The paper presents an advanced modeling approach and a simulation model for supporting supply chain management. The first objective is to develop a flexible, time-efficient and parametric supply chain simulator starting from a discrete event simulation package. To this end we propose and advanced modeling approach. The second objective is to provide a decision making tool for supply chain management. The simulator is a decision making tool capable of analyzing different supply chain scenarios by using an approach based on multiple performance measures and user-defined set of input parameters. Our simulator capabilities as decision making tool are strongly amplified if Design of Experiment (DOE) and Analysis of Variance (ANOVA) are respectively used for experiments planning and simulation results analysis. With regard to supply chain decision making process, we propose an application example for a better understanding of tool potentials. The application example considers a specific supply chain scenario and analyzes the effects of inventory control policies, lead times, customers' demand intensity and variability, on three different supply chain performance measures. (C) 2007 Elsevier Ltd. All rights reserved.

An advanced supply chain management tool based on modeling and simulation

LONGO, Francesco;Mirabelli G.
2008-01-01

Abstract

The paper presents an advanced modeling approach and a simulation model for supporting supply chain management. The first objective is to develop a flexible, time-efficient and parametric supply chain simulator starting from a discrete event simulation package. To this end we propose and advanced modeling approach. The second objective is to provide a decision making tool for supply chain management. The simulator is a decision making tool capable of analyzing different supply chain scenarios by using an approach based on multiple performance measures and user-defined set of input parameters. Our simulator capabilities as decision making tool are strongly amplified if Design of Experiment (DOE) and Analysis of Variance (ANOVA) are respectively used for experiments planning and simulation results analysis. With regard to supply chain decision making process, we propose an application example for a better understanding of tool potentials. The application example considers a specific supply chain scenario and analyzes the effects of inventory control policies, lead times, customers' demand intensity and variability, on three different supply chain performance measures. (C) 2007 Elsevier Ltd. All rights reserved.
2008
Modeling & Simulation; Decision making tool; Suppl chain Management
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.11770/140612
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