHS, Hsu HY, Rae T and Kubank D (1997) Applications of cellular manufacturing for batch production: A case study. Proc. of the world congress on Manufac. Technol. Cairns, Australia. pp117-124.
- Mahmoodi F, Dooley KJ and Starr PJ (1990) An investigation of dynamic group scheduling heuristics. Int. J. Production Res. 28(9), 1695-711.
- Mak KL, Peng P, Wang XX and Lau TL (2007) An ant colony optimization algorithm for scheduling virtual cellular manufacturing systems. Int. J. Computer Integrated Manufac. 20(6), 524 – 537.
- McLean CR, Bloom HM and Hopp TH (1982) The virtual manufacturing cell. Proc. of 4th IFAC/IFIP conf. on information control problems in manufac. Technol. pp105–111.
- Morris JS and Tersine RJ (1990) A simulation analysis of factors influencing the attractiveness of group technology cellular layouts. Management Sci. 36(12), 1567-78.
- Nomden G and van der Zee DJ (2008) Virtual cellular manufacturing: Configuring routing flexibility. Int. J. Production Economics. 112(1), 439 – 451.
- Peng YF, Guan ZL, Ma l, Zhang CY and Li PG (2009) A two-stage mathematical approach for the design of virtual manufacturing cells. Int. J. Mechatronics Manufac. Sys. 2(1/2), 80 – 96.
- Rajamani D, Singh N and Aneja Y (1990) Integrated design of cellular manufacturing systems in the presence of alternatives process plans. Int. J. Production Res. 28(8), 1541-1554.
- Rajamani D, Singh N and Aneja Y (1996) Design of cellular manufacturing systems. Int. J. Production Res. 34(7), 1917–1928.
- Saad SM and Lassila AM (2006) An integrated approach for shop floor configuration in fractal manufacturing systems. Int. J. Services Operations Management. 2(2), 109 –123.
- Schaller J (2005) Tabu search procedures for the cell formation problem with intra-cell transfer costs as a function of cell size. Computers Industrial Engg. 49(3), 449 - 462.
- Shiba S, Graham A and Walden D (1993) A new American TQM, four practical revolutions in management, Portland, OR, Productivity press.
- Sofianopoulou S (2010) Formation of manufacturing cells in group technology using a genetic algorithm approach. Int. J. Industrial Sys. Engg. 5(2), 212–225.
- Song S and Hitomi K (1992) Group technology cell formation for minimizing the inter-cell parts flow. Int. J. Production Res. 30(12), 2737–2753.
- Souilah A, Mecheri Y and Bennesroune A (1996) Intra-cell layout design: a combinatorial optimisation approach. Int. conf. on new information technologies in education. Minsk, pp123-130.
- Srinivasan G, Narendran TT and Mahadevan B (1990) An assignment model for the part-families problem in group technology. Int. J. Production Res. 28(1), 145-52.
- Stanfel LE (1989) A successive approximations method for a cellular manufacturing problem. Ann. Operations Res. 17(1), 13-30
- Suresh NC (1992) Partitioning work centers for group technology: analytical extension and shop level simulation investigation. Decision Sci. 23(2), 267-290.
- Vakharia AJ and Wemmerlöv U (1990) Designing a cellular manufacturing system: a material flow approach based on operation sequences. IIE Trans. 22(1), 84-97.
- Venugopal V and Narendran TT (1992) A genetic algorithm approach to the machine-component grouping problem with multiple objectives. Computers Industrial Engg. 22(4), 469-480.
- Waterson PE, Clegg CW, Bolden R, Pepper K, Warr PB and Wall TD (1999) The use and effectiveness ofmodern manufacturing practices: A survey of UK industry. Int. J. Production Res. 37(10), 2271–2292.
- Wei NC and Mejabi OO (2008) A clustering approach for minimizing inter-cell trips in cell formation. J. Intelligent Manufac. 19(1), 13-20.
- Wemmerlöv U and Danny Jonson J (2004) Why does cell implementation stop? Factors influencing cell penetration in manufacturing plants. Production Operations Management. 13(3), 272–289.