Advertisement

Dynamic Analysis of Inventory Policies for Improving Manufacturing Scheduling

  • Cuauhtémoc Sánchez-Ramírez
  • Miguel Rendón-Sagardi
  • Guillermo Cortes-Robles
  • Dulce Mota-López
  • Giner Alor-Hernández
Chapter

Abstract

Many researchers cite the automotive industry to study the application of Lean Manufacturing in reducing waste and improving productivity. However, in practice, the use of Lean Manufacturing techniques has spread into other industrial and service sectors, such as health and food, because of the benefits that this practice can achieve. Furthermore, different studies demonstrate that Lean Manufacturing combined with others techniques, such as simulation, produces benefits that impact on the key performance indicators of a company. Thus, in this study we analyze the combination of a simulation approach as System Dynamics on Lean Manufacturing practice in order to improve procurement policies and reduce the inventory in a livestock feed company.

Keywords

Lean manufacturing System dynamics Inventory policies 

Notes

Acknowledgments

This work was supported by the General Council of Superior Technological Education of Mexico (DGEST). Additionally, this work was sponsored by the National Council of Science and Technology (CONACYT) and the Public Education Secretary (SEP) through PROMEP.

References

  1. Al-Aomar, R. (2011). Handling multi-lean measures with simulation and simulated annealing. Journal of the Franklin Institute, 348, 1506–1522.CrossRefGoogle Scholar
  2. Abdulmalek, F. A., & Rajgopal, J. (2007). Analyzing the benefits of lean manufacturing and value stream mapping via simulation: A process sector case study. International Journal of Production Economics, 107, 223–236.CrossRefGoogle Scholar
  3. Amin, M. A., & Karim, M. A. (2012). A systematic approach to evaluate the process improvement in lean manufacturing organizations. In G. Seliger (Ed.), Sustainable manufacturing (pp. 65–70). Berlin: Springer.Google Scholar
  4. Azlina, N., Salleh, M., Kasolang, S., & Jaffar, A. (2012). Simulation of integrated total quality management (TQM) with lean manufacturing (LM) practices in forming process using Delmia Quest. Procedia Engineering, 41, 1702–1707.CrossRefGoogle Scholar
  5. Bicheno, J. (2000). The lean toolbox (2nd ed.). Buckingham: PICSIE Books.Google Scholar
  6. Chen, J. C., Cheng, C. H., & Huang, P. B. (2013). Supply chain management with lean production and RFID application: A case study. Expert Systems with Applications, 40, 3389–3397.CrossRefGoogle Scholar
  7. Demeter, K., & Matyusz, Z. (2011). The impact of lean practices on inventory turnover. International Journal of Production Economics, 133, 154–163.CrossRefGoogle Scholar
  8. Dombrowskia, U., Mielkea, T., & Engela, C. (2012). Knowledge management in lean production systems. Procedia CIRP, 3, 436–441.CrossRefGoogle Scholar
  9. Diaz-Elsayed, N., Jondral, A., Greinacher, S., Dornfeld, D., & Lanza, G. (2013). Assessment of lean and green strategies by simulation of manufacturing systems in discrete production environments. CIRP Annals-Manufacturing Technology, 62, 475–478.CrossRefGoogle Scholar
  10. Elmoselhy, S. (2013). Hybrid lean–agile manufacturing system technical facet, in automotive sector. Journal of Manufacturing Systems, 32(4), 598–619.CrossRefGoogle Scholar
  11. Eroglu, C., & Hofer, C. (2011). Lean, leaner, too lean? The inventory-performance link revisited. Journal of Operations Management, 29, 356–369.CrossRefGoogle Scholar
  12. Forrester, J. (1961). Industrial dynamics. Portland: Productivity Press.Google Scholar
  13. Ford, D. (1999). A behavioral approach to feedback loop dominance analysis system. Dynamics Review, 15, 3–36.CrossRefGoogle Scholar
