Selective Waiting-Time Reduction in Indonesian Fiberglass Shipbuilding: A Digital Lean Simulation Framework
DOI:
https://doi.org/10.59261/jequi.v8i5.470Keywords:
AnyLogic, Discrete-Event Simulation, Fiberglass Shipbuilding, Selective Waiting-Time Reduction, Value Stream MappingAbstract
Background: Uniform waiting-time reduction in fiberglass shipbuilding may compromise essential technical processes, including curing, inspection, and safety checks. Therefore, waiting time must be classified according to its technical function and potential for reduction.
Objective: This study develops a simulation-based Digital Lean Manufacturing framework for selectively reducing waiting time in Indonesian engineer-to-order fiberglass shipbuilding.
Methods: A single-case study was conducted at PT Teluk Naga Bahari, Indonesia, covering eleven production stages. Value Stream Mapping (VSM) was integrated with deterministic discrete-event simulation using AnyLogic. Waiting time was classified into avoidable waiting (AW), reducible technical waiting (RTW), and fixed technical waiting (FTW). Five scenarios (S0–S4) were evaluated using waiting time, lead time, and Process Cycle Efficiency (PCE).
Results: The baseline recorded a cycle time of 157 days, waiting time of 67 days, lead time of 224 days, and PCE of 70.09%. Waiting time comprised 15 days of AW (22.39%), 24 days of RTW (35.82%), and 28 days of FTW (41.79%). Scenario S4 achieved the greatest simulated improvement, reducing waiting time to 44 days and lead time to 189 days while increasing PCE to 76.72%. Lead time decreased by 15.63%, while FTW was preserved.
Conclusion: Selective waiting-time classification enables targeted efficiency improvements while preserving essential technical constraints. However, simulated reductions in RTW require material and process validation before implementation. The framework provides a transferable decision-making approach for fiberglass shipyards.
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Adly Ishak, F., Khudri Johari, M., & Dolah, R. (2018). A case study of LEAN application for shortest lead time in composite repair shop. International Journal of Engineering & Technology, 7(4.13), 112–119. https://doi.org/10.14419/ijet.v7i4.13.21341
Ahmad, A. W., Darsin, M., Sakinah, W., & Puspita, H. I. D. (2026). Optimasi produktivitas material kapal melalui implementasi lean tools ( value stream mapping). Prosiding SEMNAS INOTEK (Seminar Nasional Inovasi Teknologi), 10(3). https://doi.org/10.29407/0zrma225
Antonelli, D., & Stadnicka, D. (2018). Combining factory simulation with value stream mapping: a critical discussion. Procedia CIRP, 67, 30–35. https://doi.org/10.1016/j.procir.2017.12.171
Arey, D., Le, C. H., & Gao, J. (2021). Lean industry 4.0: a digital value stream approach to process improvement. Procedia Manufacturing, 54, 19–24. https://doi.org/10.1016/j.promfg.2021.07.004
Arif, M. S., Gunbeyaz, S. A., Kurt, R. E., Supomo, H., & Pribadi, T. W. (2026). Bridging the gap: A review of simulation approaches in multipurpose Shipyard integrating shipbuilding, repair, and recycling. Ocean Engineering, 351, 124303. https://doi.org/10.1016/j.oceaneng.2026.124303
Ferreira, W. de P., Armellini, F., Santa-Eulalia, L. A. de, & Thomasset-Laperrière, V. (2022). Extending the lean value stream mapping to the context of Industry 4.0: An agent-based technology approach. Journal of Manufacturing Systems, 63, 1–14. https://doi.org/10.1016/j.jmsy.2022.02.002
