Nitelikli Karton Üretiminde Üretim Hattı Modellemesinin Güvenilirlik Analizi ile Değerlendirilmesi
Year 2025,
Volume: 59 Issue: 1, 167 - 184, 22.01.2025
Aykut Güleryüz
,
Hüseyin Ünözkan
,
Mehmet Yılmaz
Abstract
Amaç: Üretim hatlarının uzun vadeli üretim beklentisini hesaplamak için yeni bir model geliştirmek ve bu modelin üretim planlama ve kontrolünde nasıl kullanılabileceğini göstermektir.
Yöntem: Üretim hattında mekanik birimlerin değerlendirilmesi ve performans ölçümü üzerine odaklanarak iyileştirme çabalarını ölçmek için gerçek veri setlerinden yararlanarak geçiş olasılıklarının hesaplanması ve uzun vadeli üretim kapasitesinin belirlenmesini içermektedir. Bu hesaplamalar, Markov Zinciri ve güvenilirlik analizi gibi yöntemler kullanılarak yapılmaktadır.
Bulgular: Altı üretim hattına sahip bir işletme için uzun vadeli bir üretim beklentisini yüksek doğruluk oranı ile kestirebilmektedir.
Özgünlük: Çalışmada önerilen modelin ve metodun, düzenli verinin tutulduğu herhangi bir üretim hattı problemini etkili bir şekilde çözebileceği düşünülmektedir.
References
- Ágota, B. (2023). “Decision Making in Operator-Machine Assignment Problems: An Optimization Approach in U-Shaped Production Lines”, Decision Making: Applications in Management and Engineering, 6(2), 620-638. https://doi.org/10.31181/dmame622023808
- Akyol Özer, E., Coşkun, E.E., Bulut, Ö., Toy, E.S. (2021). “Bir Tekstil Fabrikasinda Montaj Hattı Dengeleme ve Performansa Dayalı İşçi Atama Problemi”, Endüstri Mühendisliği, 32(2), 235-250. https://doi.org/10.46465/endustrimuhendisligi.868101
- Alaouchiche, Y., Ouazene, Y. and Yalaoui, F., (2020). "Economic and Energetic Performance Evaluation of Unreliable Production Lines: An Integrated Analytical Approach," IEEE Access, 8, 185330-185345. https://doi.org/10.1109/ACCESS.2020.3029761
- Ballarini, P. and Horváth, A., (2021). "Formal Analysis of Production Line Systems by Probabilistic Model Checking Tools", 26th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA), Vasteras,
Sweden, 1-8. https://doi.org/10.1109/ETFA45728.2021.9613494
- Duan, W., Dai, W., Wang, Y. and Sun, J. (2020). “Reliability Analysis and Optimization of Production System for Production Scheduling”, IOP Conference Series: Materials Science and Engineering, 1043, 032025. https://doi.org/10.1088/1757-899X/1043/3/032025
- Ergüt, Ö. (2019). “Üretim Sistemlerinde Bir Simülasyon Uygulaması”, Osmaniye Korkut Ata Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 3(2), 244-258.
- Hadžić, N., Ložar, V., Opetuk, T.İ. and Cajner, H. (2021). “Improvability of the Fabrication Line in A Shipyard”, Brodogradnja, 72(3), 13-28. https://doi.org/10.21278/brod72302
- Imseitif, J., Tang, H. and Smith, M. (2019). “Throughput Analysis of Manufacturing Systems with Buffers Considering Reliability and Cycle Time Using DES and DOE”, Procedia Manufacturing 39, 814-823. https://doi.org/10.1016/j.promfg.2020.01.423
- Kang, N., Zhao, C., Li, J. and Zheng, L. (2017). "A Sub-Optimal Control Policy in a Two-Product Door Manufacturing Line with Geometric Reliability Machines", IEEE Robotics and Automation Letters,2(1), 157-164, https://doi.org/10.1109/LRA.2016.2582925
- Kang, Y., Yan, H. and Ju, F. (2020). "Performance Evaluation of Production Systems Using Real-Time Machine Degradation Signals", IEEE Transactions on Automation Science and Engineering, 17(1), 273-283. https://doi.org/10.1109/TASE.2019.2920874
- Karishma, A. and Supachai, V., (2023). “A Hidden Semi-Markov Model for Predicting Production Cycle Time Using Bluetooth Low Energy Data”, Advances in Technology Innovation, 8(4), 241–253.
