EVALUATING THE CONSOLIDATION OF DISTRIBUTION FLOWS USING A DISCRETE EVENT SUPPLY CHAIN SIMULATION TOOL: APPLICATION TO A CASE STUDY IN GREECE

Author(s):  
Markus Rabe ◽  
Astrid Klueter ◽  
Alexander Wuttke
Author(s):  
Jeffrey W. Hermann ◽  
Edward Lin ◽  
Guruprasad Pundoor

Simulation is a very useful tool for predicting supply chain performance. Because there are no standard simulation elements that represent accurately the activities in a supply chain, there exist a variety of approaches for developing supply chain simulation models. To improve this situation, this paper describes a novel supply chain simulation framework that follows the Supply Chain Operations Reference (SCOR) model. This framework has been used for building powerful simulation models that integrate discrete event simulation and spreadsheets. The simulation models are hierarchical and use submodels that capture activities specific to supply chains. The SCOR framework provides a basis for defining the level of detail in a way as to include as many features as possible, while not making them industry specific. This approach enables the reuse of submodels, which reduces development time. The paper describes the implementation of the simulation models and how the submodels interact during execution.


2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
T.M. Pinho ◽  
J.P. Coelho ◽  
P.M. Oliveira ◽  
B. Oliveira ◽  
A. Marques ◽  
...  

The optimisation of forest fuels supply chain involves several entities actors, and particularities. To successfully manage these supply chains, efficient tools must be devised with the ability to deal with stakeholders dynamic interactions and to optimize the supply chain performance as a whole while being stable and robust, even in the presence of uncertainties. This work proposes a framework to coordinate different planning levels and event-based models to manage the forest-based supply chain. In particular, with the new methodology, the resilience and flexibility of the biomass supply chain is increased through a closed-loop system based on the system forecasts provided by a discrete-event model. The developed event-based predictive model will be described in detail, explaining its link with the remaining elements. The implemented models and their links within the proposed framework are presented in a case study in Finland and results are shown to illustrate the advantage of the proposed architecture.


Author(s):  
Mehmet Talha Dulman ◽  
Surendra M. Gupta

This chapter presents a methodology to evaluate the benefit of using sensors in closed-loop supply chains. Sensors can be embedded into products to collect helpful information during their use and end-of-life (EOL) phases. This information can subsequently be employed to estimate the remaining lives of components and products and to ensure that proper maintenance is provided to avoid premature failures. The information is also useful in determining the quality of the components and products when planning EOL operations such as disassembly, inspection, and remanufacturing. To statistically illustrate these benefits, discrete event simulation is employed to a case study consisting of regular and sensor-embedded refrigerator systems. A design of experiments study is then employed where experiments are run to compare the two systems. The results reveal that the sensor-embedded systems perform much better than the regular systems in terms of disassembly costs, inspection costs, and EOL profits generated by selling the remanufactured products and components.


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