Operational and strategic supply model redesign for an optical chain company using digital simulation

Abstract

Decision making inside a company is usually performed by means of decision support tools at three different levels (strategic, tactical and operational) according to the working horizon. Unfortunately, the consequences of any decision at the strategic level are propagated to the tactical and even the operational levels. In order to support highly efficient flexibility while avoiding infrastructure over-sizing, resource saturation and poor coordination of activities and resources, it is important to consider the cause—effect interaction of strategic decisions with operational ones. In this paper, a discrete-event system simulation approach to evaluate the influence of the internal interactions among material, people, information and financial resources on the success of a Spanish optician supply chain is introduced. The emergent dynamics are analyzed and a redesign of the business and distribution network is proposed to foster synergy among supply chain actors.

Keywords

discrete event simulation logistics business model

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References

Curcio D. , Longo F. Inventory and internal logistics management as critical factors affecting the supply chain performances. International Journal of Simulation and Process Modelling 2009; 5(2): 127-137.

Pecherska J. , Merkuryev Y. Discrete-event simulation: Methodology and spreadsheet-based implementation. Przeglad Elektrotechniczny 2006; 82(4): 49-55.

Tiacci L. , Saetta S. An approach to evaluate the impact of interaction between demand forecasting method and stock control policy on the inventory system performances. International Journal of Production Economics 2009; 1(118): 63-71.

Buil R. , Piera MA Warehouse redesign to satisfy tight supply chain management constraints. WSEAS Transactions on Information Science and Applications 2008; 3(5): 286-291.

Buil R. , Piera MA New Warehouse design methodology at strategic and operational level. In Proceedings of 6th WSEAS International Conference on System Science and Simulation in Engineering (ICOSSE’07). November 2007, pp. 196-201.

Buil R. , Piera MA Redesign of a picking process using a simulation model. In 19th European Modeling and Simulation Symposium. Simulation in Industry (EMSS’07), October 2007, pp. 243-248.

Cuatrecasas LL Lean Management: Volver a empezar. Gestión, 2000.

Guasch A. , Piera MA , Casanovas J. , and Figueras J. Modelado y simulación: Aplicación a procesos logísticos de fabricación y servicios, UPC Editions, 2003.

Merkuryev Y. , Merkuryeva G. , Piera MA , and Guasch A. Simulation-Based Case Studies in Logistics. Education and Applied Research . Berlin: Springer, 2009.

10.

Merkuryeva G. , Merkuryev Y. Metamodelling in computer simulation: State of art. In preprints of the Advanced Summer Institute 1999 on Life Cycle Approaches to Production Systems: Management, Control, and Supervision. Belgium : Leuven, 1999.

11.

Davis P. , Bigelow J. Motivated meta-models. Synthesis of Cause-Effect Reasoning and Statistical Metamodeling. Rand Corporation, 2003 .