Using an empirical queueing approach to predict future flow times

Abstract

The traditional method used to describe a steady-state manufacturing system is a queueing model; whereas the common tool used to predict the future performance of a dynamic manufacturing system is a simulation model. This study proposes an empirical queueing approach to obtain the flow time performance measures of a complex dynamic manufacturing system, such as semiconductor wafer fabrication. This approach is easier to implement than a simulation model and more straightforward than a queueing model. Initially, the empirical queueing curve of each work station, which defines the relationship between the utilization rate and the expected waiting time of a small time period, is obtained from the historical database. Then, an iterative scheme is used to predict the future system behavior. Several latest researches have reported that the prediction of future flow times is important in the operation management of a complex manufacturing system. The approach proposed in this study can be easily implemented for such purposes, and the experimental results show that this approach can accurately predict the future flow times.