Simulation-based approaches for processes improvement of a sugar mill yard management system: A case study of the sugar industry in the central region of Thailand
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Creator 1. Chuleeporn Kusoncum
2. Kanchana Sethanan
3. Erni Puspanantasari Putri
4. Woraya Neungmacha
Title Simulation-based approaches for processes improvement of a sugar mill yard management system: A case study of the sugar industry in the central region of Thailand
Publisher Faculty of Engineering, Khon Kaen University
Publication Year 2561
Journal Title Engineering and Applied Science Research
Journal Vol. 45
Journal No. 4
Page no. 320-331
Keyword Agro industry, Supply chain management, Queuing theory, Scheduling and sequencing, Sugarcane inbound logistics
URL Website https://www.tci-thaijo.org/index.php/easr/index
Website title Engineering and Applied Science Research
ISSN 2539-6161
Abstract Inbound logistics in the sugarcane industry focus on the efficiency of sugarcane transportation to the sugar mill under mill capacity constraints. At present, the issue of the long waiting time for vehicles at the mill yard occurs because of the high uncertainty of vehicle arrival rate and the important factor is not an unloading machine allocation strategy. This research proposes a methodology to improve mill yard management that aims to reduce the time in the system for sugarcane transport vehicles. The current management system of the mill yard system was simulated using Arena software. To treat this as a waiting time problem, the current study focuses on the average vehicle time in the system, to lead to further improvements by developing alternative configurations. Two alternative scenarios were proposed as (1) the proposed model 1: developing a registration process based on a grower type priority serving all grower types on a first come first served (FCFS) basis and (2) the proposed model 2: allocating unloading machines depending on the type of sugarcane grower. The results show that with the current system, vehicles spend 10.18 hours in the system. Proposed model 1 shows that they will spend 9.31 hours in the system while proposed model 2 predicts that they will spend 9.02 hours in the system. Thus, improvements reflected in reduced time in the system show reductions of 0.87 hours (52.2 minutes, 8.55%) and 1.16 hours (69.6 minutes, 11.39%), respectively.
Engineering and Applied Science Research

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