Mathematical model for dynamic cell formation in fast fashion apparel manufacturing stage
الموضوعات :
Gayathri Perera
1
(Department of Textile and Clothing Technology, University of Moratuwa, Moratuwa, Sri Lanka)
Vijitha Ratnayake
2
(Department of Textile and Clothing Technology, University of Moratuwa, Moratuwa, Sri Lanka)
الکلمات المفتاحية: Dynamic cell . Labor, intensive . Apparel . Product layout . Changeover . Cost saving,
ملخص المقالة :
This paper presents a mathematical programming model for dynamic cell formation to minimize changeover-related costs (i.e., machine relocation costs and machine setup cost) and inter-cell material handling cost to cope with the volatile production environments in apparel manufacturing industry. The model is formulated through findings of a comprehensive literature review. Developed model is validated based on data collected from three different factories in apparel industry, manufacturing fast fashion products. A program code is developed using Lingo 16.0 software package to generate optimal cells for developed model and to determine the possible cost-saving percentage when the existing layouts used in three factories are replaced by generated optimal cells. The optimal cells generated by developed mathematical model result in significant cost saving when compared with existing product layouts used in production/assembly department of selected factories in apparel industry. The developed model can be considered as effective in minimizing the considered cost terms in dynamic production environment of fast fashion apparel manufacturing industry. Findings of this paper can be used for further researches on minimizing the changeover-related costs in fast fashion apparel production stage.
Aft LS (2000) Work measurement and methods improvement, vol 9. Wiley, Hoboken
Agrawal AK, Bhardwaj P, Kumar R, Sharma S (2015) Particle swarm optimization for natural grouping in context of group technology application. In: 2015 international conference on IEEE industrial engineering and operations management (IEOM), pp 1–8
Anbumalar V, Raja Chandra Sekar M (2015) Methods for solving cell formation, static layout and dynamic layout cellular manufacturing system problems: a review. Asian J Sci Technol 6(12):2107–2112
Asgharpour MJ, Javadian N (2004) Solving a stochastic cellular manufacturing model by using genetic algorithms. Int J Eng Trans A 17:145–156
Aus R (2011) Trash to trend – using upcycling in fashion design. Retrieved from: http://vana.artun.ee/popFile.php?id=2269
Azadeh A, Moghaddam M, Nazari-Doust B, Jalalvand F (2015) Fuzzy and stochastic mathematical programming for optimisation of cell formation problems in random and uncertain states. Int J Oper Res 22(2):129–147
Badiger S, Laxman R (2013) Total quality management and organisation development. Int J Bus Manag Invent 2(7):34–37
Badiru AB (2013) Handbook of industrial and systems engineering. CRC Press, Boca Raton
Bagheri M, Bashiri M (2014) A new mathematical model towards the integration of cell formation with operator assignment and intercell layout problems in a dynamic environment. Appl Math Model 38(4):1237–1254
Balakrishnan J, Hung Cheng C (2005) Dynamic cellular manufacturing under multiperiod planning horizons. J Manuf Technol Manag 16(5):516–530
Bayram H, S¸ ahin R (2016) A comprehensive mathematical model for dynamic cellular manufacturing system design and Linear Programming embedded hybrid solution techniques. Comput Ind Eng 91:10–29
Bhardwaj V, Fairhurst A (2009) Fast fashion: response to changes in the fashion industry. Int Rev Retail Distrib Consum Res
20(1):165–173
Cachon GP, Swinney R (2011) The value of fast fashion: quick response, enhanced design, and strategic consumer behavior. Manag Sci 57(4):778–795
Caro F, Martı´nez-de-Albe´niz V (2015) Fast fashion: business model overview and research opportunities. In: Agrawal N, Smith S (eds) Retail supply chain management. Springer, Boston, pp 237–264
Case K, Newman ST (eds) (2004) Advances in manufacturing technology VIII: proceedings of the 10th national conference on manufacturing research. CRC Press, Boca Raton
Chang CC, Wu TH, Wu CW (2013) An efficient approach to determine cell formation, cell layout and intracellular machine
sequence in cellular manufacturing systems. Comput Ind Eng 66(2):438–450
Chary SN (1988) Production and operations management. Tata McGraw-Hill, New York
Cheng TC, Podolsky S (1996) Just-in-time manufacturing: an introduction. Springer, Berlin
Chowdary BV, Slomp J, Suresh NC (2005) A new concept of virtual cellular manufacturing. West Indian J Eng 28(1):45–60
Chung SH, Wu TH, Chang CC (2011) An efficient tabu search algorithm to the cell formation problem with alternative routings and machine reliability considerations. Comput Ind Eng 60(1):7–15
Curry GL, Feldman RM (2010) Manufacturing systems modeling and analysis. Springer, Berlin, pp 117–128
Dalfard VM (2013) New mathematical model for problem of dynamic cell formation based on number and average length of intra and intercellular movements. Appl Math Model 37(4):1884–1896
