Non-Container Port Services Bottlenecks Identification Using Process Mining and Simulation Analysis
- DOI
- 10.2991/aebmr.k.211226.006How to use a DOI?
- Keywords
- Business process management; event log; non-container loading and unloading; process mining; queuing system simulation analysis
- Abstract
The number of loading and unloading processes is one of the port’s main business processes. In carrying out loading and unloading services, there are fundamental indicators used as performance evaluation of a port in Indonesia, namely T/G/H (Ton/Gang/Hours) for the non-container performance of loading and unloading production. At one of Indonesia’s ports, the T/G/H indicator from 2018 to 2020 several times did not reach the specified minimum standard. Therefore, it is necessary to evaluate the loading and unloading time of activities with bottlenecks to minimize and improve performance. In this research, the identification of business process flows is based on applicable SOP using YAWL to obtain the event logs. The process mining tools then carry out the event log results from the system to identify the most significant bottlenecks in the business process. The activities are then analyzed using a queuing system simulation analysis based on ARENA tools. This study’s results obtained three processes with the biggest bottlenecks in the business process: the loading and unloading process, the timesheet, and the realization entries with the highest waiting time are 67 hours. These results can be a reference for the company to improve its performance in the future.
- Copyright
- © 2021 The Authors. Published by Atlantis Press International B.V.
- Open Access
- This is an open access article under the CC BY-NC license.
Cite this article
TY - CONF AU - Alvin Syarifudin Shahab AU - Mohammad Isa Irawan PY - 2021 DA - 2021/12/31 TI - Non-Container Port Services Bottlenecks Identification Using Process Mining and Simulation Analysis BT - Proceedings of the 3rd International Conference on Business and Management of Technology (ICONBMT 2021) PB - Atlantis Press SP - 40 EP - 46 SN - 2352-5428 UR - https://doi.org/10.2991/aebmr.k.211226.006 DO - 10.2991/aebmr.k.211226.006 ID - Shahab2021 ER -