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Modeling multilevel supply chain systems to optimize order quantities and order points through mathematical models, discrete event simulation and physical simulations

Posted on:2006-12-28Degree:Ph.DType:Dissertation
University:Old Dominion UniversityCandidate:Verma, Alok KFull Text:PDF
GTID:1459390008451638Subject:Engineering
Abstract/Summary:
Managing supply chains in today's distributed manufacturing environment has become more complex. To remain competitive in today's global marketplace, organizations must streamline their supply chains. The practice of coordinating the design, procurement, flow of goods, services, information and finances, from raw material flows to parts supplier to manufacturer to distributor to retailer and finally to consumer requires synchronized planning and execution. Efficient and effective supply chain management assists an organization in getting the right goods and services to the place needed at the right time, in the proper quantity and at acceptable cost. Managing this process involves developing and overseeing relationships with suppliers and customers, controlling inventory, and forecasting demand, all requiring constant feedback from every link in the chain. Base Stock Model and (Q, r) models are applied to three tier single-product supply chain to calculate order quantities and reorder point at various locations within the supply chain. Two physical simulations are designed to study the above supply chain. One of these simulations is specifically designed to validate the results from Base Stock model. A computer based discrete event simulation model is created to study the three tier supply chain and to validate the results of the Base Stock model. Results from these mathematical models, physical simulation models and computer based simulation model are compared. In addition, the physical simulation model studies the impact of lean implementation through various performance metrics and the results demonstrate the power of physical simulations as a pedagogical tool for training. Contribution of present work in understanding the supply chain integration is discussed and future research topics are presented.
Keywords/Search Tags:Supply chain, Discrete event simulation, Physical simulations, Mathematical models, Order quantities, Base stock model, Validate the results
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