Graduation Year

2004

Document Type

Thesis

Degree

M.S.I.E.

Degree Granting Department

Industrial Engineering

Major Professor

Suresh K. Khator, Ph.D.

Committee Member

Geoffrey Okogbaa, Ph.D.

Committee Member

James Stock, Ph.D.

Keywords

just-in-time, dedicated cards, shared cards, breakdowns, simulation

Abstract

Over the years, much attention has been given to the analysis of the pull type ordering system to reduce in-process inventory and to improve product quality. Kanban Control Systems are widely used to control the release of parts in multi-stage manufacturing systems operating under a pull mechanism. Considerable research has been done to study the individual manufacturing systems for multi stage and single product. However, not much research has been done to compare different pull control policies for multi product manufacturing systems.

Most of the research done in multi-product system assumes that a kanban card is dedicated to a part type. The aim of this research is to compare the Kanban Control System (KCS), Generalized Kanban Control System (GKCS) and Extended Kanban Control System (EKCS) in the context of multi-product manufacturing systems where the kanban cards are either dedicated to a single part type or shared among the different part types. In this study, we analyze the performance of various control policies for a multi-product multi-stage manufacturing system. The manufacturing system considered in this research use a single-card kanban system, where the transportation of materials between the different work-centers is controlled by production kanbans. Demands that arrive to the system are satisfied from the finished goods inventory whenever possible and are backordered otherwise. Performance measures are number of backorders, average waiting time of backordered demand and average work in process.

Our results show that Shared GKCS has lower number of backorders when the variability in the processing time is low, while Shared EKCS performs better when variability in the processing time is high. Trade off analysis was performed on average WIP and time to satisfy backorders. The Shared EKCS makes a better service-inventory compromise than traditional KCS. The Shared GKCS results in lower average waiting time to satisfy the backordered demand indicating responsiveness of this control system.

The overall results indicate GKCS and EKCS with dedicated or shared kanbans outclass kanban control policy. The shared kanban-like control systems outperform dedicated control systems for all performance measures considered in this research.

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