Analysis and productivity improvement of an automated material handling system through simulation
Leaders for Global Operations Program.
Zeynep Ton and Brian Anthony.
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As Amazon.com has grown, the company has invested in warehouse systems similar to those traditionally found in manufacturing. These systems are a complex and interconnected set of manned work processing stations linked together by conveyance. This thesis examines one such system, arranged as a set of parallel single piece workflow lines joined by a central computerized sorter that route work between lines, and examines the effect of sorter algorithms and line capacity on production output. Work studies, interviews, and a practical experiment suggest a deterioration in the feedback provided to the central sorter for work routing. A Monte Carlo simulation model of the system further supports this hypothesis, suggesting that system throughput is 11.7% lower than a system that perfectly routes work to line in a pull fashion. While perfect routing is not practically feasible, the thesis then explores two routing heuristics designed around starvation response and dynamic capacity analysis, which simulation suggest may yield a 6.73% increase in throughput. In doing so, the thesis provides a case study on process improvement using simulation to characterize a complicated mechanical production system that is otherwise analytically intractable.
Thesis: M.B.A., Massachusetts Institute of Technology, Sloan School of Management, 2015. In conjunction with the Leaders for Global Operations Program at MIT.Thesis: S.M., Massachusetts Institute of Technology, Department of Mechanical Engineering, 2015. In conjunction with the Leaders for Global Operations Program at MIT.Cataloged from PDF version of thesis.Includes bibliographical references (pages 66-67).
DepartmentLeaders for Global Operations Program at MIT; Massachusetts Institute of Technology. Department of Mechanical Engineering; Sloan School of Management
Massachusetts Institute of Technology
Sloan School of Management., Mechanical Engineering., Leaders for Global Operations Program.