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Reliability based particle swarm optimization for obtaining optimal dimensions of boom crane lifting mechanism

Yıl 2026, Sayı: Advanced Online Publication
https://doi.org/10.5505/pajes.2025.27860
https://izlik.org/JA35XP48PA

Öz

Articulated Mobile Cranes are specially designed systems intended for lifting and transporting loads of varying weights and dimensions. The physical dimensions of these systems may vary depending on their field of application and specific technical requirements. Such variations can have significant impacts on both lifting capacity and operational speed. Dimensional changes may lead to undesirable deviations within the safety limits established during the design phase. Therefore, in order to optimize the dimensions of these mechanisms, the statistical nature of manufacturing and measurement errors must be carefully assessed. In this study, the dimensional optimization of crane boom lifting mechanisms was performed based on reliability analysis by combining Monte Carlo Simulation with the Particle Swarm Optimization method to determine the optimal mechanism dimensions. According to the results obtained, it was found that the lambda values for different operating modes are primarily influenced by the geometric parameter (ψ) and, to a lesser extent, by the cylinder speed (vc). Depending on the selected parameters, the lambda value was observed to vary between 0.35 and 0.55.

Kaynakça

  • [1] Kennedy, J., Eberhart, R. “Particle swarm optimization”. Proceedings IEEE International Conference Neural Networks, IEEE, Perth, WA, Australia, 27 November–1 December 1995.
  • [2] Naka, S., Genji, T., Yura, T., Fukuyama, Y. “A hybrid particle swarm optimization for distribution state estimation”. IEEE Transactions on Power Systems, 18, 60–68, 2003.
  • [3] Ratnaweera, A., Halgamuge, S.K. “Self-organizing hierarchical particle swarm optimizer with time-varying acceleration coefficient”. IEEE Transactions on Evolutionary Computation, 8, 240–255, 2004.
  • [4] Shi, Y., Eberhart, R.C. “A modified particle swarm optimizer”. Proceedings of the IEEE International Conference on Evolutionary Computation, Anchorage, Alaska, 4–9 May 1998.
  • [5] Clerc, M. “The Swarm and the Queen: Towards the deterministic and adaptive particle swarm optimization”. Proceedings of the Congress on Evolutionary Computation, IEEE Service Center, Washington, DC, USA, 6–9 July 1999.
  • [6] Arumugam, M.S., Rao, M.V.R., Tan, A.W.C. “A novel and effective particle swarm optimization-like algorithm with extrapolation technique”. Applied Soft Computing, 9, 308–320, 2009.
  • [7] Fateh, M.M., Zirkohi, M.M. “Adaptive impedance control of a hydraulic suspension system using particle swarm optimisation”. Vehicle System Dynamics, 49(12), 1951–1965, 2011.
  • [8] Lu, H., Dong, Y. “A reliability index computation method based on particle swarm optimization”. International Conference on Advances in Energy, Environment and Chemical Engineering (AEECE-2015).
  • [9] Elegbede, C. “Structural reliability assessment based on particle swarm optimization”. Structural Safety, 27, 171–186, 2005.
  • [10] Wu, P., Gao, L., Zou, D., Li, S. “An improved particle swarm optimization algorithm for reliability problems”. ISA Transactions, 50, 71–81, 2011.
  • [11] Chengming, L., Hui, L. “Structural reliability and sensitivity analysis of random variables based on PSO”. Journal of Xi'an University of Architecture & Technology, 38, 614–618, 2006.
  • [12] Kuo, W., Prasad, V.R. “An annotated overview of system-reliability optimization”. IEEE Transactions on Reliability, 49, 176–187, 2000.