- Kozłowski, E., Borucka, A., Oleszczuk, P. and Jałowiec, T., (2023). “Evaluation of the maintenance system readiness using the semi-Markov model taking into account hidden factors”, Eksploatacja i Niezawodnosc – Maintenance and Reliability, 25(4). http://doi.org/10.17531/ein/172857
- Liberopoulos, G. and Tsarouhas, P. (2005). “Reliability Analysis of An Automated Pizza Production Line”, Journal of Food Engineering, 69, 79-96. https://doi.org/10.1016/j.jfoodeng.2004.07.014
- Öz, D., Edizkan, R. and Yazici, A. (2023). “Seri Üretim Hatlarinda Güvenilirlik Analizi Ile Durumsal Farkındalığın Artırılması”, Eskişehir Osmangazi Üniversitesi Mühendislik Ve Mimarlık Fakültesi Dergisi, 31(2), 630-643. https://doi.org/10.31796/ogummf.1192034
- Pérez-Lechuga, G., Venegas-Martínez, F. and Martínez-Sánchez, J.F. (2021). “Mathematical Modeling of Manufacturing Lines with Distribution by Process: A Markov Chain Approach”, Mathematics, 9(24), 3269. https://doi.org/10.3390/math9243269
- Pinsky, M.A. and Karlin, S. (2011). “An Introduction to Stochastic Modeling” (Fourth Edition), Elsevier.
- Savsar, M. (2016). “Reliability and Availability Analysis of A Manufacturing Line System”, Journal of Applied and
Physical Sciences. 2(3), 96-106. https://doi.org/10.20474/japs-2.3.5
- Tsarouhas, P.H. and Arvanitoyannis, I.S. (2014). “Yogurt Production Line: Reliability Analysis”, Production & Manufacturing Research: 2(1), 11-23.
- Ünözkan, H. and Yılmaz, M. (2021). “A Stochastic Approach to a Combined Parallel System”, International Journal of Applied Mathematics and Statistics, 60(1), 81-87.
- Yang, Z., Li, J., Chen, C., He, J., Tian, H. and Yu, L. (2021). “A Study on Overall Line Efficiency (OLE) Centered Production Line Maintenance Prioritization Considering Equipment Operational Reliability”, The International Journal of Advanced Manufacturing Technology, 124, 3783-3794. https://doi.org/10.1007/s00170-021-07547-9
- Zhang, Y., Cheng, Y., Wang, X.V., Zhong, R.Y., Zhang, Y. and Tao, F. (2019). “Data-Driven Smart Production Line and Its Common Factors”, The International Journal of Advanced Manufacturing Technology, 103, 1211-1223. https://doi.org/10.1007/s00170-019-03469-9
- Zhao, C., Li, J., Huang, N. and Horst, J.A., (2017) "Flexible Serial Lines with Setups: Analysis, Improvement, and Application," in IEEE Robotics and Automation Letters, 2(1), 120-127, https://doi.org/10.1109/LRA.2016.2556078
Evaluation of Production Line Modelling in Qualified Cardboard Production with Reliability Analysis
Year 2025,
Volume: 59 Issue: 1, 167 - 184, 22.01.2025
Aykut Güleryüz
,
Hüseyin Ünözkan
,
Mehmet Yılmaz
Abstract
Purpose: To develop a new model for calculating the long-term production expectation of production lines and to show how this model can be used in production planning and control.
Methodology: The methodology leverages real-world data to assess mechanical unit performance and improvement efforts. By calculating transition probabilities and employing Markov Chain and reliability analysis, it predicts long-term production capacity for the production line.
Findings: It can predict long-term production expectations with high accuracy for a business with six production lines.
Originality: The proposed model and method in this current study are capable of effectively addressing any production line problem where regular data is maintained.
References
- Ágota, B. (2023). “Decision Making in Operator-Machine Assignment Problems: An Optimization Approach in U-Shaped Production Lines”, Decision Making: Applications in Management and Engineering, 6(2), 620-638. https://doi.org/10.31181/dmame622023808
- Akyol Özer, E., Coşkun, E.E., Bulut, Ö., Toy, E.S. (2021). “Bir Tekstil Fabrikasinda Montaj Hattı Dengeleme ve Performansa Dayalı İşçi Atama Problemi”, Endüstri Mühendisliği, 32(2), 235-250. https://doi.org/10.46465/endustrimuhendisligi.868101
- Alaouchiche, Y., Ouazene, Y. and Yalaoui, F., (2020). "Economic and Energetic Performance Evaluation of Unreliable Production Lines: An Integrated Analytical Approach," IEEE Access, 8, 185330-185345. https://doi.org/10.1109/ACCESS.2020.3029761
- Ballarini, P. and Horváth, A., (2021). "Formal Analysis of Production Line Systems by Probabilistic Model Checking Tools", 26th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA), Vasteras,
Sweden, 1-8. https://doi.org/10.1109/ETFA45728.2021.9613494
- Duan, W., Dai, W., Wang, Y. and Sun, J. (2020). “Reliability Analysis and Optimization of Production System for Production Scheduling”, IOP Conference Series: Materials Science and Engineering, 1043, 032025. https://doi.org/10.1088/1757-899X/1043/3/032025
- Ergüt, Ö. (2019). “Üretim Sistemlerinde Bir Simülasyon Uygulaması”, Osmaniye Korkut Ata Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 3(2), 244-258.
