Reduce Transportation Costs Using the Milk-run System and Dynamo Stages in the Vehicle Manufacturing Industry

Authors

  • Indra Setiawan Department of Production and Manufacture Engineering, ASTRA Polytechnic, Bekasi, Indonesia
  • Hibarkah Kurnia Department of Industrial Engineering, Universitas Pelita Bangsa, Bekasi, Indonesia
  • Setiawan Setiawan Department of Industrial Engineering, Universitas Mercu Buana, Jakarta, Indonesia
  • Humiras Hardi Purba Department of Industrial Engineering, Universitas Mercu Buana, Jakarta, Indonesia
  • Hernadewita Hernadewita Department of Industrial Engineering, University Mercu Buana, Jakarta, Indonesia

DOI:

https://doi.org/10.31181/oresta240622030s

Keywords:

Covid-19, Dynamo , Milk-run, Transportation Cost, Vehicle Industry

Abstract

The vehicle manufacturing industry is one of the automotive industries in Indonesia that produces four-wheeled vehicles with the main product being cars. The vehicle manufacturing industry has several sub-companies including Vehicle Manufacturers (VM) and Vehicle Sales (VS). The VM industry is experiencing problems with rising transportation operating costs. The same thing is also experienced by the corporate company such as VS. In 2020, transportation operational costs incurred by the company exceed the target, which can cause losses for the company. The purpose of this study is to find the cause of the problem and improve the transportation operational costs that continue to increase so that the company gets a reduction in transportation costs. The implementation of the improvement concept is carried out using the Dynamo++ stages starting from pre-study until the implementation of improvements. Through improvements to the milk-run system, it was found that vehicle manufacturers and vehicle sales benefited from a reduction in transportation costs of 77,861 USD or a decrease of 79.3%.

Downloads

Download data is not yet available.

References

Adriano, D. D., Montez, C., Novaes, A. G. N., & Wangham, M. (2020). Dmrvr: Dynamic milk-run vehicle routing solution using fog-based vehicular ad hoc networks. Electronics (Switzerland), 9(12), 1–24. https://doi.org/10.3390/electronics9122010

Baalsrud Hauge, J., Zafarzadeh, M., Jeong, Y., Li, Y., Ali Khilji, W., Larsen, C., & Wiktorsson, M. (2021). Digital Twin Testbed and Practical Applications in Production Logistics with Real-Time Location Data. International Journal of Industrial Engineering and Management, 12(2), 129–140. https://doi.org/10.24867/IJIEM-2021-2-282

Bajic, B., Suzic, N., Simeunovic, N., Moraca, S., & Rikalovic, A. (2020). Real-time Data Analytics Edge Computing Application for Industry 4.0: The Mahalanobis-Taguchi Approach. International Journal of Industrial Engineering and Management, 11(3), 146–156. https://doi.org/10.24867/IJIEM-2020-3-260

Biswas, T. K., & Das, M. C. (2020). Selection of the barriers of supply chain management in Indian manufacturing sectors due to Covid-19 impacts. Operational Research in Engineering Sciences: Theory and Applications, 3(3), 1–12. https://doi.org/10.31181/oresta2030301b

Bocewicz, G., Bozejko, W., Wójcik, R., & Banaszak, Z. (2019). Milk-run routing and scheduling subject to a trade-off between vehicle fleet size and storage capacity. Management and Production Engineering Review, 10(3), 41–53. https://doi.org/10.24425/mper.2019.129597

Hendra, Setiawan, I., Hernadewita, & Hermiyetti. (2021). Evaluation of Product Quality Improvement Against Waste in the Electronic Musical Instrument Industry. Jurnal Ilmiah Teknik Elektro Komputer Dan Informatika, 7(3), 402–411. https://doi.org/10.26555/jiteki.v7i3.21904

Herlambang, H., Purba, H. H., & Jaqin, C. (2021). Development of machine vision to increase the level of automation in indonesia electronic component industry. Journal Europeen Des Systemes Automatises, 54(2), 253–262. https://doi.org/10.18280/JESA.540207

Klenk, E., & Galka, S. (2019). Analysis of real-time tour building and scheduling strategies for in-plant milk-run systems with volatile transportation demand. IFAC-PapersOnLine, 52(13), 2110–2115. https://doi.org/10.1016/J.IFACOL.2019.11.517

Kluska, K., & Pawlewski, P. (2018). The use of simulation in the design of Milk-Run intralogistics systems. IFAC-PapersOnLine, 51(11), 1428–1433. https://doi.org/10.1016/J.IFACOL.2018.08.314

Kurnia, H., Jaqin, C., & Manurung, H. (2022). Implemantation of the DMAIC Approach for Quality Improvement at the Elastic Tape Industry. J@ti Undip: Jurnal Teknik Industri, 17(1), 40–51. https://doi.org/10.14710/jati.17.1.40-51

