Journal of Korean Society of Industrial and Systems Engineering (산업경영시스템학회지)

Society of Korea Industrial and System Engineering (한국산업경영시스템학회)
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Simulation Modeling for Production Scheduling under Make-To-Order Production Environment : Focusing on the Flat Glass Production Environment

주문생산 방식의 생산계획 수립을 위한 시뮬레이션 모델 설계 : 판유리 제조 공정을 중심으로

  • Choi, Yong-Hee (Department of Management Consulting, Hanyang University) ;
  • Hwang, Seung-June (Department of Business Administration, Hanyang University ERICA)
  • 최용희 (한양대학교 일반대학원 경영컨설팅학과) ;
  • 황승준 (한양대학교 경상대학 경영학부)
  • Received : 2019.02.18
  • Accepted : 2019.03.19
  • Published : 2019.03.31
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Abstract

The manufacturing companies under Make-To-Order (MTO) production environment face highly variable requirements of the customers. It makes them difficult to establish preemptive production strategy through inventory management and demand forecasting. Therefore, the ability to establish an optimal production schedule that incorporates the various requirements of the customers is emphasized as the key success factor. In this study, we suggest a process of designing the simulation model for establishing production schedule and apply this model to the case of a flat glass processing company. The flat glass manufacturing industry is under MTO production environment. Academic research of flat glass industry is focused on minimizing the waste in the cutting process. In addition, in the practical view, the flat glass manufacturing companies tend to establish the production schedule based on the intuition of production manager and it results in failure of meeting the due date. Based on these findings, the case study aims to present the process of drawing up a production schedule through simulation modeling. The actual data of Korean flat glass processing company were used to make a monthly production schedule. To do this, five scenarios based on dispatching rules are considered and each scenario is evaluated by three key performance indicators for delivery compliance. We used B2MML (Business To Manufacturing Markup Language) schema for integrating manufacturing systems and simulations are carried out by using SIMIO simulation software. The results provide the basis for determining a suitable production schedule from the production manager's perspective.

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References

  1. Arbib, C. and Marinelli, F., An Optimiztion Model for Trim Loss Minimization in an Automotive Glass Plant, European Journal of Operational Research, 2007, Vol. 183, No. 3, pp. 1421-1432. https://doi.org/10.1016/j.ejor.2005.07.034
  2. Beamon, B.M., Measuring Supply Chain Performance, International Journal of Operations & Production Management, 1999, Vol. 19, No. 3, pp. 275-292. https://doi.org/10.1108/01443579910249714
  3. Dyson, R.G. and Gregory, A.S., The Cutting Stock Problem in the Flat Glass Industry, Journal of the Operational Research Society, 1974, Vol. 25, No. 1, pp. 41-53. https://doi.org/10.1057/jors.1974.5
  4. He, D., Lobov, A., and Lastra, J.M., ISA-95 Tool for Enterprise Modeling, Proceeding of ICONS, 2012, pp. 83-87.
  5. Kelton, W.D., Smith, J.S., and Sturrock, D.T., Simio and Simulation : Modeling, Analysis, Applications, Learning Solutions, 2011.
  6. Kwon, K.J., Hong, S.D., and Kim, K.H., Designing Racks for Transporting Flat Glass Products in a Construction Industry, Journal of the Korean Institute of Industrial Engineers, 2016, Vol. 42, No. 4, pp. 270-279. https://doi.org/10.7232/JKIIE.2016.42.4.270
  7. Lee, C.S. and Choe, K.I., A Manufacturing Execution System based on ISA-95, Proceedings of the Conference on Korean Operations Research and Management Society, 2007, pp. 1092-1096.
  8. Lee, D.K. and Oh, D.K., A Study on Simulation based Manufacturing in Shipyards : Focused on a Long-term Plan Verification, Journal of the Korean Society of Marine Environment & Safety, 2014, Vol. 20, No. 1, pp. 86-95. https://doi.org/10.7837/kosomes.2014.20.1.086
  9. Lee, J.Y. and Shin, M.S., Research Trends of Scheduling Techniques for Domestic Major Industries, Journal of Society of Korea Industrial and Systems Engineering, 2018, Vol. 41, No. 1, pp. 55-69.
  10. Lee, S.W., Kim, H.S., and Cho, S.Y., A Study on Dynamic Scheduling in Flexible Manufacturing System Environment, Journal of Society of Korea Industrial and Systems Engineering, 2004, Vol. 27, No. 2, pp. 17-23.
  11. Lin, J.T. and Chen, C.M., Simulation Optimization Approach for Hybrid Flow Shop Scheduling Problem in Semiconductor Back-end Manufacturing, Simulation Modelling Practice and Theory, 2015, Vol. 51, pp. 100-114. https://doi.org/10.1016/j.simpat.2014.10.008
  12. Madsen, O.B., Glass Cutting in a Small Firm, Mathematical Programming, 1979, Vol. 17, No. 1, pp. 85-90. https://doi.org/10.1007/BF01588227
  13. Mun, J.S., Park, S.Y., and Lee, D.H., A Study on the Productivity Improvement of the Dicing Blade Production Process, Journal of Society of Korea Industrial and Systems Engineering, 2016, Vol. 39, No. 3, pp. 147-155. https://doi.org/10.11627/jkise.2016.39.3.147
  14. Na, B., Ahmed, S., Nemhauser, G., and Sokol, J., A Cutting and Scheduling Problem in Float Glass Manufacturing, Journal of Scheduling, 2004, Vol. 17, No. 1, pp. 95-107. https://doi.org/10.1007/s10951-013-0335-z
  15. Na, B., Ahmed, S., Nemhauser, G., and Sokol, J., Optimization of Automated Float Glass Lines, International Journal of Production Economics, 2013, Vol. 145, No. 2, pp. 561-572. https://doi.org/10.1016/j.ijpe.2013.04.024
  16. Papavasileiou, V., Koulouris, A., Siletti, C., and Petrides, D., Optimize Manufacturing of Pharmaceutical Products with Process Simulation and Production Scheduling Tools, Chemical Engineering Research and Design, 2007, Vol. 85, No. 7, pp. 1086-1097. https://doi.org/10.1205/cherd06240
  17. Pinedo, M.L., Scheduling : Theory, Algorithms, and Systems, Springer, 2016.
  18. Pipero, C. and Manjunath, K., ISA 95 Implementation Best Practices : Workflow Descriptions using B2MML, WBF North American Conference, Atlanta, GA, 2006.
  19. Smith, J.S., Sturrock, D.T., and Kelton, W.D., Simio and Simulation : Modeling, Analysis, Application, Simio LLC, 2017.
  20. Taskin, Z.C. and Unal, A.T., Tactical Level Planning in Float Glass Manufacturing with Co-production, Random Yields and Substitutable Products, European Journal of Operational Research, 2009, Vol. 199, No. 1, pp. 252-261. https://doi.org/10.1016/j.ejor.2008.11.024