Document Type : Research Paper

Authors

1 Department of Industrial and Systems Engineering, North Carolina State University, Raleigh, USA.

2 Department of Industrial Manufacturing, and Systems Engineering, University of Texas at EL Paso, USA.

Abstract

Many industrial production lines today are initially constructed and outfitted with machinery that, despite its inherent capabilities, struggles to satisfy increasing demand over time. The goal of this research is to find solutions to bottlenecks and improve the efficiency of the production line to satisfy rising productivity demands. The study primarily looks at an existing bottle production line in the edible oil industry, where the product is witnessing a boom in demand. Data on processing times at various workstations and their capacities were thoroughly collected and analyzed. Simulation emerged as the preferred tool for investigating and addressing the production line's intrinsic difficulties. Using Microsoft Excel for statistical analysis, an existing simulation model was created using Flexsim simulation, a process-oriented simulation software, to detect bottlenecks in the production line using the Processor block in the simulation. As a result, a modified model was offered to reduce waiting times by 12%, increase productivity by 6%, and increase overall profitability while efficiently dealing with rising demand across all seasons. As a result, this research represents a complete effort to identify operational challenges and present viable solutions that correspond with the industry's changing objectives. The study aims to contribute to optimizing production lines by utilizing contemporary simulation tools and statistical analysis, guaranteeing that they stay adaptive and responsive in the face of rising productivity demands.

