Performance analysis of an automated production system with queue length dependent service rates

In this paper, a simulation model is built to analyze the performance of a pull type (Kanban) automated production system with a continuous supply of raw materials and generally distributed demand and service times. The system under consideration represents an attempt of modeling a Kanban controlled production system where the station production rates are dependent on product queue lengths. It is composed of three stations; one of them is a bottleneck station. Stations have different processing speeds (low, medium and high) and are connected by a conveyor system whose actuation is coordinated with the stations. Conveyors transfer the products between stations and provide local buffering of material at the processing tool level. A number of sensors exist on each conveyor to control the processing speed and the operational/stoppage state of the stations. Numerical experiments are conducted to check the model validity and to study the effect of different parameters on the system performance. Results obtained from the simulation model are compared with results obtained from an analytical model built for the same system. The model is used to obtain accurate estimates of the system performance measures such as throughput, waiting queue lengths and work-in-process inventory. Results show that changing sensors' positions affect the system performance considerably. Hence, an optimization study is conducted in order to find the values of sensors' positions that optimize the system performance.