Hansen, M. J., Vaagen, H., & van Oorschot, K. (2020). Team Collective Intelligence in Dynamically Complex Projects—A Shipbuilding Case. Project Management Journal, 51(6). https://doi.org/10.1177/8756972820928695
Ismail, A., Ma’ruf, B., Zubaydi, A., Octavanny, M. A. D., & Ginta, T. L. (2024). Strength assessment of fiberglass layer configurations in FRP ship materials from yard practices using a statistical approach. Curved and Layered Structures, 11(1). https://doi.org/10.1515/cls-2024-0007
Kolich, D., Storch, R. L., & Fafandjel, N. (2017). Lean Methodology to Transform Shipbuilding Panel Assembly. Journal of Ship Production and Design, 33(04), 317–326. https://doi.org/10.5957/JSPD.160028
Mrabti, A., Bouajaja, S., & Nouri, K. (2025). Digital Value Stream Mapping through Simulation in the Automotive Wiring Industry. WPOM-Working Papers on Operations Management, 16. https://doi.org/10.4995/wpom.23686
Muharom, R., Alamsyah, Hidayat, T., & Syahab, H. (2024). The Influence of Fiberglass Fiber Arrangement Variations on the Tensile and Bending Strength of Ships. Indonesian Journal of Maritime Technology, 2(2). https://doi.org/10.35718/ismatech.v2i2.1203
Neves, A., Erikstad, S. O., & Godina, R. (2025). Enhancing efficiency and sustainability in shipbuilding: insights from lean implementation and challenges. Journal of Marine Science and Technology, 30(3), 575–616. https://doi.org/10.1007/s00773-025-01078-8
Nor Azian, A. A., Che Mamat, R., Ibrahim, D., & Abu, F. (2025). Lean Manufacturing and Industry 4.0: Unveiling Trends, Applications, and Global Impacts in Manufacturing Through Comprehensive Literature Review. Jurnal Kejuruteraan, 37(1), 151–165. https://doi.org/10.17576/jkukm-2025-37(1)-10
Okubo, Y., & Mitsuyuki, T. (2022). Ship Production Planning Using Shipbuilding System Modeling and Discrete Time Process Simulation. Journal of Marine Science and Engineering, 10(2), 176. https://doi.org/10.3390/jmse10020176
Oliveira, A., & Gordo, J. M. (2018). Lean tools applied to a shipbuilding panel line assembling process. Brodogradnja, 69(4), 53–64. https://doi.org/10.21278/brod69404
Praharsi, Y., Jami’in, M. A., Suhardjito, G., Reong, S., & Wee, H. M. (2022). Supply chain performance for a traditional shipbuilding industry in Indonesia. Benchmarking, 29(2). https://doi.org/10.1108/BIJ-05-2020-0232
Saputra, H., Cahyagi, D., Perkasa, V. N., Purnama, D., Nurmannsyah, O., Saputra, R., Ferari, R., Al Fauzy, F. I., & Fadillah, M. (2024). Design and Fabrication of 6 Meter Fiberglass Boat for Coastal Water Tourism in Batam. International Journal of Marine Engineering Innovation and Research, 9(2). https://doi.org/10.12962/j25481479.v9i2.20342
Sargent, R. G. (2013). Verification and validation of simulation models. Journal of Simulation, 7(1), 12–24. https://doi.org/10.1057/jos.2012.20
Sharma, S., & Gandhi, P. J. (2017). Scope and Impact of Implementing Lean Principles & Practices in Shipbuilding. Procedia Engineering, 194, 232–240. https://doi.org/10.1016/j.proeng.2017.08.140
Strandhagen, J. W., Buer, S. V., Semini, M., Alfnes, E., & Strandhagen, J. O. (2022). Sustainability challenges and how Industry 4.0 technologies can address them: a case study of a shipbuilding supply chain. Production Planning and Control, 33(9–10). https://doi.org/10.1080/09537287.2020.1837940
Woldemicael, W. W., Berhan, E., Kitaw, D., & Tesfaye, G. (2024). Enhancing operation efficiency of leather manufacturing industry through hybrid of value stream mapping and discrete event simulation. Cogent Engineering, 11(1). https://doi.org/10.1080/23311916.2024.2375423
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