Linear Programming for Aggregate Production Planning in a Textile Company

• Autorzy: Campo E. A. , Cano J. A. , Gómez-Montoya R. A.

Identyfikatory

DOI

10.5604/01.3001.0012.2525

Warianty tytułu

PL

Programowanie liniowe do planowania produkcji w firmie włókienniczej

• Języki publikacji: EN

Abstrakty

EN

This article aims to propose and implement an aggregated production planning model to provide optimal strategies in the medium term for a textile company, for which a linear programming model is proposed to minimise total costs associated with labour and inventory levels. The model proposed takes into account characteristics associated with fabric contraction, wastes in the process, the efficiency of new employees, and training requirements. The model is implemented and solved in GAMS, supported on an MSExcel interface, to find the optimal solution, which is to apply a hybrid strategy to the production plan, and also some strategies for improving the production process are generated.

PL

Celem pracy było zaproponowanie i wdrożenie zagregowanego modelu planowania produkcji w celu zapewnienia optymalnych strategii w perspektywie średnioterminowej dla firmy tekstylnej, dla której zaproponowano model programowania liniowego, tak aby zminimalizować całkowite koszty związane z poziomem pracy i poziomem rezerw. Zaproponowany model uwzględnia cechy związane ze skurczem tkaniny, odpadami procesowymi, wydajnością nowych pracowników i wymaganiami szkoleniowymi. W celu znalezienia optymalnego rozwiązania, które polegało na zastosowaniu strategii hybrydowej do planu produkcji, a także generowało pewne strategie usprawniania procesu produkcyjnego wdrożono model GAMS, obsługiwany w interfejsie MSExcel.

Słowa kluczowe

EN

aggregate planning; linear programming; textiles; strategies; fabrics

PL

planowanie zagregowane; programowanie liniowe; tekstylia; strategie; tkaniny

• Wydawca: Sieć Badawcza Łukasiewicz - Łódzki Instytut Technologiczny
• Czasopismo: Fibres & Textiles in Eastern Europe
• Rocznik: 2018
• Tom: Vol. 26, no. 5 (131)
• Strony: 13--19
• Opis fizyczny: Bibliogr. 23 poz., rys., tab.

Twórcy

autor

Campo E. A.

• ESACS – Escuela Superior en Administración de Cadena de Suministro, Medellín, Colombia

autor

Cano J. A.

• Universidad de Medellín, Medellín, Colombia

autor

Gómez-Montoya R. A.