De Carlo F, Arleo MA, Borgia O, Tucci M (2013) Layout design for a low capacity manufacturing line: a case study. Int J Eng Bus Manag 5:35
Deep K, Singh PK (2015) Design of robust cellular manufacturing system for dynamic part population considering multiple processing routes using genetic algorithm. J Manuf Syst 35:155–163
Deep K, Singh PK (2016) Dynamic cellular manufacturing system design considering alternative routing and part operation tradeoff using simulated annealing based genetic algorithm. Sadhana 41(9):1063–1079
Duncan WP (2011) Methods for reducing changeover times through scheduling. University of Rhode Island, Kingston
Egilmez G, Su¨er GA, Huang J (2012) Stochastic cellular manufacturing system design subject to maximum acceptable risk level. Comput Ind Eng 63(4):842–854
Elavia S (2014) How the lack of copyright protections for fashion designs affects innovation in the fashion Industry. Senior Theses, Trinity College, Hartford
Esmailnezhad B, Fattahi P, Kheirkhah AS (2015) A stochastic model for the cell formation problem considering machine reliability. J Ind Eng Int 11(3):375–389
Forghani K, Mohammadi M, Ghezavati V (2013) Designing robust layout in cellular manufacturing systems with uncertain
demands. Int J Ind Eng Comput 4(2):215–226
Giri PK, Moulick SK (2016) Comparison of cell formation techniques in cellular manufacturing using three cell formation algorithms. Int J Eng Res Appl 6(1):98–101
Guo ZX, Ngai EWT, Yang C, Liang X (2015) An RFID-based intelligent decision support system architecture for production
monitoring and scheduling in a distributed manufacturing environment. Int J Prod Econ 159:16–28
Hachicha W, Masmoudi F, Haddar M (2006) Principal component analysis model for machine-part cell formation problem in group technology. In: The international conference on advances in mechanical engineering and mechanics (ICAMEM 2006)
Hamedi M, Esmaeilian GR, Ismail N, Ariffin MKA (2012) Capability-based virtual cellular manufacturing systems formation in dual-resource constrained settings using Tabu Search. Comput Ind Eng 62(4):953–971
Heizer J (2016) Operations management, 11/e. Pearson Education India, Noida
Houshyar AN, Leman Z, Moghadam HP, Ariffin MKAM, Ismail N, Iranmanesh H (2014) Literature review on dynamic cellular manufacturing system. In: IOP conference series: materials science and engineering, vol 58, No. 1, p. 012016. IOP
Publishing
Ireland F, Dale BG (2001) A study of total productive maintenance implementation. J Qual Maint Eng 7(3):183–192
Islam I, Rahman MF, LeHew ML (2015) Predicting total assembling time for different apparel products utilizing learning curve and time study approaches: a comparative case study. In: International Textile and Apparel Association (ITAA) Annual Conference Proceedings 110
Johnson DJ (2003) A framework for reducing manufacturing throughput time. J Manuf Syst 22(4):283
Jovanovic VM, Mann M, Katsioloudis PJ, Dickerson DL (2014) Enabling multidisciplinary perspective in student design project: fast fashion and sustainable manufacturing systems. Paper presented at 2014 ASEE annual conference & exposition, Indianapolis, Indiana. https://peer.asee.org/20370
Kahraman C (2012) Computational intelligence systems in industrial engineering: with recent theory and applications. Springer, Berlin, pp 505–508
Kannan B (2011) Reliability/availability of manufacturing cells and transfer lines (Doctoral dissertation, Auburn University)
Karger DW, Bayha FH (1987) Engineered work measurement: the principles, techniques, and data of methods-time measurement background and foundations of work measurement and methodstime measurement, plus other related material. Industrial Press Inc., New York
Kasimbeyli R, Dincer C, Ozpeynirci S (2010) Sub-gradient based solution approach for cell formation problem with alternative routes. In: International conference 24th mini EURO conference ‘‘continuous optimization and information-based technologies in the financial sector’’ (MEC EurOPT 2010), June 23–26, 2010, Izmir, Turkey
Kentli A, Dal V, Alkaya AF (2013) Minimizing machine changeover time in product line in an apparel industry. J Text Appar/Tekst Konfeks 23(2):159–167
Khannan MSA, Maruf A, Wangsaputra R, Sutrisno S, Wibawa T, (2016) Cellular manufacturing system with dynamic lot size
material handling. In: IOP conference series: materials science and engineering, vol 114, No 1, p 012144. IOP Publishing
Kia R, Shirazi H, Javadian N, Tavakkoli-Moghaddam R (2013) A multi-objective model for designing a group layout of a dynamic cellular manufacturing system. J Ind Eng Int 9(1):8
Kumar SA, Suresh N (2006) Production and operations management. New Age International, New Delhi
Kumar PG, Moulick SK (2016) Comparison of cell formation techniques in cellular manufacturing using three cell formation algorithms. Int J Eng Res Appl 6(1):98–101 (Part - 5)
Lago A, Martinez-de-Albeniz V, Moscoso P, Vall A (2013) The role of quick response in accelerating sales of fashion goods.
