ANALISIS BOTTLENECK DAN PENINGKATAN KINERJA LINI PRODUKSI PADA INDUSTRI MAKANAN DENGAN PENDEKATAN SIMULASI
DOI:
https://doi.org/10.51804/jiso.v8i1.1-9Keywords:
bottleneck, lini produksi, simulasiAbstract
ABSTRAK
Sebuah lini produksi dirancang untuk memastikan bahwa aktivitas produksi berlangsung lancar dengan output maksimal. Namun, kelancaran lini produksi dapat terganggu jika terjadi bottleneck dalam aktivitas atau proses tertentu, yang dapat menurunkan tingkat produksi secara signifikan. Penelitian ini bertujuan untuk mengidentifikasi dan menganalisis bottleneck dalam lini produksi industri makanan menggunakan pendekatan simulasi. Hasil simulasi kondisi eksisting menunjukkan bahwa proses packing menjadi bottleneck utama. Melalui skenario perbaikan berupa kombinasi penugasan mesin manual packing yang lebih fleksibel dan penambahan konveyor, simulasi membuktikan bahwa throughput produksi per jam dapat meningkat sebesar 8,6%.
ABSTRACT
A production line is designed to ensure that production activities run smoothly and achieve maximum output. However, its smooth operation can be disrupted if a bottleneck occurs in certain activities or processes, significantly reducing the production rate. This research aims to identify and analyze bottlenecks within a food industry production line using a simulation-based approach. The simulation results of the existing conditions indicate that the packing process is the primary bottleneck. Through an improvement scenario involving a combination of more flexible manual packing machine assignments and the addition of conveyors, the simulation demonstrated that hourly production throughput could increase by 8.6%.
References
Abed, S. Y. (2008). Improving productivity in food processing industries using simulation: a case study. ICS'08: Proceedings of the 12th WSEAS international conference on Systems. https://dl.acm.org/doi/10.5555/1580134.1580277
Attia, E. A., Sobhi, N., Alarjani, A., & Karam, A. (2023). Improving electric motor assembly using one piece flow, ergonomics, and cellular layout. International Journal of Simulation Modelling, 22(2), 255–266. https://doi.org/10.2507/IJSIMM22-2-643
Azwir, H. H., & Pratomo, H. W. (2017). Implementasi Line Balancing untuk Peningkatan Efisiensi di Line Welding Studi Kasus: PT X. Jurnal Rekayasa Teknik Industri, 6(1), 57–64. https://doi.org/10.26593/jrsi.v6i1.2428.57-64
Banks, J., Carson, J. S., Nelson, B. L., & Nicol, D. M. (2005). Discrete-Event System Simulation. Pearson Education.
Bartholdi, J. J., Eisenstein, D. D. (1996). A Production Line that Balances Itself. Operations Research, 44(1), 21–34. https://doi.org/10.1287/opre.44.1.21
Conway, R., Maxwell W., McClain, J. O., Thomas, L. J. (1988). The Role of Work-in-Process Inventory in Serial Production Lines. Operations Research, 36(2), 229–241. https://doi.org/10.1287/opre.36.2.229
Eskandari, H., & Babolmorad, N. (2013). Bottleneck analysis in a pharmaceutical production line using simulation approach. SCSC '13: Proceedings of the 2013 Summer Computer Simulation Conference. https://dl.acm.org/doi/abs/10.5555/2557696.2557711
Goldratt, E. M. (2004). The Goal: A Process of Ongoing Improvement. North River Press.
Grenzfurtner, W., Tizghadam, P., & Gruchmann, T. (2025). Production line balancing and reconfiguration in the food industry: A simulation study from a baked goods manufacturer. Procedia Computer Science, 253, 2684–2692. https://doi.org/10.1016/j.procs.2025.01.328
Groover, M. P. (2015). Automation, Production Systems, and Computer-Integrated Manufacturing. Pearson Higher Education.
Harrell, C., Gosh, B. K. & Bowden, R. O. (2004). Simulation Using Promodel. 2nd ed. Mc. Graw Hill.
Heragu, S. S. (2008). Facilities Design. Taylor & Francis Group.
Hoover, S., & Perry, R. (1990). Simulation: A Problem Solving Approach. Addison-Wesley.
Hopp, W. J., Spearman, M. L. (2011). Factory Physics. Waveland Press.
Knop, K. (2021). Analysing the machines working time utilization for improvement purposes. Production Engineering Archives, 27(2), 137–147. https://doi.org/10.30657/pea.2021.27.18
Krishnan, S., Dev, A. S., Suresh, R., Sumesh, A., & Rameshkumar, K. (2018). Bottleneck identification in a tyre manufacturing plant using simulation analysis and productivity improvement. In Materials Today: Proceedings (Vol. 5). https://doi.org/10.1016/j.matpr.2018.10.270
Law, A. M. (2011). Simulation Modeling and Analysis. McGraw-Hill Education.
Lewis, M. A. (2019). Operations Management: A Research Overview. McGraw-Hill Education.
Li, C., Yu, T., Fan, H.-T., Xiao, G., Arinez, J., & Chang, Q. (2023). Manufacturing Letters Dynamic Bottleneck Identification and Production Loss Evaluation for Assembly Lines. In Manufacturing Letters (Vol. 35). https://doi.org/10.1016/j.mfglet.2023.08.089
Potts, C. N., & Whitehead, J. D. (2001). Workload balancing and loop layout in the design of a flexible manufacturing system. European Journal of Operational Research, 129(2), 326–336. https://doi.org/https://doi.org/10.1016/S0377-2217(00)00230-7
Protzman, C., McNamara J., Protzman, D. (2016). One-Piece Flow vs. Batching: A Guide to Understanding How Continuous Flow Maximizes Productivity and Customer Value. 1st ed. CRC Press.
Robinson, S. (2014). Simulation: the practice of model development and use. Bloomsbury Publishing.
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. https://doi.org/10.1016/j.procs.2022.01.314
Roser, C., Nakano, M., Tanaka M. (2001). A Practical Bottleneck Detection Method. Proceedings of the 2001 Winter Simulation Conference. https://doi.org/10.1109/WSC.2001.977398
Sagwekar, A., Rajhans, N. R., & Hans, N. (2019, February). Workload balancing of assembly line in an automobile manufacturing industry. International Conference on Manufacturing Excellence. https://www.researchgate.net/publication/331248194
Sharda, B., & Bury, S. J. (2010). Bottleneck Analysis of a Chemical Plant using Discrete Event Simulation. Proceedings of the 2010 Winter Simulation Conference. https://doi.org/10.1109/WSC.2010.5678916
Siswanto, N., Latiffianti, E., Wiratno, S. E. (2017). Simulasi Sistem Diskrit Implementasi dengan Software Arena. ITS Tekno Sains.
Velumani, S., & Tang, H. (2017). Operations Status and Bottleneck Analysis and Improvement of a Batch Process Manufacturing Line Using Discrete Event Simulation. Procedia Manufacturing, 10, 100–111. https://doi.org/10.1016/j.promfg.2017.07.033
Vijaya, M. A., & Amirthavarshini, V. (2025). Effectiveness of Single Piece Flow Implementation in Assembly Line Operations. International journal of scientific research in engineering and management, 09(05), 1–9. https://doi.org/10.55041/IJSREM46931
Zahraee, S. M., Golroudbary, S. R., Hashemi, A., Afshar, J., & Haghighi, M. (2014). Simulation of manufacturing production line based on Arena. Advanced Materials Research, 933, 744–748. https://doi.org/10.4028/www.scientific.net/AMR.933.744
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