On the performance of a manufacturing process with employee learning and turnover

Abstract

Discrete-event simulation (DES) is a method of mimicking the behavior of a real system and has the ability to model complex systems and phenomena. In this study a DES model of a real production system was developed. The model provides an accurate representation of the real system and insight into the underlying behavior of the system. The production line of interest assembles medical garments for the health care industry. Data from the real system was used to accurately characterize: random assembly cycle times, random times until machine failures, random times until machine repairs, improvements that result from worker experience (i.e. learning) and random durations of worker employment. Numerical experiments were conducted to examine the impact of important factors on the production line, and to suggest system design improvements. If the changes recommended in this study are implemented a 13.5% increase in throughput rate of the production line may be realized.