Date of Award


Degree Name

Master of Science


Industrial and Entrepreneurial Engineering and Engineering Management


Industrial and Manufacturing Engineering

First Advisor

Dr. Tarun Gupta

Second Advisor

Dr. Frank Wolf

Third Advisor

Dr. David Lyth

Access Setting

Masters Thesis-Open Access


The study of effects of production data variabilities on Kanban based cellular manufacturing system is vital before its design and implementation because it would give better understanding of their uncertain behavior.

In this research, a detailed analysis of a Kanban system, with subcell scenario, under dynamic operating conditions is performed. The Control variables considered were number of Kanbans, processing time variability, demand variability and machine breakdown. The performance parameters considered were profit, production lead time, machine utilization and material processing lead time.

Approximately 200 simulation runs were made with 3 replications each by varying one control variable at a time. The conclusions of this study were that an increase in the number of Kanbans has positive effect on the system performance, only, up to a certain threshold number of Kanbans; processing time variability and demand variability have deteriorating effect on the system performance; effect of demand variability depends upon the number of Kanbans; and machine breakdown in main-line has severe negative effect on the system compared to that of in the subcell. This presented can be used as an effective base for the design of a new system or updating an existing one.

Included in

Manufacturing Commons