- Hadžić, N., Ložar, V., Opetuk, T.İ. and Cajner, H. (2021). “Improvability of the Fabrication Line in A Shipyard”, Brodogradnja, 72(3), 13-28. https://doi.org/10.21278/brod72302
- Imseitif, J., Tang, H. and Smith, M. (2019). “Throughput Analysis of Manufacturing Systems with Buffers Considering Reliability and Cycle Time Using DES and DOE”, Procedia Manufacturing 39, 814-823. https://doi.org/10.1016/j.promfg.2020.01.423
- Kang, N., Zhao, C., Li, J. and Zheng, L. (2017). "A Sub-Optimal Control Policy in a Two-Product Door Manufacturing Line with Geometric Reliability Machines", IEEE Robotics and Automation Letters,2(1), 157-164, https://doi.org/10.1109/LRA.2016.2582925
- Kang, Y., Yan, H. and Ju, F. (2020). "Performance Evaluation of Production Systems Using Real-Time Machine Degradation Signals", IEEE Transactions on Automation Science and Engineering, 17(1), 273-283. https://doi.org/10.1109/TASE.2019.2920874
- Karishma, A. and Supachai, V., (2023). “A Hidden Semi-Markov Model for Predicting Production Cycle Time Using Bluetooth Low Energy Data”, Advances in Technology Innovation, 8(4), 241–253.
- Kozłowski, E., Borucka, A., Oleszczuk, P. and Jałowiec, T., (2023). “Evaluation of the maintenance system readiness using the semi-Markov model taking into account hidden factors”, Eksploatacja i Niezawodnosc – Maintenance and Reliability, 25(4). http://doi.org/10.17531/ein/172857
- Liberopoulos, G. and Tsarouhas, P. (2005). “Reliability Analysis of An Automated Pizza Production Line”, Journal of Food Engineering, 69, 79-96. https://doi.org/10.1016/j.jfoodeng.2004.07.014
- Öz, D., Edizkan, R. and Yazici, A. (2023). “Seri Üretim Hatlarinda Güvenilirlik Analizi Ile Durumsal Farkındalığın Artırılması”, Eskişehir Osmangazi Üniversitesi Mühendislik Ve Mimarlık Fakültesi Dergisi, 31(2), 630-643. https://doi.org/10.31796/ogummf.1192034
- Pérez-Lechuga, G., Venegas-Martínez, F. and Martínez-Sánchez, J.F. (2021). “Mathematical Modeling of Manufacturing Lines with Distribution by Process: A Markov Chain Approach”, Mathematics, 9(24), 3269. https://doi.org/10.3390/math9243269
- Pinsky, M.A. and Karlin, S. (2011). “An Introduction to Stochastic Modeling” (Fourth Edition), Elsevier.
- Savsar, M. (2016). “Reliability and Availability Analysis of A Manufacturing Line System”, Journal of Applied and
Physical Sciences. 2(3), 96-106. https://doi.org/10.20474/japs-2.3.5
- Tsarouhas, P.H. and Arvanitoyannis, I.S. (2014). “Yogurt Production Line: Reliability Analysis”, Production & Manufacturing Research: 2(1), 11-23.
- Ünözkan, H. and Yılmaz, M. (2021). “A Stochastic Approach to a Combined Parallel System”, International Journal of Applied Mathematics and Statistics, 60(1), 81-87.
- Yang, Z., Li, J., Chen, C., He, J., Tian, H. and Yu, L. (2021). “A Study on Overall Line Efficiency (OLE) Centered Production Line Maintenance Prioritization Considering Equipment Operational Reliability”, The International Journal of Advanced Manufacturing Technology, 124, 3783-3794. https://doi.org/10.1007/s00170-021-07547-9
- Zhang, Y., Cheng, Y., Wang, X.V., Zhong, R.Y., Zhang, Y. and Tao, F. (2019). “Data-Driven Smart Production Line and Its Common Factors”, The International Journal of Advanced Manufacturing Technology, 103, 1211-1223. https://doi.org/10.1007/s00170-019-03469-9
- Zhao, C., Li, J., Huang, N. and Horst, J.A., (2017) "Flexible Serial Lines with Setups: Analysis, Improvement, and Application," in IEEE Robotics and Automation Letters, 2(1), 120-127, https://doi.org/10.1109/LRA.2016.2556078