Research Article
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Year 2025, Volume: 14 Issue: 2, 1166 - 1181, 30.06.2025
https://doi.org/10.17798/bitlisfen.1656352

Abstract

References

  • Dalbiçer, Cem. Experimental Analysis of Gearbox Housing Design. Dokuz Eylül University, The Graduate School of Natural and Applied Sciences, Master Thesis, 2016.
  • Mousavi, Sadra. Design of New Type-High Efficiency Magnetic Gear. İstanbul Technical University, Graduate School of Science Engineering and Technology, Master Thesis, 2015.
  • A. Suresh, K.S. Kalyan, K.S. Kumar, K.V. Kumar, V.T. Varma, and B.S. Kumar, “Design and simulation of gearbox for stone crushing ball mill,” Materials Today: Proceedings, vol. 64, pp. 239-245, 2022.
  • K. Mujiburrahman, S. Saravanakumar, and R. Krishnaraj, “Design and analysis of E-glass gearbox housing in tractor and optimization of its design parameters,” Materials Today: Proceedings, vol. 49, pp. 3696-3704, 2022.
  • S.M. Kumar, E. Govindaraj, D. Balamurugan, and F. Daniel, “Design analysis and fabrication of automotive transmission gearbox using hollow gears for weight reduction,” Materials Today: Proceedings, vol. 45, pp. 6822-6832, 2021.
  • B. Sharda, and S.J. Bury, “Evaluating production improvement opportunities in a chemical plant: a case study using discrete event simulation,” Journal of Simulation, vol. 6, no. 2, pp. 81-91, 2012.
  • B. Özcan, and E. Yıldırak, “Bir Üretim Sisteminde Simülasyon Uygulaması,” Aksaray University Journal of Science and Engineering, vol. 4, no. 2, pp. 172-186, 2020.
  • A. Sütçü, O. Karşıyaka, and M.E. Burhan, “Bir mobilya üretim tesisinde iş analizi ve benzetim uygulaması ile süreç verimliliğinin artırılması,” Avrupa Bilim ve Teknoloji Dergisi, vol. 17, pp. 45-57, 2019.
  • R.R. Neeraj, R.P. Nithin, P. Niranjhan, A. Sumesh, and M. Thenarasu, “Modelling and simulation of discrete manufacturing industry,” Materials Today: Proceedings, vol. 5, no. 11, pp. 24971-24983, 2018.
  • E. Cihangir, F.D. Keskin, U.G. Çiçekli, and G. Yakan, “Bir Üretim İşletmesinde Simülasyon Yöntemi ile Darboğaz Analizi ve Sistem İyileştirmesi,” Avrupa Bilim ve Teknoloji Dergisi, vol. 28, pp. 917-923, 2021.
  • D.H. Utku, “The evaluation and improvement of the production processes of an automotive industry company via simulation and optimization,” Sustainability, vol. 15, no. 3, 2023.
  • L.G. Eberle, H. Sugiyama, and R. Schmidt, “Improving lead time of pharmaceutical production processes using Monte Carlo simulation,” Computers & Chemical Engineering, vol. 68, pp. 255-263, 2014.
  • S. Supsomboon, and A. Vajasuvimon, “Simulation model for job shop production process improvement in machine parts manufacturing,” International Journal of Simulation Modelling, vol. 15, no. 4, pp. 611-622, 2016.
  • R. El-Khalil, “Simulation analysis for managing and improving productivity: A case study of an automotive company,” Journal of Manufacturing Technology Management, vol. 26, no. 1, pp. 36-56, 2015.
  • N. Sundararajan, and R. Terkar, “A roadmap to improving productivity in a fastener manufacturing unit by process optimization using ARENA,” Materials Today: Proceedings, vol. 62, pp. 1017-1025, 2022.
