OPTIMASI DISTRIBUSI KONVEKSI PAKAIAN DENGAN PENDEKATAN SIMULASI (STUDI KASUS CV. XYZ)
Keywords:
Distribution, System Simulation, PromodelAbstract
One of the biggest challenges faced by garment manufacturing companies is optimizing the distribution of products to improve operational efficiency and minimize costs. Timely and effective distribution is crucial to ensure customer satisfaction and maintain the company's competitiveness. Therefore, efforts need to be made to optimize the distribution system in garment manufacturing companies by utilizing the latest technology, one of which is through simulation approaches. The aim of this research is to apply simulation to optimize the clothing distribution at CV. XYZ and provide recommendations for improving efficiency and reducing distribution costs. To achieve the research objectives, a case related to the distribution system was selected and analyzed in depth, specifically at CV. XYZ. To analyze this case, this research employs a case study strategy focusing on data collection from relevant distribution systems.
One of the tools used to describe the distribution process systematically is a flowchart, which provides a visual overview of the sequence and relationships between various stages in the distribution process. The simulation results indicate that the distribution system at CV. XYZ could be improved by increasing the schedule from once to twice, rather than by adding distribution units. In terms of costs, this approach reduces the expenses, with the additional schedule only adding a fuel cost of IDR 46,800,000, while adding units would incur a cost of IDR 615,600,000.
Downloads
References
Vaghefi, A. & Sarhangian, V. Contribution of simulation to the optimization of inspection plans for multi-stage manufacturing systems. Comput. Ind. Eng. 57(4), 1226–1234. (2009).
Werker, G., Saure, A., French, J. & Shechter, S. The use of discrete-event simulation modeling to improve radiation therapy planning
process. Radiother. Oncol. 92(1), 76–82. (2009).
Jayant, A., Gupta, P. & Garg, S. K. Simulation modeling and analysis on network design for closed-loop supply chain: A case study battery industry. Procedia Eng. 97, 2213–2221. (2014).
Mourtzis, D., Papakostas, N., Mavrikios, D., Makris, S. & Alexopoulos, K. The role of simulation in digital manufacturing: applications and outlook. Int. J. Comput. Integr. Manuf. (IJCIM) 28(1), 3–24. https:// doi. org/ 10. 1080/ 09511 92X. 2013. 800234 (2015).
Eftonova, T., Kiran, M. & Stannett, M. Long-term macroeconomic dynamics of competition in the Russian economy using agentbased modeling. Int. J. Syst. Dyn. Appl. (IJSDA) 6(1), 1–20. (2017).
Bhushan, S. System dynamics base-model of humanitarian supply chain (HSCM) in disaster prone eco-communities of India: A discussion on simulation and scenario results. Int. J. Syst. Dyn. Appl. (IJSDA) 6(3), 20–37. (2017).
Jiménez-Rolland M., Macías-Ponce .C., rtínez-Álvarez .F. (2020). Using simulation in the assessment of voting procedures: an epistemic instrumental approach. SIMULATION, 98(2), 127-144.
ITO T., RAHMAN M.S.A., MOHAMAD E., RAHMAN A.A.A., SALLEH M.R. (2020). Internet of things and simulation approach for decision support system in lean manufacturing. Journal of Advanced Mechanical Design, Systems, and Manufacturing, 14(2), JAMDSM0027.
Nunes V.A., Barbosa G.F. (2020). Simulation-based analysis of AGV workload used on aircraft manufacturing system: a theoretical approach. Acta Scientiarum. Technology, 42.
Santos R., Toscano C., e Sousa J.P. (2021). A new Simulation-Based Approach in the Design of Manufacturing Systems and Real-Time Decision Making. IFAC-PapersOnLine, 54(1), 282-287.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2024 Anisa Pauziah, Diki Muchtar, Muhamad Ihsan, Tarman
This work is licensed under a Creative Commons Attribution 4.0 International License.