  14. GröBler, A., & Schieritz, N. (2005). Of stocks, flows, agents and rules—strategic simulation in supply chain research. In H. Kotzab et al. (Eds.), Research Methodologies in Supply Chain Management (pp. 445–460). Heidelberg: Physica-Verlag.Google Scholar
  15. Hofer, C., Eroglu, C., & Hofer, A. R. (2012). The effect of lean production on financial performance: The mediating role of inventory leanness. International Journal of Production Economics, 138, 242–253.CrossRefGoogle Scholar
  16. Holweg, M. (2007). The genealogy of lean production. Journal of Operations Management, 25, 420–437.CrossRefGoogle Scholar
  17. Jurado, P. J., & Moyano, J. (2011). Lean production y gestión de la cadena de suministro en la industria aeronáutica. Investigaciones Europeas de Dirección y Economía de la Empresa, 17(1), 137–157.CrossRefGoogle Scholar
  18. Krogstie, L., & Martinsen, K. (2013). Beyond lean and six sigma; cross-collaborative improvement of tolerances and process variations—A case study. Procedia CIRP, 7, 610–615.CrossRefGoogle Scholar
  19. Morecroft, J., & Stewart, R. (2005). Explaining puzzling dynamics: A comparison the use of system dynamics and discrete event simulation. Proceedings of System Dynamics Society.Google Scholar
  20. Robinson, S., Radnor, Z. J., Burgess, N., & Worthington, C. (2012). SimLean: Utilizing simulation in the implementation of lean in healthcare. European Journal of Operational Research, 219, 188–197.CrossRefzbMATHGoogle Scholar
  21. Riezebos, J., Klingenberg, W., & Hicks, C. (2009). Lean production and information technology: Connection or contradiction? Computers in Industry, 60, 237–247.CrossRefGoogle Scholar
  22. Spear, S., & Bowen, K. H. (1999). Decoding the DNA of the Toyota production system. Harvard Business Review, 77(5), 97–106.Google Scholar
  23. Sandanayake, Y. G., Oduoza, C. F., & Proverbs, D. G. (2008). A systematic modelling and simulation approach for JIT performance optimization. Robotics and Computer-Integrated Manufacturing, 24, 735–743.Google Scholar
  24. Sterman, J. (2000). Business Dynamics: Systems Thinking and Modeling for a Complex World. Boston: Irwin McGraw-Hill.Google Scholar
  25. Sweeter, A. (1999). A comparison of system dynamics (SD) and discrete event simulation (DES). Proceedings of System Dynamics Society.Google Scholar
  26. Scholl, H. (2001). Looking across the fence: comparing finding from SD modeling efforts with those other modeling techniques. International Conference of the System Dynamics Society, Atlanta, GA: System Dynamics Society.Google Scholar
  27. Tako, A., & Robinson, S. (2009). Comparing model development in discrete event simulation and system dynamics. Proceedings of the 2009 Winter Simulation Conference.Google Scholar
  28. Voss, C. A. (1995). Alternative paradigms for manufacturing strategy. International Journal of Operations and Production Management, 15(4), 5–16.CrossRefGoogle Scholar
  29. Womack, J., Jones, D., & Roos, D. (1990). The machine that changed the world. New York: Rawson Associates.Google Scholar
  30. Watanabe, N., & Hiraki, S. (1997). A modeling approach to a JIT-based ordering system. Annals of Operations Research, 69, 379–403.CrossRefzbMATHGoogle Scholar
  31. Zhang, H., Calvo-Amodio, J., & Haapala, K. R. (2013). A conceptual model for assisting sustainable manufacturing through system dynamics. Journal of Manufacturing Systems, 32(4), 543–549.CrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Cuauhtémoc Sánchez-Ramírez
    • 1
  • Miguel Rendón-Sagardi
    • 1
  • Guillermo Cortes-Robles
    • 1
  • Dulce Mota-López
    • 1
  • Giner Alor-Hernández
    • 1
  1. 1.Division of Research and Postgraduate StudiesInstituto Tecnológico de OrizabaOrizabaMexico

Personalised recommendations