  • H. Guzman-Moratto, C. Uribe-Martes, and D. Neira-Rodado, “Improving productivity using simulation: Case study of a mattress manufacturing process,” Procedia Computer Science, vol. 198, pp. 650-655, 2022.
  • M. Kliment, P. Trebuna, M. Pekarcikova, M. Straka, J. Trojan, and R. Duda, “Production efficiency evaluation and products’ quality improvement using simulation,” International Journal of Simulation Modelling, vol. 19, no. 3, pp. 470-481, 2020.
  • A. Skoogh, M. Thürer, M. Subramaniyan, A. Matta, and C. Roser, “Throughput bottleneck detection in manufacturing: a systematic review of the literature on methods and operationalization modes,” Production & Manufacturing Research, vol. 11, no. 1, pp. 2283031, 2023.
  • J. Tang, Z. Dai, W. Jiang, X. Wu, M. Zhuravkov, Z. Xue, and J. Wang, “A comprehensive review of theories, methods, and techniques for bottleneck identification and management in manufacturing systems,” Applied Sciences, vol. 14, no. 17, pp. 7712, 2024.
  • S. Velumani, and H. Tang, “Operations status and bottleneck analysis and improvement of a batch process manufacturing line using discrete event simulation,” Procedia Manufacturing, vol. 10, no. 1, pp. 100-111, 2017.
  • S. Krishnan, A.S. Dev, R. Suresh, A. Sumesh, and K. Rameshkumar, “Bottleneck identification in a tyre manufacturing plant using simulation analysis and productivity improvement,” Materials Today: Proceedings, vol. 5, no. 11, pp. 24720-24730, 2018.
  • M. Thürer, L. Ma, M. Stevenson, and C. Roser, “Bottleneck detection in high-variety make-to-Order shops with complex routings: an assessment by simulation,” Production Planning & Control, vol. 33, no. 15, pp. 1481-1492, 2022.
  • G.Z. Li, Z. Xu, S.L. Yan, H.Y. Wang, X.L. Bai, and Z.H. Ren, “Bottleneck identification and alleviation in a blocked serial production line with discrete event simulation: A case study,” Advances in Production Engineering & Management, vol. 15, no. 2, pp. 125-136, 2020.
  • A. Mousavi, E. Isokangas, and I. Dzakpata, “A Simulation-Based Bottleneck Identification Approach for Complex Mining Production Systems,” Mining, Metallurgy & Exploration, doi: 10.1007/s42461-025-01213-4, 2025.
  • S. Sharova, O. Androsova, O. Bezpartochna, and V. Tsypko, “Features of Use of Simulation Modeling When Managing the Production and Economic Systems,” In Distributed Sensing and Intelligent Systems: Proceedings of ICDSIS 2020, Cham: Springer International Publishing, pp. 289-297, 2022.
  • A. Negahban, and J.S. Smith, “Simulation for manufacturing system design and operation: Literature review and analysis,” Journal of Manufacturing Systems, vol. 33, no. 2, pp. 241-261, 2014.
  • M. Jahangirian, T. Eldabi, A. Naseer, L.K. Stergioulas, and T. Young, “Simulation in manufacturing and business: A review,” European Journal of Operational Research, vol. 203, no. 1, pp. 1-13, 2010.
  • S.M. Jeon, and G. Kim, “A survey of simulation modeling techniques in production planning and control (PPC),” Production Planning & Control, vol. 27, no. 5, pp. 360-377, 2016.
  • D. Mourtzis, “Simulation in the design and operation of manufacturing systems: state of the art and new trends,” International Journal of Production Research, vol. 58, no. 7, pp. 1927-1949, 2020.