Keywords

Main Subjects

[1]     Nath, N. C. (2021). Manufacturing sector of Bangladesh-growth, structure and strategies for future development [presentation]. Biennial Conference on "Global Economy and Vision 2021" (pp. 1–43). https://www.academia.edu/download/53386683/47.pdf
[2]     Fowler, J. W., & Rose, O. (2004). Grand challenges in modeling and simulation of complex manufacturing systems. Simulation, 80(9), 469–476. DOI:10.1177/0037549704044324
[3]     Manivel, M., & Sandeep, D. (2014). Layout planning in a pump manufacturing industry using ARENA. International journal of scientific & engineering research, 5(5), 432–435.
[4]     Watanapa, A., Kajondecha, P., Duangpitakwong, P., & Wiyaratn, W. (2011). Analysis plant layout design for effective production. Proceeding of the international multi conference of engineers and computer scientists (Vol. 2, pp. 543–559). Newswood Limited. https://www.iaeng.org/publication/IMECS2011/
[5]     Wiyaratn, W., Watanapa, A., & Kajondecha, P. (2013). Improvement plant layout based on systematic layout planning. IACSIT international journal of engineering and technology, 5(1), 76–79.
[6]     Ahmadi, R. H., Dasu, S., & Tang, C. S. (1992). The dynamic line allocation problem. Management science, 38(9), 1341–1353. DOI:10.1287/mnsc.38.9.1341
[7]     Eneyo, E. S., & Pannirselvam, G. P. (1998). The use of simulation in facility layout design: a practical consulting experience. 1998 winter simulation conference. proceedings (Cat. No. 98CH36274) (Vol. 2, pp. 1527–1532). IEEE. https://ieeexplore.ieee.org/abstract/document/746025
[8]     John, B., & E, J. J. (2013). Analysis and simulation of factory layout using ARENA. International journal of science and research publication, 3(2), 1–8.
[9]     Altiok, T., & Ranjan, R. (1989). Analysis of production lines with general service times and finite buffers: a two-node decomposition approach. Engineering costs and production economics, 17(1–4), 155–165. DOI:10.1016/0167-188X(89)90065-7
[10]   Dallery, Y., & Gershwin, S. B. (1992). Manufacturing flow line systems: a review of models and analytical results. Queueing systems, 12(1–2), 3–94. DOI:10.1007/BF01158636
[11]   Hammann, J. E., & Markovitch, N. A. (1995). Introduction to arena. Proceedings of the 27th conference on winter simulation (pp. 519–523). IEEE Computer Society.
[12]   Ullah, M. R., Molla, S., Mustaquim, S. M., Siddique, I. M., & Siddique, A. A. (2024). Exploratory approaches for improved cost effectiveness and profitability: utilizing mathematical analysis and value stream mapping on production floors. World journal of advanced engineering technology and sciences, 11(1), 076–085. DOI:10.30574/wjaets.2024.11.1.0028
[13]   Ullah, M. R., Molla, S., Siddique, I. M., Siddique, A. A., & Abedin, M. M. (2023). Utilization of Johnson’s algorithm for enhancing scheduling efficiency and identifying the best operation sequence: an illustrative scenario. Journal of recent activities in production, 8(3), 11–20. DOI:10.46610/jorap.2023.v08i03.002
[14]   Ullah, M. R., Molla, S., Md Siddique, I., Ahmed Siddique, A., & Abedin, M. M. (2023). Manufacturing excellence using line balancing & optimization tools: a simulation-based deep framework. Journal of modern thermodynamics in mechanical system, 5(3), 8–22. DOI:10.46610/jmtms.2023.v05i03.002
[15]   Ullah, M. R., Molla, S., Siddique, I. M., Siddique, A. A., & Abedin, M. M. (2023). Optimizing performance: a deep dive into overall equipment effectiveness (OEE) for operational excellence. Journal of industrial mechanics, 8(3), 26–40. DOI:10.46610/joim.2023.v08i03.004
[16]   Molla, S., Md Siddique, I., Siddique, A. A., & Abedin, M. M. (2023). Securing the future: a case study on the role of TPM technology in the domestic electronics industry amid the COVID-19 pandemic. Journal of industrial mechanics, 8(3), 41–51. DOI:10.46610/joim.2023.v08i03.005
[17]   Molla, S., Hasan, M. R., Siddique, A. A., & Siddique, I. M. (2024). SMED implementation for setup time reduction : a case study in the electronics manufacturing landscape. European journal of advances in engineering and technology, 11(1), 1–15.
[18]   Hasan, R., & Hossain, M. S. (2017). Design and construction of a portable charger by using solar cap analysis of a simple spring view project. Global journal of researches in engineering: a mechanical and mechanics engineering, 17(5), 14–18. https://www.researchgate.net/publication/327262942
[19]   Hasan, M. R., Molla, S., & Siddique, I. M. (2024). Next-gen production excellence: a deep simulation perspective on process improvement. Journal of mechatronics machine design and manufacturing, 6(1), 7–20. DOI:10.46610/jmmdm.2024.v06i01.002
[20]   Hossain, M. Z., Rahman, S. M. A., Hasan, M. I., Ullah, M. R., & Siddique, I. M. (2023). Evaluating the effectiveness of a portable wind generator that produces electricity using wind flow from moving vehicles. Journal of industrial mechanics, 8(2), 44–53. DOI:10.46610/joim.2023.v08i02.005
[21]   Rahman, S. A., & Shohan, S. (2015). Supplier selection using fuzzy-topsis method: a case study in a cement industry. IASET: journal of mechanicalengineering, 4(1), 31–42.
[22]   Rahman, S. M. A., Rahman, M. F., Tseng, T. L. B., & Kamal, T. (2023). A simulation-based approach for line balancing under demand uncertainty in production environment. 2023 winter simulation conference (WSC) (pp. 2020–2030). IEEE. https://ieeexplore.ieee.org/abstract/document/10408105
[23]   Faghidian, S. F., & Mahmodi, S. (2024). Evaluation of total quality management enablers using the DEMATEL-ISM integration method in the steel industry. Systemic analytics, 2(1), 14–26. DOI:10.31181/sa2120246
[24]   Maia, A. L. M. D., & Frogeri, R. F. (2023). Optimizing business value via IT governance mechanisms: an examination of SMEs in Southern Minas Gerais, Brazil. Journal of operational and strategic analytics, 1(3), 106–114. DOI:10.56578/josa010301
[25]   Bazargan, A., Najafi, S. E., Lotfi, F. H., Fallah, M., & Edalatpanah, S. A. (2023). Presenting a productivity analysis model for Iran oil industries using Malmquist network analysis. Decision making: applications in management and engineering, 6(2), 251–292. DOI:10.31181/dmame622023705
[26]   Hanan, F., & Ali, R. (2023). Production optimization in manufacturing industries using Cobb-Douglas production function. Journal of operational and strategic analytics, 1(3), 131–139. DOI:10.56578/josa010304
[27]   Zhang, Y., Imeni, M., & Edalatpanah, S. A. (2023). Environmental dimension of corporate social responsibility and earnings persistence: an exploration of the moderator roles of operating efficiency and financing cost. Sustainability (Switzerland), 15(20), 14814. DOI:10.3390/su152014814