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A comparative simulation study of manufacturing resource planning, just-in-time and theory of constraints in vat classified flow shops facing smooth and lumpy demand

Posted on:2003-02-11Degree:Ph.DType:Dissertation
University:Texas Tech UniversityCandidate:Gamas Buentello, Edmundo JoseFull Text:PDF
GTID:1469390011989136Subject:Operations Research
Abstract/Summary:
Three production planning and control methods currently vie for supremacy in real-world industrial application. One of the production planning and control methods in question is Manufacturing Resource Planning (MRPII), which is founded upon the logic of its predecessor, Material Requirements Planning (MRP). The other two production planning and control methods concerned are Just-In-Time (JIT) and Theory Of Constraints (TOC).; Each one of these production planning and control methods purports to endow an industrial manager with an excellent conceptual framework for the planning and control of his or her production operations. The question of whether one of the three production planning and control methods mentioned is superior to the others is by logical extension a valid and important one.; Two prior simulation studies compare the performance of the three aforementioned production planning and control methods. One study was conducted by Fogarty, Blackstone and Hoffmann (1991), and the more recent study was undertaken by Cook (1994). Both studies contrast the three production planning and control methods in an “I” classified flow shop, which is characterized by a single production path.; This dissertation compares the performance of the three production planning and control methods in flow shops with a more complex layout, known a “V”, “A” and “T” flow shops respectively in accordance with the shape of their layout. It builds a simulation model to represent each of these three layouts, and runs it under each of the three production planning and control methods.; The simulation runs also confront the three flow shops with either a smooth or a lumpy demand profile, and with one of four possible total material buffer capacities. In all, 72 different scenarios are evaluated. The performance measures collected are mean total output, mean flow time, mean work-in-progress and mean tardiness. The results of the simulation runs indicate that substantial differences exist in flow shop performance with respect to the production planning and control method selected, the demand profile faced, and the total material buffer capacity that is made available.
Keywords/Search Tags:Planning, Flow shops, Simulation
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