Retrieved from: http://webprofesores.iese.edu/valbeniz/RoleQRFashion_web.pdf. Accessed 27 Feb 2014
Leflar J (2001) Practical TPM. Productivity Press, Portland Mahdavi I, Aalaei A, Paydar MM, Solimanpur M (2010) Designing a mathematical model for dynamic cellular manufacturing systems considering production planning and worker assignment. Comput Math Appl 60(4):1014–1025
Mahdavi I, Teymourian E, Baher NT, Kayvanfar V (2013) An integrated model for solving cell formation and cell layout
problem simultaneously considering new situations. J Manuf Syst 32(4):655–663
Malakooti B (2014) Operations and production systems with multiple objectives. Wiley, Hoboken
Marsh RF, Meredith JR, McCutcheon DM (1997) The life cycle of manufacturing cells. Int J Oper Prod Manag 17(12):1167–1182
Memic M, Minhas FN (2011) The fast fashion phenomenon: luxury fashion brands responding to fast fashion. The Swedish School of Textiles April.
Mihm B (2010) Fast fashion in a flat world: global sourcing strategies. The International Business & Economics Research Journal 9(6):55
Mir MSS, Rezaeian J (2016) A robust hybrid approach based on particle swarm optimization and genetic algorithm to minimize the total machine load on unrelated parallel machines. Appl Soft Comput 41:488–504
Mital A, Desai A, Mital A (2017) Fundamentals of work measurement: what every engineer should know. CRC Press, Boca Raton Mittlehauser M (1997) Employment trends in textiles and apparel, 1973–2005. Monthly Labor Review, August, 1997, pp 24–35
Mo Z (2015) Internationalization process of fast fashion retailers: evidence of H&M and Zara. Int J Bus Manag 10(3):217
Modra´k V (2011) Operations management research and cellular manufacturing systems: innovative methods and approaches: innovative methods and approaches. IGI Global, Hershey
Moll P, Schu¨tte U, Zo¨ll K, Molfino R, Carca E, Zoppi M, Montorsi R (2009) Automated garment assembly and manufacturing simulation. In: Walter L, Kartsounis GA, Carosio S (eds) Transforming clothing production into a demand-driven, knowledge-based, high-tech industry. Springer, London, pp 9–59
Moradgholi M, Paydar MM, Mahdavi I, Jouzdani J (2016) A genetic algorithm for a bi-objective mathematical model for dynamic virtual cell formation problem. J Ind Eng Int 12(3):343–359
Moretta Tartaglione A, Antonucci E (2013) Value creation process in the fast fashion industry: towards a networking approach. In: The 2013 Naples Forum on Service. Service Dominant Logic, Networks & Systems Theory and Service Science: Integrating Three Perspectives for a New Service Agenda, p 91
Mungwattana A (2000) Design of cellular manufacturing systems for dynamic and uncertain production requirements with presence of routing flexibility (Doctoral dissertation)
Neumann CSR, Fogliatto FS (2013) Systematic approach to evaluating and improving the flexibility of layout in dynamic
environments. Manag Prod 20(2):235–254
Niakan F (2015) Design and configuration of sustainable dynamic cellular manufacturing systems (Doctoral dissertation, Lyon, INSA)
Niakan F, Baboli A, Moyaux T, Botta-Genoulaz V (2016) A biobjective model in sustainable dynamic cell formation problem with skill-based worker assignment. J Manuf Syst 38:46–62
Nouri H (2016) Development of a comprehensive model and BFO algorithm for a dynamic cellular manufacturing system. Appl Math Model 40(2):1514–1531
Nouri HA, Leman Z, Moghadam HP, Sulaiman R (2014) Literature review on machine reliability in cellular manufacturing system. Am J Appl Sci 11(12):1964–1968
Nunkaew W, Phruksaphanrat B (2013) Effective fuzzy multi-objective model based on perfect grouping for manufacturing cell formation with setup cost constrained of machine duplication. Songklanakarin J Sci Technol 35(6):715–726
