Simulation model of a stop production line: the relationship between financial return and productivity

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Bruno Miranda Santos
Taís Bisognin Garlet
Luciano Klein
Franco Silveira
Paulo Cesar Chagas Rodrigues
Wagner Bueno

Abstract

Making innovations to become competitive is not always an easy task, and in the industrial sphere, this thinking becomes even more complex. In this sense, proper use in raw material transformation processes becomes very challenging for managers, since improving processes is a condition where more can be done with less. Thus, many organizations seek to develop improvements through existing activities using a variety of techniques that are addressed in the literature, such as value flow mapping, lean production, simulations, among others. Therefore, this article aims to study and apply the computational simulation, through the use of Tecnomatix Plant Simulation © software, to obtain the best relation between financial return and productivity of a upholstery production line. In the methodology of this work was carried out the structural proposition of five scenarios. For the construction of these, a current scenario of the production line was carried out and for each new scenario, operators were added with new tasks to be performed. Although the final results show a better financial return for scenario three, the results obtained in scenario five are significant in terms of productivity indicators, although the cost with extra operators is much higher than in the other scenarios. Thus, it was clear the relevance of applying simulation in the production line, since the model assisted the managers in the decision making.

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Article Details

Section
IFLOG
Author Biographies

Bruno Miranda Santos, Universidade Federal dos Rio Grande do Sul (UFRGS)

Programa de Pós-Graduação em Engenharia de Produção da Universidade Federal do Rio Grande do Sul (UFRGS)

Taís Bisognin Garlet, Universidade Federal dos Rio Grande do Sul (UFRGS)

Programa de Pós-Graduação em Engenharia de Produção da Universidade Federal do Rio Grande do Sul (UFRGS)

Franco Silveira, Universidade Federal dos Rio Grande do Sul (UFRGS)

Programa de Pós-Graduação em Engenharia de Produção da Universidade Federal do Rio Grande do Sul (UFRGS)

Paulo Cesar Chagas Rodrigues, Instituto Federal de São Paulo (IFSP)

Professor do Instituto Federal de São Paulo (IFSP)

Wagner Bueno, Universidade Federal dos Rio Grande do Sul (UFRGS)

Programa de Pós-Graduação em Engenharia de Produção da Universidade Federal do Rio Grande do Sul (UFRGS)

References

ADULYASAK, Y.; CORDEAU, J. F.; JANS, R. (2015) The production routing problem: a review of formulations and solution algorithms. Comput Oper Res, v. 55, p. 141–152. DOI: 10.1016/j.cor.2014.01.011.

ALVES, R. T.; WANDERLEY, F. B.; FIEDLER, N. C.; NOGUEIRA, M.; OLIVEIRA, J. T. D. S.; GUIMARÃES, P. P. (2009) Otimização do layout de marcenarias no sul do espírito santo baseado em parâmetros ergonômicos e de produtividade. R. Árvore, Viçosa-MG, v. 33, n. 1, p. 161-170.

ANTONIO, K. L.; RICHARD, C. Y.; TANG, E. (2009) The complementarity of internal integration and product modularity: An empirical study of their interaction effect on competitive capabilities. Journal of Engineering and Technology Management, v. 26, n. 4, p. 305-326.

BAYOU, M. E.; DE KORVIN, A. (2008) Measuring the leanness of manufacturing systems: a case study of Ford Motor Company and General Motors. Journal of Engineering and Technology Management, v. 25, n. 4, p. 287-304.

BIAVA, I.; DAVALOS, R. V. (2014) Um estudo de modelagem e simulação de uma linha de produção de mortadela visando incorporar estratégias competitivas. XXXIV Encontro Nacional de Engenharia de Produção, Curitiba, Brasil.

