Modeling of Automobile Assembly Line Performance Using ARENA Simulation Software
DOI:
https://doi.org/10.56294/sctconf2024828Keywords:
Computer Simulation, Assembly Line, Bottlenecks, Modeling, ThroughputAbstract
Due to the intense competition in today's business environment, companies must continuously analyze and enhance their existing manufacturing systems. Discrete event simulation, which is especially helpful for simulating queuing systems, involves describing the system as it evolves. The building and study of a simulation model of an existing production line are the main topics of this paper. The findings demonstrate that the current system's throughput is low due to bottlenecks, extended processing times at workstations, and inefficient resource utilization, all contribute to productivity losses in automotive assembly lines. This paper aims to evaluate the efficiency of the production line performance of automobile assembly lines using Arena modeling and simulation. Data provided by the company's management is utilized to calculate the processing time and standard time for each step in the production line. Additional information is gathered through direct observation of the assembly line. A car assembly manufacturing line was selected as a case study, and Arena 16.0 software was employed for basic modeling and analysis to achieve these objectives
References
1. E. CARATA, “Analysis of shop floor machine parts manufacturing through discrete event simulation,” Univ. Teh. „Gheorghe Asachi” din Iaşi, vol. 66, p. 70, 2020.
2. T. Araya, Simulation with ARENA. McGraw-hill, 2002.
3. S. Anil Kumar and N. Suresh, Production and operations management:(with skill development, caselets and cases). New Age International (P) Ltd., Publishers, 2008.
4. G. A. Benti* and 1 & Dr. Balkeshwar Singh2, “INTERNATIONAL JOURNAL OF ENGINEERING SCIENCES & RESEARCH TECHNOLOGY,” 2019.
5. S. H. Han, M. Al-Hussein, S. Al-Jibouri, and H. Yu, “Automated post-simulation visualization of modular building production assembly line,” Autom. Constr., vol. 21, pp. 229–236, 2012.
6. S. Kłos and J. Patalas-Maliszewska, “Throughput analysis of automatic production lines based on simulation methods,” in International Conference on Intelligent Data Engineering and Automated Learning, 2015, pp. 181–190.
7. A. S. Kathem, L. A. H. Al-Kindi, and Z. Al-Baldawi, “Integration of Lean Concepts and Line balancing Focusing on Value Adding Activities,” Des. Eng., no. 6, pp. 6263–6275, 2021.
8. P. Pawlewski and M. Fertsch, “Modeling and simulation method to find and eliminate bottlenecks in production logistics systems,” in Proceedings of the 2010 Winter Simulation Conference, 2010, pp. 1946–1956.
9. I. Radulescu, A. C. Tociu, and A. V Radulescu, “Modeling and simulating the activities in an automobile repair shop using ARENA software–part 1,” in IOP Conference Series: Materials Science and Engineering, 2020, vol. 997, no. 1, p. 12128.
10. G. Çalışkan, “Bir tekstil işletmesinde simülasyonoptimizasyon yaklaşımı ile hat dengeleme çalışması.” Pamukkale Üniversitesi Fen Bilimleri Enstitüsü, 2020.
Published
Issue
Section
License
Copyright (c) 2024 Ali J. Mohammed, Amjad B. Abdulghafour, Abass M.Jabber AL- Enzi (Author)
This work is licensed under a Creative Commons Attribution 4.0 International License.
The article is distributed under the Creative Commons Attribution 4.0 License. Unless otherwise stated, associated published material is distributed under the same licence.
