Date of Graduation
Statler College of Engineering and Mineral Resources
Industrial and Managements Systems Engineering
Just-In-Time (JIT) has become one of the most popular production control philosophies in the last three decades. JIT did not find acceptance in the American companies until after the oil crisis. To be more flexible and to adapt quickly to changes in the market, many American companies took to the recourse of JIT and have been extremely successful. JIT systems typically employ kanbans as a means of inventory control. A JIT system operating under kanban control is commonly termed as a "pull system" due to the way in which succeeding stages trigger production at preceding stages. Owing to this close dependence of stages on a production line, the performance of a kanban controlled JIT system is sensitive to various kinds of stochasticity.;It was the aim of this thesis to characterize such inventory systems under different conditions. In particular, the research focused on kanban controlled feeder lines. Various design and operational parameters like number of kanbans, number of stages, number of product types assembled and processing time variability were studied. Metrics such as time-in-system, throughput, kanban waiting time, utilization, stockout and work-in-process were used to measure the performance of the system. A simulation model was constructed to model the system and to carry out the various experiments conducted as part of this research. It was observed that time in system was significantly affected by de number of kanbans, number of product types and the level of processing time variability at the stages. The analysis of work-in-process indicated that it was affected by the number (of kanbans, number of stages, number of product types and the level of processing time variability at the stages. The factors affecting stockout were the number of kanbans and the number of products. Kanban waiting times were impacted by the number of kanbans, number of stages, number of product types and the level of processing time variability.
Krishnappa, Arvind R., "Simulation study of a kanban-controlled production system" (1999). Graduate Theses, Dissertations, and Problem Reports. 950.