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.
Design for production (DFP) refers to methods that evaluate manufacturing system performance as a function of product design variables. DFP can lead a product development team to consider changing the product design to avoid problems or improve profitability. In addition, DFP can provoke suggestions to improve the manufacturing system.This paper reviews studies that have successfully applied DFP techniques in a variety of product domains. In addition, the paper discusses how product development teams can create new DFP techniques that will help them create more profitable products. The presentation of these examples and guidelines should encourage the use of DFP and improve product development.
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