Evaluation of Cement Production for Continuous and Discrete Flow Systems by Applying a Discrete Event Simulation Approach

Authors

  • Wan Laailatul Author
  • Mohd Kamal Nawawi Northern University of Malaysia image/svg+xml Author
  • Nur Anis Hannan Md Shahid Author

DOI:

https://doi.org/10.66901/vrc6pk51

Keywords:

Arena software, cement grinding process, discrete event simulation, material flow modeling, mixing tank

Abstract

The purpose of this study is to model and simulate the operations of the cement manufacturing industry using the Discrete Event Simulation (DES) approach. The study focuses on improving operational efficiency and supporting decision-making through systematic process analysis and modelling. Although cement manufacturing consists of three main stages, including raw material preparation, pyro processing, and cement grinding and distribution, this study adopts a tank-flow approach to analyze material flow behavior during the critical cement grinding process. A simulation model was developed using Arena Software version 16.2 to represent both continuous and discrete flow characteristics of the system. Four alternative scenarios were evaluated against the basic model. According to the results, Scenario 2 reduced the mixing time of Mixing Tank 2 by almost 22%, while Scenario 3 obtained the lowest average total mixing time for Mixing Tank 1 (2.194 hours), which is a decrease of roughly 32% when compared to the basic model. Scenario 4 significantly increased the accumulation in Mixing Tank 2 (4046.9 tons) in terms of tank levels, suggesting possible bottlenecks downstream. These results emphasize the difference between higher inventory levels and shorter processing times. Preventive maintenance techniques are suggested, considering the simulation results, in order to reduce delays and manage excessive material accumulation, which will enhance system dependability and overall operating performance.

References

Abd Jalal, M. Z. H., Nawawi, M. K. M., Desa, W. L. H. M., Khalid, R., Abduljabbar, W. K., & Ramli, R. (2017). Green Supply Chain: Simulating Road Traffic Congestion. Journal of Physics: Conference Series, 890(1).

Abideen, A., & Mohamad, F. B. (2021). Improving the Performance of a Malaysian Pharmaceutical Warehouse Supply Chain by Integrating Value Stream Mapping and Discrete Event Simulation. Journal of Modelling in Management, 16(1), 70–102.

Dalle Mura, M., & Dini, G. (2022). Job Rotation and Human–Robot Collaboration for Enhancing Ergonomics in Assembly Lines by a Genetic Algorithm. International Journal of Advanced Manufacturing Technology, 118(9–10), 2901–2914.

Hawari, N. N., Chen, L. L., & Nizad, N. S. (2021). Modeling and Simulation of the Queuing System at University Parcel Centre (UPC). Applied Mathematics and Computational Intelligence, 10(1), 87–100.

Hawari, N. N., Desa, W. L. H. M., Nordin, N., & Zaki, N. H. M. (2025). Improving Customer Service at Gas Stations Using Discrete Event Simulation Approach. ASM Science Journal, 20(1), 1–11

Javadi, S. M., Sadjadi, S. J., & Makui, A. (2023). Identification and Fixing Bottlenecks of A Food Manufacturing System using A Simulation Approach. Scientific Reports, 13(1), 1–10.

Katsigiannis, M., Pantelidakis, M., & Mykoniatis, K. (2024). Assessing the Transition from Mass Production to Lean Manufacturing using a Hybrid Simulation Model of a LEGO® Automotive Assembly Line. International Journal of Lean Six Sigma, 15(2), 220–246.

Kelton, W. D., Zupick, N. B., & Ivey, N. J. (2024). Simulation with Arena (7th ed.). McGraw Hill.

Kolny, D., Kaczmar-Kolny, E., & Dulina, Ľ. (2023). Modeling and Simulation of the Furniture Manufacturing and Assembly Process in the Arena Simulation Software. Technologia i Automatyzacja Montażu, 119(1), 13–22.

Nganga, P., Wakiru, J., & Muchiri, P. (2023). Maintenance Performance Optimization for Critical Subsystems in Cement Pre-Grinding Section: A Case Study Approach. International Journal of Industrial Engineering and Management, 14(3), 200–213.

Rocha, E. M., & Lopes, M. J. (2022). Bottleneck Prediction and Data-Driven Discrete-Event Simulation for A Balanced Manufacturing Line. Procedia Computer Science, 200, 1145–1154.

Sakamoto, N. (2019). Examination of the Congestion Situation of a Restaurant in a Theme Park using Feedback Control. Journal of Hospitality and Tourism Technology, 10(1), 73–89.

Sala, F., D’Urso, G., & Giardini, C. (2023). Discrete-Event Simulation Study of a COVID-19 Mass Vaccination Centre. International Journal of Medical Informatics, 170(August 2022), 104940.

Scrivano, S., Tan, B., & Tolio, T. (2023). Continuous-Flow Simulation of Manufacturing Systems with Assembly/Disassembly Machines, Multiple Loops and General Layout. Journal of Manufacturing Systems, 69(February), 103–118.

Published

2026-10-11