Kurnia, H., Jaqin, C., Purba, H. H., & Setiawan, I. (2021). Implementation of Six Sigma in the DMAIC Approach for Quality Improvement in the Knitting Socks Industry. Tekstilvemuhendis, 28(124), 269–278. https://doi.org/10.7216/1300759920212812403

Mácsay, V., & Bányai, T. (2017). Toyota Production System in Milkrun Based in-Plant Supply. Journal of Production Engineering, 20(1), 141–146. https://doi.org/10.24867/jpe-2017-01-141

Mao, Z., Huang, D., Fang, K., Wang, C., & Lu, D. (2020). Milk-run routing problem with progress-lane in the collection of automobile parts. Annals of Operations Research, 291(1–2), 657–684. https://doi.org/10.1007/s10479-019-03218-x

Mei, H., Jingshuai, Y., Teng, M., Xiuli, L., & Ting, W. (2017). The Modeling of Milk-run Vehicle Routing Problem Based on Improved C-W Algorithm that Joined Time Window. Transportation Research Procedia, 25, 716–728. https://doi.org/10.1016/j.trpro.2017.05.453

Mirzaei, N., Nejad, M. G., & Fernandes, N. O. (2021). Combining Line Balancing Methods and Discrete Event Simulation: A Case Study from a Metalworking Company. International Journal of Industrial Engineering and Management, 12(1), 14–24. https://doi.org/10.24867/IJIEM-2020-1-273

Muhammad, M., Baig, U., Ali, Y., & Rehman, O. U. (2022). Enhancing Resilience of Oil Supply Chain in the Context of Developing Contries. Operational Research in Engineering Sciences: Theory and Applications, 5(1), 69–89. https://doi.org/10.31181/oresta210322091b

Pattanaik, L. N. (2021). Simulation Optimization of Manufacturing Takt Time for a Leagile Supply Chain with a De-coupling Point. International Journal of Industrial Engineering and Management, 12(2), 102–114. https://doi.org/10.24867/IJIEM-2021-2-280

Purba, H. H., Fitra, A., & Nindiani, A. (2019). Control and integration of milk-run operation in Japanese automotive company in Indonesia. Management and Production Engineering Review, 10(1), 79–88. https://doi.org/10.24425/mper.2019.128246

Ranjbaran, F., Husseinzadeh Kashan, A., & Kazemi, A. (2020). Mathematical formulation and heuristic algorithms for optimisation of auto-part milk-run logistics network considering forward and reverse flow of pallets. International Journal of Production Research, 58(6), 1741–1775. https://doi.org/10.1080/00207543.2019.1617449

Setiawan, S., Setiawan, I., Jaqin, C., Prabowo, H. A., & Purba, H. H. (2021). Integration of Waste Assessment Model and Lean Automation to Improve Process Cycle Efficiency in the Automotive Industry. Quality Innovation Prosperity, 25(3), 48–64. https://doi.org/10.12776/qip.v25i3.1613

Shobur, M., Nurmutia, S., & Pratama, G. A. (2021). Optimization of Staple Products Using the Supply Chain Operation Reference (SCOR) To Customer Satisfaction in Central Java. Sinergi, 25(3), 269. https://doi.org/10.22441/sinergi.2021.3.004

Suratno, & Ichtiarto, B. P. (2021). Reduce Carbon Emissions of Logistic Transportation Using Eight Steps Approach in Indonesian Automotive Industry. Journal Europeen Des Systemes Automatises, 54(6), 819–826. https://doi.org/10.18280/jesa.540603

Tellini, T., Silva, F. J. G., Pereira, T., Morgado, L., Campilho, R. D. S. G., & Ferreira, L. P. (2019). Improving in-plant logistics flow by physical and digital pathways. Procedia Manufacturing, 38(2019), 965–974. https://doi.org/10.1016/j.promfg.2020.01.180

Urru, A., Bonini, M., & Echelmeyer, W. (2018). Planning and dimensioning of a milk-run transportation system considering the actual line consumption. IFAC-PapersOnLine, 51(9), 404–409. https://doi.org/10.1016/j.ifacol.2018.07.066

Yuik, C. J., & Puvanasvaran, P. (2020). Development of Lean Manufacturing Implementation Framework in Machinery and Equipment SMEs. International Journal of Industrial Engineering and Management, 11(3), 157–169. https://doi.org/10.24867/IJIEM-2020-3-261

Published

2022-06-24

How to Cite

Setiawan, I., Kurnia, H., Setiawan, S., Purba, H. H., & Hernadewita, H. (2022). Reduce Transportation Costs Using the Milk-run System and Dynamo Stages in the Vehicle Manufacturing Industry. Operational Research in Engineering Sciences: Theory and Applications, 5(2), 17–27. https://doi.org/10.31181/oresta240622030s

Most read articles by the same author(s)