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Full-Text Articles in Other Operations Research, Systems Engineering and Industrial Engineering
Randomly Generating Manufacturing Flow Line Models Using Mathematica, Paul Savory
Randomly Generating Manufacturing Flow Line Models Using Mathematica, Paul Savory
Department of Industrial and Management Systems Engineering: Faculty Publications
To test heuristic algorithms and techniques, researchers need numerous datasets so as to measure effectiveness and improve approaches. This paper discusses using Mathematica, a mathematical programming language, for randomly generating the specifications for manufacturing flow line models. Important issues include determining an arrival rate to a flow line, the number of flow line stations, the number of parallel servers for each production station, and specifying the service time distributions and their associated parameters. The paper concludes with a discussion on generating more general types of simulation models.
An Aggregation Procedure For Simulating Manufacturing Flow Line Models, Paul Savory, Gerald Mackulak
An Aggregation Procedure For Simulating Manufacturing Flow Line Models, Paul Savory, Gerald Mackulak
Department of Industrial and Management Systems Engineering: Faculty Publications
We develop a formal method for specifying an aggregate discrete-event simulation model of a production flow line manufacturing system. The methodology operates by aggregating production stations or resources of a flow line. Determining the specifications for representing the aggregated resources in a simulation model is the focus of our presentation. We test the methodology for a set of flow lines with exponentially distributed arrival and service times. Comparisons between analytical and simulation results indicate the aggregation approach is quite accurate for estimating average part cycle time.