Analysis and Improvement of Gearbox Manufacturing Process Using Simulation Modelling

Year 2025, Volume: 14 Issue: 2, 1166 - 1181, 30.06.2025
https://doi.org/10.17798/bitlisfen.1656352

Abstract

Industrial valves, which control the flow of fluids such as liquid, gas or vapor, are an essential part of modern industrial processes. The gearboxes used in industrial valves are critical components that optimize power transmission and control. Design and quality of gearboxes have a great impact on efficiency and safety of the processes. In this concern, analyzing gearbox manufacturing processes and carrying out process improvement studies will provide advantages to manufacturers in terms of time, cost and quality. This study aims to analyze and improve the gearbox manufacturing process of an industrial valve manufacturer. To this aim, the current gearbox manufacturing process was simulated and the bottleneck station was identified. In order to overcome the bottleneck, alternative production scenarios such as contract manufacturing and new machine investment were proposed. Afterwards, simulation models for alternative scenarios were developed, taking into account the quality problems that may occur in alternative scenarios and the investment cost associated with the new machine investment. Finally, all alternative production scenarios were compared with the current situation in terms of production quantities, makespan and profit. The results revealed that investing in a new machine is more profitable for the company than contract manufacturing.

Ethical Statement

The study is complied with research and publication ethics.

Thanks

We would like to express our gratitude to Doğuş Vana ve Döküm San. Tic. A.Ş. for their help and support.

References

  • Dalbiçer, Cem. Experimental Analysis of Gearbox Housing Design. Dokuz Eylül University, The Graduate School of Natural and Applied Sciences, Master Thesis, 2016.
  • Mousavi, Sadra. Design of New Type-High Efficiency Magnetic Gear. İstanbul Technical University, Graduate School of Science Engineering and Technology, Master Thesis, 2015.
  • A. Suresh, K.S. Kalyan, K.S. Kumar, K.V. Kumar, V.T. Varma, and B.S. Kumar, “Design and simulation of gearbox for stone crushing ball mill,” Materials Today: Proceedings, vol. 64, pp. 239-245, 2022.
  • K. Mujiburrahman, S. Saravanakumar, and R. Krishnaraj, “Design and analysis of E-glass gearbox housing in tractor and optimization of its design parameters,” Materials Today: Proceedings, vol. 49, pp. 3696-3704, 2022.
  • S.M. Kumar, E. Govindaraj, D. Balamurugan, and F. Daniel, “Design analysis and fabrication of automotive transmission gearbox using hollow gears for weight reduction,” Materials Today: Proceedings, vol. 45, pp. 6822-6832, 2021.
  • B. Sharda, and S.J. Bury, “Evaluating production improvement opportunities in a chemical plant: a case study using discrete event simulation,” Journal of Simulation, vol. 6, no. 2, pp. 81-91, 2012.
  • B. Özcan, and E. Yıldırak, “Bir Üretim Sisteminde Simülasyon Uygulaması,” Aksaray University Journal of Science and Engineering, vol. 4, no. 2, pp. 172-186, 2020.
  • A. Sütçü, O. Karşıyaka, and M.E. Burhan, “Bir mobilya üretim tesisinde iş analizi ve benzetim uygulaması ile süreç verimliliğinin artırılması,” Avrupa Bilim ve Teknoloji Dergisi, vol. 17, pp. 45-57, 2019.
  • R.R. Neeraj, R.P. Nithin, P. Niranjhan, A. Sumesh, and M. Thenarasu, “Modelling and simulation of discrete manufacturing industry,” Materials Today: Proceedings, vol. 5, no. 11, pp. 24971-24983, 2018.
  • E. Cihangir, F.D. Keskin, U.G. Çiçekli, and G. Yakan, “Bir Üretim İşletmesinde Simülasyon Yöntemi ile Darboğaz Analizi ve Sistem İyileştirmesi,” Avrupa Bilim ve Teknoloji Dergisi, vol. 28, pp. 917-923, 2021.
  • D.H. Utku, “The evaluation and improvement of the production processes of an automotive industry company via simulation and optimization,” Sustainability, vol. 15, no. 3, 2023.
  • L.G. Eberle, H. Sugiyama, and R. Schmidt, “Improving lead time of pharmaceutical production processes using Monte Carlo simulation,” Computers & Chemical Engineering, vol. 68, pp. 255-263, 2014.
  • S. Supsomboon, and A. Vajasuvimon, “Simulation model for job shop production process improvement in machine parts manufacturing,” International Journal of Simulation Modelling, vol. 15, no. 4, pp. 611-622, 2016.
