Analysis of Factors that Influence Automobile Workshop Queue Performance Using Design of Experiments

Subject Areas : Tectonostratigraphy

Welly  Sugianto ¹ (Faculty of Mechanical and Manufacturing Engineering, Universiti Tun Hussein Onn Malaysia, Parit Raja, Johor, 86400)
Reazul Haq  Abdul Haq ² (Faculty of Mechanical and Manufacturing Engineering, Universiti Tun Hussein Onn Malaysia, Parit Raja, Johor, 86400)

Received: 2023-10-29 Accepted : 2023-11-28 Published : 2024-09-01

Keywords: Queue, Design of Experiments, automobile workshop, categorical, numerical,

Abstract :

Probability and simulation techniques have been applied to analyze automobile workshop queue performance, but no study has been conducted to identify factors that affect automobile workshop queue performance. It is necessary to identify the factors that influence queue performance to design automobile workshop queue system. This study uses the design of experiments method to investigate the factors that influence queue performance. The number of servers, server area, number of phases, number of workers, and arrival rate are among the numerical factors evaluated. There are two categorical factors to consider: layout type and worker experience. Their effect on queue performance, including queue cost, service time, average customer waiting time, and number of customers, is examined. Additionally, this study seeks to discover appropriate experimental designs. There are three different experimental designs used. The first design is a split plot 2_VI^(7-1) that considers arrival rate as a categorical factor. The second design is a robust design that considers arrival rate as a source of variation. The third design is a full split plot design that considers arrival rate as a numeric factor. According to this study, a full split plot design offers higher accuracy in identifying factors influencing queue performance. The queue performance is significantly affected by the number of servers, phases, workers, arrival rate, and layout. This study paves the way for future studies to determine the optimal point of queue performance.

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