CASSEL, R. A. (1996) Desenvolvimento de uma abordagem para a divulgação da simulação no setor calçadista gaúcho. Universidade Federal do Rio Grande do Sul (UFRGS) – (Dissertação de Mestrado apresentada ao Programa de Pós-Graduação em Engenharia de Produção). Porto Alegre/Brasil.

CHEN, Z. L. (2004) Integrated production and distribution operations: taxonomy, models, and review. In: SIMCHI-LEVI. D. WU, S.; SHEN, Z. J. (eds) Handbook of quantitative supply chain analysis: modeling in the e-business era, chap 17. Kluwer Acad,emic Publishers, Boston, p. 711–745.

CHEN, Z. L. (2010) Integrated production and outbound distribution scheduling: review and extensions. Oper Res, v. 58, n. 1, p. 130–148. DOI: 10.1287/opre.1080.0688.

CHWIF, L.; MEDINA, A. C. (2007) Modelagem e simulação de eventos discretos, teoria & aplicações. 2ª ed. São Paulo.

DÍAZ-MADROÑERO, M.; PEIDRO, D.; MULA, J. (2015) A review of tactical optimization models for integrated production and transport routing planning decisions. Comput Ind Eng, 88:518–535. DOI: 10.1016/j.cie.2015.06.010.

DURANIK, T.; RUŽBARSKÝ, J.; MANLIG, F. (2013) Proposal for possibilities of increasing production productivity of thermosets compression molding with using process simulation software. In Applied Mechanics and Materials, v. 308, p. 191-194.

HOVANEC, M.; PÍĽA, J.; KORBA, P.; PAČAIOVÁ, H. (2015) Plant Simulation as an Instrument of Logistics and Transport of Materials in a Digital Factory. NAŠE MORE: znanstveno-stručni časopis za more i pomorstvo, v. 62, n. 3, p. 187-192.

MALEGA, P.; KADAROVA, J.; KOBULNICKY, J. (2017) IMPROVEMENT OF PRODUCTION EFFICIENCY OF TAPERED ROLLER BEARING BY USING PLANT SIMULATION. International Journal of Simulation Modelling, v. 16, n. 4.

MIRANDA, P. L.; MORABITO, R.; FERREIRA, D. (2018) Optimization model for a production, inventory, distribution and routing problem in small furniture companies. TOP, v. 26, n. 1, p. 30-67.

MOONS, S.; RAMAEKERS, K.; CARIS, A.; ARDA, Y. (2017) Integrating production scheduling and vehicle routing decisions at the operational decision level: a review and discussion. Comput Ind Eng, v. 104, p. 224–245.

MULA, J.; PEIDRO, D.; DÍAZ-MADROÑERO, M.; VICENS, E. (2010) Mathematical programming models for supply chain production and transport planning. Eur J Oper Res, v. 204, n. 3, p. 377–390. DOI: 10.1016/j.ejor.2009.09. 008.

SARMIENTO, A. M.; NAGI, R. (1999) A review of integrated analysis of production–distribution systems. IIE Trans, v. 31, n. 11, p. 1061–1074.

SILVA, A. N.; ARAÚJO, A. V.; GODOY, L. C.; MINETTE, L. J.; SUZUK, J. A. (2017) Contribution of computational simulation for layout analysis in a wooden furniture industry. Revista Árvore, v. 41, n. 2.

SOARES, B. B. (2014) A utilização do modelo de simulação computacional para análise e modificação de um sistema de produção de pinturas automotivas. Universidade de Caxias de Sul (UCS) – (Dissertação de Mestrado apresentada ao Programa de Pós-Graduação em Engenharia Mecânica). Caxias do Sul/Brasil.

TOIVONEN, R. M. (2012) Product quality and value from consumer perspective-An application to wooden products. Journal of Forest Economics, v. 18, p. 157-73.

VIDAL, C. J.; GOETSCHALCKX, M. (1997) Strategic production–distribution models: a critical review with emphasis on global supply chain models. Eur J Oper Res, v. 98, n.1, p. 1–18.

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