• Politécnico Colombiano Jaime Isaza Cadavid, Medellín, Colombia

Bibliografia

• 1. Saricam C, Kalaoglu F, Polat S, Carrill N. Application of Godet’s Scenario Methodology to the Turkish Apparel Industry FIBRES &TEXTILES in Eastern Europe 2013; 21, 2(98): 7–12.
• 2. Cano JA, Campo EA, Gómez RA. Simulación de eventos discretos en la planificación de producción para sistemas de confección modular. Rev Técnica la Fac Ing Univ del Zulia [Internet]. 2018;41(1):50–8.
• 3. Sadeghi M, Razavi Hajiagha SH, Hashemi SS. A fuzzy grey goal programming approach for aggregate production planning. Int J Adv Manuf Technol [Internet]. Springer-Verlag; 2013 Feb 1 [cited 2018 Mar 28];64(9–12):1715–27.
• 4. Alfieri A, Tolio T, Urgo M. A project scheduling approach to production and material requirement planning in Manufacturing-to-Order environments. J Intell Manuf [Internet]. Springer US; 2012 Jun 18 [cited 2018 Mar 28];23(3):575–85.
• 5. Maropoulos PG, Bramall DG, McKay KR, Rogers B, Chapman P. An aggregate resource model for the provision of dynamic “resource-aware” planning. Proc Inst Mech Eng Part B J Eng Manuf. 2003; 217(10):1471–80.
• 6. Mezghani M, Loukil T, Aouni B. Aggregate planning through the imprecise goal programming model: integration of the manager’s preferences. Int Trans Oper Res [Internet]. Wiley/Blackwell (10.1111); 2012 Jul 1 [cited 2018 Mar 28];19(4):581–97.
• 7. Matsui M, Takahashi Y, Wang Z. A construction and theory of the manager-aided planner for collaborative demand and supply. J Japan Ind Manag Assoc [Internet]. JIMA; 2006 [cited 2018 Mar 28];57(2):120–31.
• 8. Vieira G, Ribas PC. A new multi-objective optimization method for master production scheduling problems using simulated annealing. Int J Prod Res [Internet]. Taylor & Francis Group; 2004 Nov [cited 2018 Mar 28];42(21):4609–22.
• 9. Buxey G. Aggregate planning for seasonal demand: reconciling theory with practice. Int J Oper Prod Manag [Internet]. Emerald Group Publishing Limited; 2005 Nov 11 [cited 2018 Mar 28];25(11):1083–100.
• 10. Buxey G. Strategy not tactics drives aggregate planning. Int J Prod Econ [Internet]. Elsevier; 2003 Sep 11 [cited 2018 Mar 28];85(3):331–46.
• 11. Simamora BH, Natalia D. Aggregate Planning for Minimizing Costs: A Case Study of PT XYZ in Indonesia. Int Bus Manag [Internet]. 2014 [cited 2018 Mar 28];8(6):353–6.
• 12. Ji P, Chu K. A dual-matrix approach to the transportation problem. Asia-pacific J Oper Res [Internet]. Operational Research Society of Singapore; 2002 [cited 2018 Mar 28];19(1):35–45.
• 13. Raa B, Dullaert W, Aghezzaf E-H. A matheuristic for aggregate production–distribution planning with mould sharing. Int J Prod Econ [Internet]. Elsevier; 2013 Sep 1 [cited 2018 Mar 28];145(1):29–37.
• 14. Arts J, Flapper SD. Aggregate overhaul and supply chain planning for rotables. Ann Oper Res [Internet]. 2015 Jan 18 [cited 2018 Mar 28];224(1):77–100.
• 15. Gomes da Silva C, Figueira J, Lisboa J, Barman S. An interactive decision support system for an aggregate production planning model based on multiple criteria mixed integer linear programming. Omega [Internet]. Pergamon; 2006 Apr 1 [cited 2018 Mar 28];34(2):167–77.
• 16. Corominas A, Lusa A, Olivella J. A manufacturing and remanufacturing aggregate planning model considering a non-linear supply function of recovered products. Prod Plan Control [Internet]. Taylor & Francis Group ; 2012 Feb 8 [cited 2018 Mar 28];23(2–3):194–204.
• 17. Mezghani M, Loukil T. Remanufacturing planning with imprecise quality inputs through the Goal Programming and the satisfaction functions. In: 2011 4th International Conference on Logistics [Internet]. IEEE; 2011 [cited 2018 Mar 28]. p. 122–5.
• 18. Leung J, Yu A. Quota allocation by linear programming using a spreadsheet solver. Asia-Pacific J Oper Res. 2002;19(1):63–70.
• 19. Espey RL, Balakrishnan J. A spreadsheet decision support optimization model for railcar storage at Canadian Pacific Railway. J Oper Res Soc [Internet]. Palgrave Macmillan UK; 2012 Feb 21 [cited 2018 Mar 28];63(2):139–50.
• 20. Jain A, Palekar US. Aggregate production planning for a continuous reconfigurable manufacturing process. Comput Oper Res [Internet]. Pergamon; 2005 May 1 [cited 2018 Mar 28];32(5):1213–36.
• 21. Junqueira R de ÁR, Morabito R. Um modelo de otimização linear para o planejamento agregado da produção e logística de sementes de milho. Production [Internet]. 2006 Dec [cited 2018 Mar 28];16(3):510–25.
• 22. Arango M, Cano JA, Alvarez K. Modelos de sistemas mrp cerrados integrando incertidumbre. Rev EIA [Internet]. 2012;1(18):61–76.
• 23. Płonka S, Ogiński L. Multicriterial optimisation of the manufacturing process of a spindle working in a ring spinning frame. FIBRES & TEXTILES in Eastern Europe. 2014; 22, 6(108): 51–8.

Uwagi

PL

Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2018).