Orcao AIE, Pe´rez DR (2014) Global production chains in the fast fashion sector, transports and logistics: the case of the Spanish retailer Inditex. Investigaciones Geogra´ficas, Boletı´n del Instituto de Geografı´a 2014(85):113–127
Pillai VM, Hunagund IB, Krishnan KK (2011) Design of robust layout for dynamic plant layout problems. Comput Ind Eng
61(3):813–823
Pinheiro RG, Martins IC, Protti F, Ochi LS, Simonetti LG, Subramanian A (2016) On solving manufacturing cell formation
via Bicluster Editing. Eur J Oper Res 254(3):769–779
Rafiei H, Ghodsi R (2013) A bi-objective mathematical model toward dynamic cell formation considering labor utilization. Appl Math Model 37(4):2308–2316
Rajput RK (2007) A textbook of manufacturing technology: manufacturing processes. Firewall Media, New Delhi
Rodriguez Leon J, Quiroga Me´ndez JE, Ortiz Pimiento NR (2013) Performance comparison between a classic particle swarm optimization and a genetic algorithm in manufacturing cell design. Dyna 80(178):29–36
Sabet E, Sabet E, Yazdani N, Yazdani N, De Leeuw S, De Leeuw S (2017) Supply chain integration strategies in fast evolving
industries. Int J Logist Manag 28(1):29–46
Sakhaii M, Tavakkoli-Moghaddam R, Bagheri M, Vatani B (2016) A
robust optimization approach for an integrated dynamic cellular manufacturing system and production planning with unreliable machines. Appl Math Model 40(1):169–191
Saxena L, Jain P (2011) Dynamic cellular manufacturing systems design—a comprehensive model. Int J Adv Manuf Technol 53:11–34. https://doi.org/10.1007/s00170-010-2842-9
Seifoddini S, Djassemi M (2001) The effect of reliability consideration on the application of quality index. Comput Ind Eng
40:65–77. https://doi.org/10.1016/S0360-8352(00)00072-3
Shafigh F, Defersha FM, Moussa SE (2017) A linear programming embedded simulated annealing in the design of distributed layout with production planning and systems reconfiguration. Int J Adv Manuf Technol 88(1–4):1119–1140
Shen B (2014) Sustainable fashion supply chain: lessons from H&M. Sustainability 6(9):6236–6249
Su¨er GA, Dagli C (2005) Intra-cell manpower transfers and cell loading in labor-intensive manufacturing cells. Comput Ind Eng 48(3):643–655
Su¨er GA, Huang J, Maddisetty S (2010) Design of dedicated, shared and remainder cells in a probabilistic demand environment. Int J Prod Res 48(19):5613–5646
Suresh NC, Kay JM (eds) (2012) Group technology and cellular manufacturing: a state-of-the-art synthesis of research and
practice. Springer, Berlin
Tavakkoli-Moghaddam R et al (2011) Solving a new bi-objective model for a cell formation problem considering labor allocation by multi-objective particle swarm optimization. Int J Eng Trans A Basics 24(3):249
Vecchi A, Buckley C (2016) Handbook of research on global fashion management and merchandising. IGI Global
Yadollahi MS et al (2014) Design a bi-objective mathematical model for cellular manufacturing systems considering variable failure rate of machines. Int J Prod Res 52(24):7401–7415
Zhao, L. and Yang, J. (2011) Clothing workshop production line analysis and improvement research based on IE. In: Advanced material research, vol 291–294, pp 3147–3151. Trans Tech
Publications, Switzerland
Zhelyazkov G (2011) Agile supply chain: Zara’s case study analysis. Design, manufacture & engineering management. Strathclyde University Glasgow, Velika Britanija, pp 2–11
Zhenxiang W, Lijie Z (2011) Case study of online retailing fast fashion industry. Int J e-Educ e-Bus e-Manag e-Learn 1(3):195
Zohrevand AM, Rafiei Hamed, Zohrevand AH (2016) Multi-objective dynamic cell formation problem: a stochastic programming approach. Comput Ind Eng 98:323–332