  • R. El-Khalil, “Simulation analysis for managing and improving productivity: A case study of an automotive company,” Journal of Manufacturing Technology Management, vol. 26, no. 1, pp. 36-56, 2015.
  • N. Sundararajan, and R. Terkar, “A roadmap to improving productivity in a fastener manufacturing unit by process optimization using ARENA,” Materials Today: Proceedings, vol. 62, pp. 1017-1025, 2022.
  • H. Guzman-Moratto, C. Uribe-Martes, and D. Neira-Rodado, “Improving productivity using simulation: Case study of a mattress manufacturing process,” Procedia Computer Science, vol. 198, pp. 650-655, 2022.
  • M. Kliment, P. Trebuna, M. Pekarcikova, M. Straka, J. Trojan, and R. Duda, “Production efficiency evaluation and products’ quality improvement using simulation,” International Journal of Simulation Modelling, vol. 19, no. 3, pp. 470-481, 2020.
  • A. Skoogh, M. Thürer, M. Subramaniyan, A. Matta, and C. Roser, “Throughput bottleneck detection in manufacturing: a systematic review of the literature on methods and operationalization modes,” Production & Manufacturing Research, vol. 11, no. 1, pp. 2283031, 2023.
  • J. Tang, Z. Dai, W. Jiang, X. Wu, M. Zhuravkov, Z. Xue, and J. Wang, “A comprehensive review of theories, methods, and techniques for bottleneck identification and management in manufacturing systems,” Applied Sciences, vol. 14, no. 17, pp. 7712, 2024.
  • S. Velumani, and H. Tang, “Operations status and bottleneck analysis and improvement of a batch process manufacturing line using discrete event simulation,” Procedia Manufacturing, vol. 10, no. 1, pp. 100-111, 2017.
  • S. Krishnan, A.S. Dev, R. Suresh, A. Sumesh, and K. Rameshkumar, “Bottleneck identification in a tyre manufacturing plant using simulation analysis and productivity improvement,” Materials Today: Proceedings, vol. 5, no. 11, pp. 24720-24730, 2018.
  • M. Thürer, L. Ma, M. Stevenson, and C. Roser, “Bottleneck detection in high-variety make-to-Order shops with complex routings: an assessment by simulation,” Production Planning & Control, vol. 33, no. 15, pp. 1481-1492, 2022.
  • G.Z. Li, Z. Xu, S.L. Yan, H.Y. Wang, X.L. Bai, and Z.H. Ren, “Bottleneck identification and alleviation in a blocked serial production line with discrete event simulation: A case study,” Advances in Production Engineering & Management, vol. 15, no. 2, pp. 125-136, 2020.
  • A. Mousavi, E. Isokangas, and I. Dzakpata, “A Simulation-Based Bottleneck Identification Approach for Complex Mining Production Systems,” Mining, Metallurgy & Exploration, doi: 10.1007/s42461-025-01213-4, 2025.
  • S. Sharova, O. Androsova, O. Bezpartochna, and V. Tsypko, “Features of Use of Simulation Modeling When Managing the Production and Economic Systems,” In Distributed Sensing and Intelligent Systems: Proceedings of ICDSIS 2020, Cham: Springer International Publishing, pp. 289-297, 2022.
  • A. Negahban, and J.S. Smith, “Simulation for manufacturing system design and operation: Literature review and analysis,” Journal of Manufacturing Systems, vol. 33, no. 2, pp. 241-261, 2014.
  • M. Jahangirian, T. Eldabi, A. Naseer, L.K. Stergioulas, and T. Young, “Simulation in manufacturing and business: A review,” European Journal of Operational Research, vol. 203, no. 1, pp. 1-13, 2010.
  • S.M. Jeon, and G. Kim, “A survey of simulation modeling techniques in production planning and control (PPC),” Production Planning & Control, vol. 27, no. 5, pp. 360-377, 2016.
  • D. Mourtzis, “Simulation in the design and operation of manufacturing systems: state of the art and new trends,” International Journal of Production Research, vol. 58, no. 7, pp. 1927-1949, 2020.
There are 29 citations in total.

Details

Primary Language English
Subjects Industrial Engineering
Journal Section Research Article
Authors

Bilal Coşkun This is me 0000-0002-3528-5718

Hülya Güçdemir 0000-0002-1993-5848

Early Pub Date June 27, 2025
Publication Date June 30, 2025
Submission Date March 12, 2025
Acceptance Date May 29, 2025
Published in Issue Year 2025 Volume: 14 Issue: 2

Cite

IEEE B. Coşkun and H. Güçdemir, “Analysis and Improvement of Gearbox Manufacturing Process Using Simulation Modelling”, Bitlis Eren Üniversitesi Fen Bilimleri Dergisi, vol. 14, no. 2, pp. 1166–1181, 2025, doi: 10.17798/bitlisfen.1656352.

Bitlis Eren University
Journal of Science Editor
Bitlis Eren University Graduate Institute
Bes Minare Mah. Ahmet Eren Bulvari, Merkez Kampus, 13000 BITLIS