Skip to main content
SpringerLink
Log in

Dynamic Analysis of Inventory Policies for Improving Manufacturing Scheduling

  • Chapter
  • First Online:
Lean Manufacturing in the Developing World

  • 4157 Accesses

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.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 129.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 169.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  • Al-Aomar, R. (2011). Handling multi-lean measures with simulation and simulated annealing. Journal of the Franklin Institute, 348, 1506–1522.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • 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 

  • 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.

    Article  Google Scholar 

  • Bicheno, J. (2000). The lean toolbox (2nd ed.). Buckingham: PICSIE Books.

    Google Scholar 

  • 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.

    Article  Google Scholar 

  • Demeter, K., & Matyusz, Z. (2011). The impact of lean practices on inventory turnover. International Journal of Production Economics, 133, 154–163.

    Article  Google Scholar 

  • Dombrowskia, U., Mielkea, T., & Engela, C. (2012). Knowledge management in lean production systems. Procedia CIRP, 3, 436–441.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • Elmoselhy, S. (2013). Hybrid lean–agile manufacturing system technical facet, in automotive sector. Journal of Manufacturing Systems, 32(4), 598–619.

    Article  Google Scholar 

  • Eroglu, C., & Hofer, C. (2011). Lean, leaner, too lean? The inventory-performance link revisited. Journal of Operations Management, 29, 356–369.

    Article  Google Scholar 

  • Forrester, J. (1961). Industrial dynamics. Portland: Productivity Press.

    Google Scholar 

  • Ford, D. (1999). A behavioral approach to feedback loop dominance analysis system. Dynamics Review, 15, 3–36.

    Article  Google Scholar 

  • 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 

  • 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.

    Article  Google Scholar 

  • Holweg, M. (2007). The genealogy of lean production. Journal of Operations Management, 25, 420–437.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • 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 

  • 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.

    Article  MATH  Google Scholar 

  • Riezebos, J., Klingenberg, W., & Hicks, C. (2009). Lean production and information technology: Connection or contradiction? Computers in Industry, 60, 237–247.

    Article  Google Scholar 

  • Spear, S., & Bowen, K. H. (1999). Decoding the DNA of the Toyota production system. Harvard Business Review, 77(5), 97–106.

    Google Scholar 

  • 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 

  • Sterman, J. (2000). Business Dynamics: Systems Thinking and Modeling for a Complex World. Boston: Irwin McGraw-Hill.

    Google Scholar 

  • Sweeter, A. (1999). A comparison of system dynamics (SD) and discrete event simulation (DES). Proceedings of System Dynamics Society.

    Google Scholar 

  • 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 

  • Tako, A., & Robinson, S. (2009). Comparing model development in discrete event simulation and system dynamics. Proceedings of the 2009 Winter Simulation Conference.

    Google Scholar 

  • Voss, C. A. (1995). Alternative paradigms for manufacturing strategy. International Journal of Operations and Production Management, 15(4), 5–16.

    Article  Google Scholar 

  • Womack, J., Jones, D., & Roos, D. (1990). The machine that changed the world. New York: Rawson Associates.

    Google Scholar 

  • Watanabe, N., & Hiraki, S. (1997). A modeling approach to a JIT-based ordering system. Annals of Operations Research, 69, 379–403.

    Article  MATH  Google Scholar 

  • 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.

    Article  Google Scholar 

Download references

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.

Author information

Authors and Affiliations

  1. Division of Research and Postgraduate Studies, Instituto Tecnológico de Orizaba, Av. Oriente 9, No. 852, Orizaba, Veracruz, Mexico

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

Authors
  1. Cuauhtémoc Sánchez-Ramírez
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Miguel Rendón-Sagardi
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Guillermo Cortes-Robles
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Dulce Mota-López
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Giner Alor-Hernández
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Cuauhtémoc Sánchez-Ramírez .

Editor information

Editors and Affiliations

  1. Departamento de Ingeniería Industrial y Manufactura, Instituto de Ingeniería y Tecnología Universidad Autónoma de Ciudad Juárez, Chihuahua, Mexico

    Jorge Luis García-Alcaraz

  2. Avenue Del Charro, Autonomous University of Ciudad Juarez, Chihuahua, Mexico

    Aidé Aracely Maldonado-Macías

  3. Institute of Technology of Orizaba Av. Instituto Tecnologico, Orizaba, Mexico

    Guillermo Cortes-Robles

Rights and permissions

Reprints and permissions

Copyright information

© 2014 Springer International Publishing Switzerland

About this chapter

Cite this chapter

Sánchez-Ramírez, C., Rendón-Sagardi, M., Cortes-Robles, G., Mota-López, D., Alor-Hernández, G. (2014). Dynamic Analysis of Inventory Policies for Improving Manufacturing Scheduling. In: García-Alcaraz, J., Maldonado-Macías, A., Cortes-Robles, G. (eds) Lean Manufacturing in the Developing World. Springer, Cham. https://doi.org/10.1007/978-3-319-04951-9_27

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-04951-9_27

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-04950-2

  • Online ISBN: 978-3-319-04951-9

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation