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An Innovative Framework for the Simulation of Manufacturing Systems: An Application to the Footwear Industry

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Advances in Sustainable and Competitive Manufacturing Systems

Abstract

Simulation in industrial environments has been recognized as a valuable approach for capturing the different characteristics and complexity of the dynamics in industrial processes. However, there is a clear need for spreading the use of simulation tools in manufacturing companies and for simplifying the simulation modeling process. In fact this process is still highly demanding in terms of the specific skills of the modelers and in terms of the time needed to develop models that are effectively useful in actual manufacturing systems. The slow modeling process often precludes the use of simulation for facing the operational problems that rise in the day-to-day operations. This paper presents a brief overview of the use of simulation tools in manufacturing, and focus on the development of an innovative simulation framework based on libraries of components and modules. This framework will contribute for reducing the learning curve in developing simulation models for manufacturing and logistics systems. The requirements and advantages of this novel modular modeling approach are presented and discussed in the context of a case study that uses the SIMIO software for simulating the production and logistics systems of a generic footwear manufacturing system in Portugal.

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References

  1. Swain J (2011) Software survey: simulation-back to the future. ORMS-Today 38(5). http://informs.org/ORMS-Today

  2. Wenzel S, Boyaci P, Jessen U (2010) Simulation in production and logistics: trends, solutions and applications, advanced manufacturing and sustainable logistics, lecture notes in business information processing, 46, Part 1, pp 73–84

    Google Scholar 

  3. Fowler JW, Rose O (2004) Grand challenges in modeling and simulation of complex manufacturing systems. Simulation 80(9):469–476

    Article  Google Scholar 

  4. Kuehn W (2006) Digital factory: integration of simulation enhancing the product and production process towards operative control and optimization. Int J Simul 7(7):27–29

    Google Scholar 

  5. McLean C, Leong S (2001) The expanding role of simulation in future manufacturing. In: Proceedings of the 2001 winter simulation conference, pp 1478–1486

    Google Scholar 

  6. Mujica MA, Piera MA (2011) A compact timed state space approach for the analysis of manufacturing systems: key algorithmic improvements. Int J Comput Integr Manuf 24(2):135–153. Taylor & Francis

    Google Scholar 

  7. Geyer A, Scapolo F, Boden M, Dory T, Ducatel K (2003) The future of manufacturing in Europe 2015–2020: the challenge for sustainability. IPTS-EU. 2003. http://foresight.jrc.ec.europa.eu/documents/eur20705en.pdf

  8. National Research Council (NRC)/Board on Manufacturing and Engineering Design (BMED) (1998) Visionary manufacturing challenges for 2020. National Academy Press, Washington, D.C

    Google Scholar 

  9. Sterman J (2000) Business dynamics: systems thinking and modeling for a complex world. Irwin/McGraw-Hill, Boston

    Google Scholar 

  10. Wakeland WW, Gallaher EJ, Macovsky LM, Aktipis CA (2004) A comparison of system dynamics and agent-based simulation applied to the study of cellular receptor dynamics. In: Proceedings of the 37th annual Hawaii, international conference on system sciences

    Google Scholar 

  11. North MJ, Macal CM (2007) Managing business complexity discovering strategic solutions with agent-based modelling and simulation. Oxford University Press, Oxford

    Google Scholar 

  12. Banks J, Carson J, Nelson B, Nicol D (2005) Discrete-event system simulation, 4th edn. Pearson

    Google Scholar 

  13. Schriber TJ, Brunner DT (2010) Inside discrete-event simulation software: how it works and why it matters. In: Proceedings of the 2010 winter simulation conference, pp 216–229

    Google Scholar 

  14. Schriber TJ, Brunner DT (1997) Inside discrete-event simulation software: how it works and why it matters. In: Proceedings of the 1997 winter simulation conference, pp 14–22

    Google Scholar 

  15. Herrmann JW, Lin E, Ram B, Sarin S (2000) Adaptable simulation models for manufacturing. In: Proceedings of the 10th international conference on flexible automation and intelligent manufacturing, vol 2. College Park, USA, pp 989–995

