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Full-Text Articles in Operations Research, Systems Engineering and Industrial Engineering
A Robust Aggregation Approach To Simplification Of Manufacturing Flow Line Models, Paul Savory
A Robust Aggregation Approach To Simplification Of Manufacturing Flow Line Models, Paul Savory
Department of Industrial and Management Systems Engineering: Faculty Publications
One of the more difficult tasks facing a modeler in developing a simulation model of a discrete part manufacturing system is deciding at what level of abstraction to represent the resources of the system. For example, questions about plant capacity can be modeled with a simple model, whereas questions regarding the efficiency of different part scheduling rules can only be answered with a more detailed model. In developing a simulation model, most of the actual features of the system under study must be ignored and an abstraction must be developed. If done correctly, this idealization provides a useful approximation of …
A Robust Aggregation Approach To Simplification Of Manufacturing Flow Line Models, Paul Savory
A Robust Aggregation Approach To Simplification Of Manufacturing Flow Line Models, Paul Savory
Industrial and Management Systems Engineering: Presentations
One of the more difficult tasks facing a modeler in developing a simulation model of a discrete part manufacturing system is deciding at what level of abstraction to represent the resources of the system. For example, questions about plant capacity can be modeled with a simple model, whereas questions regarding the efficiency of different part scheduling rules can only be answered with a more detailed model. In developing a simulation model, most of the actual features of the system under study must be ignored and an abstraction must be developed. If done correctly, this idealization provides a useful approximation of …
Introduction To Intellisim 2.0, Paul Savory
Introduction To Intellisim 2.0, Paul Savory
Department of Industrial and Management Systems Engineering: Faculty Publications
IntelliSIM is a prototype for a new generation of knowledge-based simulation tool that has been developed by the Systems Simulation Laboratory at Arizona State University. This tool is a computer environment that allows non-simulation trained modelers to predict the performance of a manufacturing system for which the necessary data is available. The system provides predictive data on such items as throughput time, queue levels, equipment utilization, reactions to machine failures, etc. With IntelliSIM, the benefits of discrete-event simulation can be exploited without requiring the high level of expertise necessary to successfully conduct a sound simulation study. The approach offered with …