1887
Volume 2013, Issue 1
  • EISSN: 2223-506X

Abstract

In this paper, a simulation optimization-based decision support tool has been developed to study the capacity enhancement scenarios in a tire manufacturing company located in Iran. This company is experiencing challenges in synchronizing production output with customer demand causing an unbalanced work-in-process (WIP) inventory distribution throughout the tire manufacturing process. However, a new opportunity to increase the supplying of raw materials by fifty percent and increase the expected growth in market demand, necessitate this study of the current company situation. This research supported by the company, is to analyze whether the ongoing production logistics system can respond to the increased market demand, considering the raw material expansion. Implementation of a proposed hybrid push/pull production control strategy, together with the facility capacity enhancement options in bottleneck stations and/or heterogeneous lines within the plant, are investigated by the proposed simulation optimization methodology.

Loading

Article metrics loading...

/content/journals/10.5339/connect.2013.13
2013-06-01
2024-03-29
Loading full text...

Full text loading...

/deliver/fulltext/connect/2013/1/connect.2013.13.html?itemId=/content/journals/10.5339/connect.2013.13&mimeType=html&fmt=ahah

References

  1. Baykoç ÖF, Erol S. Simulation modelling and analysis of a JIT production system. Int J Prod Econ. 1998 55:2:203212
    [Google Scholar]
  2. Huang M, Wang D, Ip W. Simulation study of CONWIP for a cold rolling plant. Int J Prod Econ. 1998 54:3:257266
    [Google Scholar]
  3. Lee E, Farahmand K. Simulation of a base stock inventory management system integrated with transportation strategies of a logistic network. Proceedings of the 2010 Winter Simulation Conference. 2010
    [Google Scholar]
  4. Brito TB, Silva RCS, Botter RC, Pereira NN, Medina AC. Discrete event simulation combined with multi-criteria decision analysis applied to steel plant logistics system planning. Proceedings of the 2010 Winter Simulation Conference. 2010
    [Google Scholar]
  5. Sharda B, Bury SJ. Bottleneck analysis of chemical plant using discrete event simulation. Proceedings of the 2010 Winter Simulation Conference. 2010
    [Google Scholar]
  6. Bernard JS, Tseng FT. Modeling complex manufacturing systems using simulation. Proceedings of the 1987 Winter Simulation Conference. 1987. 1
    [Google Scholar]
  7. Schroer BJ, Tseng FT. Modelling complex manufacturing systems using discrete event simulation. Comput Ind Eng. 1988 14:4:455464
    [Google Scholar]
  8. Hao Q, Shen W. Implementing a hybrid simulation model for a Kanban-based material handling system. Robotics Comput-Integrated Manuf. 2008 24:5:635646
    [Google Scholar]
  9. Sandanayake YG, Oduoza CF, Proverbs DG. A systematic modelling and simulation approach for JIT performance optimisation. Robotics Comput-Integrated Manuf. 2008 24:6:735743
    [Google Scholar]
  10. Hsieh S-J. Hybrid analytic and simulation models for assembly line design and production planning. Simul Model Pract Theory. 2002 10:1–2:87108
    [Google Scholar]
  11. Smith JS. Survey on the use of simulation for manufacturing system design and operation. J Manuf Syst. 2003 22:2:157171
    [Google Scholar]
  12. Sun Y, Shank DL, Fowler JW, Gel ES. Strategic factor-driven supply chain design for semiconductors. California J Operations Manage. 2010 8:1:3143
    [Google Scholar]
  13. Koskela L. Application of new production philosophy to the construction industry. 1992. Center for Integrated Facilities Engineering, Department of Civil Engineering, Stanford University, CA. Technical Report No. 72
  14. Law AM. Simulation Modeling and Analysis. 4th ed. New York, NY: McGraw-Hill 2006
    [Google Scholar]
  15. Chwif L, Medina A. Modeling and Simulation of Discrete Events: Theory & Practice. 2nd ed. São Paulo 2007:254
    [Google Scholar]
  16. April J, Glover F, Kelly JP, Laguna M. Practical Introduction to simulation optimization. Proceedings of the 2003 Winter Simulation Conference. 2003
    [Google Scholar]
  17. Glover F, Laguna M, Martí R. Scatter Search and Path Relinking: Foundations and Advanced Designs: Springer-Verlag 2004:8799
    [Google Scholar]
  18. Banks J, Carson JS, Nelson BL, Nicol DM. Discrete-Event System Simulation. 4th ed. Englewood Cliffs, NJ: Prentice-Hall 2009
    [Google Scholar]
  19. Howell GA. What is lean construction? Proceedings of the Seventh Annual Conference of the International Group for Lean Construction. Berkeley, CA: IGLC-7 1999:110
    [Google Scholar]
  20. Kelton WD, Sadowski RP, Swets NB. Simulation with Arena. 5th ed. New York, NY: McGraw-Hill 2010
    [Google Scholar]
http://instance.metastore.ingenta.com/content/journals/10.5339/connect.2013.13
Loading
/content/journals/10.5339/connect.2013.13
Loading

Data & Media loading...

  • Article Type: Research Article
Keyword(s): System simulation and Tire manufacturing Multi-criteria decision analysis
This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error