    Google Scholar 

  16. Nylund H, Salminen K, Andersson P (2011) Framework for extended digital manufacturing systems. Int J Comput Integr Manuf 24(5):446–456

    Article  Google Scholar 

  17. Lohse N, Hirani H, Ratchev S, Turitto M (2006) An ontology for the definition and validation of assembly processes for evolvable assembly systems (ISATP 2005). The 6th IEEE international symposium on assembly and task planning: from nano to macro assembly and manufacturing, pp 242–247

    Google Scholar 

  18. Terkaj W, Pedrielli G, Sacco M (2012) Virtual factory data model. In: Proceedings of OSEMA 2012 workshop, 7th international conference on formal ontology in information systems, Graz, Austria, 24–27 July 2012. http://www.vff-project.eu/

  19. Cutting-Decelle AF, Michel JJ (2003) ISO 15531 MANDATE: a standardised data model for manufacturing management. Int J Comput Appl Technol 18(1/2/3/4):43–61

    Google Scholar 

  20. Scholten B (2007) The roadmap to integration: A guide to applying the ISA-95 standard in manufacturing. ISA

    Google Scholar 

  21. Core Manufacturing Simulation Data Product Development Group (2010) SISO-STD-008-2010 standard for: core manufacturing simulation data–UML model. http://www.sisostds.org/

  22. Leong SK, Lee YT, Riddick FH (2006) A core manufacturing simulation data information model for manufacturing applications. In: Proceedings of the systems interoperability standards organization 2006 fall simulation interoperability workshop

    Google Scholar 

  23. Leong SK, Johansson M, Johansson B, Lee T, Riddick FH (2008) A real world pilot implementation of the core manufacturing simulation information model. In: Proceedings of the simulation interoperability standards organization (SISO) spring 2008 SIW workshop, p 11

    Google Scholar 

  24. Johansson M, Johansson B, Skoogh A, Leong S, Riddick F, Lee YT, Shao G, Klingstam P (2007) A test implementation of the core manufacturing simulation data specification. In: Proceedings of the 2007 winter simulation conference, pp 1673–1681

    Google Scholar 

  25. Kelton W, Jeffrey Smith J, David Sturrock D (2011) Simio and simulation: modeling, analysis, applications, 2nd edn. Simio LLC, p 400

    Google Scholar 

  26. Rose-Anderssen C, Baldwin JS, Ridgway K, Boettinger F, Agyapong-Kodua K, Brencsics I, Nemeth I (2012) Application of production system classification in rapid design and virtual prototyping. In: Proceedings of the 14th international conference on modern information technology in the innovation processes of the industrial enterprises, Budapest, Hungary, 24–26 Oct 2012

    Google Scholar 

  27. APICCAPS (1993) Statistical study on footwear, components and leather goods-2011. p 237

    Google Scholar 

  28. CTCP (1993) Manual Prático de Novas Tecnologias de Produção e Organização do Sector do Calçado”. p 237

    Google Scholar 

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Acknowledgments

This research was conducted under the scope of the project Produtech PTI (n.º 13851) - New Processes and Innovative Technologies for Production Technologies (www.productech.org), partly funded by the Incentive System for Technology Research and Development in Companies (SI I&DT), under the Competitive Factors Thematic Operational Programme, of the Portuguese National Strategic Reference Framework, and EU’s European Regional Development Fund.

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Correspondence to Alexandra F. Marques .

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Marques, A.F., Mujica, M., de Sousa, J.P., Sá Marques, P., Rebelo, R., Alves, A.C. (2013). An Innovative Framework for the Simulation of Manufacturing Systems: An Application to the Footwear Industry. In: Azevedo, A. (eds) Advances in Sustainable and Competitive Manufacturing Systems. Lecture Notes in Mechanical Engineering. Springer, Heidelberg. https://doi.org/10.1007/978-3-319-00557-7_18

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  • DOI: https://doi.org/10.1007/978-3-319-00557-7_18

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