  • [13] Gaby, G., Prayogo, D., Wijaya, B.H., Wong, F.T., Tjandra, D. “Reliability-based design optimization for structures using particle swarm optimization”. Journal of Physics: Conference Series, 1625, 012016, 2020.
  • [14] Prayogo, D., Cheng, M.Y., Wong, F.T., Tjandra, D., Tran, D.H. “Optimization model for construction project resource leveling using a novel modified symbiotic organisms search”. Asian Journal of Civil Engineering, 19, 625–638, 2018.
  • [15] Coelho, L.S. “An efficient particle swarm approach for mixed-integer programming in reliability–redundancy optimization applications”. Reliability Engineering and System Safety, 94(4), 830–837, 2009.
  • [16] Liu, Z., Zhu, C., Zhu, P., Chen, W. “Reliability-based design optimization of composite battery box based on modified particle swarm optimization algorithm”. Composite Structures, 204, 239–255, 2018.
  • [17] Liu, Y., Qin, G. “A modified particle swarm optimization algorithm for reliability redundancy optimization problem”. Journal of Computers, 9(9), September 2014.
  • [18] Malhotra, R., Negi, A. “Reliability modeling using particle swarm optimization”. International Journal of System Assurance Engineering and Management, 4, 275–283, 2013.
  • [19] Sun, G., Zhang, H., Fang, J., Li, G., Li, Q. “A new multi-objective discrete robust optimization algorithm for engineering design”. Applied Mathematical Modelling, 53, 602–621, 2018.
  • [20] Xu, X., Chen, X., Liu, Z., Yang, J., Xu, Y., Zhang, Y., Gao, Y. “Multi-objective reliability-based design optimization for the reducer housing of electric vehicles”. Engineering Optimization, 1–17, 2021.
  • [21] Xu, X., Chen, X., Liu, Z., Xu, Y., Zhang, Y. “Reliability-based design for lightweight vehicle structures with uncertain manufacturing accuracy”. Applied Mathematical Modelling, 95, 22–37, 2021.
  • [22] Fang, J., Gao, Y., Sun, G., Xu, C., Li, Q. “Multiobjective robust design optimization of fatigue life for a truck cab”. Reliability Engineering & System Safety, 135, 1–8, 2015.
  • [23] Dawood, T., Elwakil, E., Novoa, H.M., Delgado, J.F.G. “Soft computing for modeling pipeline risk index under uncertainty”. Engineering Failure Analysis, 117, 104949, 2020.
  • [24] Li, W., Gao, L., Xiao, M. “Multidisciplinary robust design optimization under parameter and model uncertainties”. Engineering Optimization, 52, 426–445, 2020.
  • [25] Chen, Z., Li, T., Xue, X., Zhou, Y., Jing, S. “Fatigue reliability analysis and optimization of vibrator baseplate based on fuzzy comprehensive evaluation method”. Engineering Failure Analysis, 127, 105357, 2021.
  • [26] Yuan, R., Tang, M., Wang, H., Li, H. “A reliability analysis method of accelerated performance degradation based on Bayesian strategy”. IEEE Access, 7, 169047–169054, 2019.
  • [27] Xian, J., Su, C. “Stochastic optimization of uncertain viscous dampers for energy-dissipation structures under random seismic excitations”. Mechanical Systems and Signal Processing, 164, 108208, 2022.
  • [28] Tan, Y., Zhan, C., Pi, Y., Zhang, C., Song, J., Chen, Y., Golmohammadi, A.M. “A hybrid algorithm based on social engineering and artificial neural network for fault warning detection in hydraulic turbines”. Mathematics, 11, 2274, 2023.
  • [29] Xue, Y., Deng, Y. “Extending set measures to orthopair fuzzy sets”. International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, 30, 63–91, 2022.
  • [30] Zhu, S.P., Keshtegar, B., Bagheri, M., Hao, P., Trung, N.T. “Novel hybrid robust method for uncertain reliability analysis using finite conjugate map”. Computer Methods in Applied Mechanics and Engineering, 371, 113309, 2020.
  • [31] Bagheri, M., Zhu, S.P., Ben Seghier, M.E.A., Keshtegar, B., Trung, N.T. “Hybrid intelligent method for fuzzy reliability analysis of corroded X100 steel pipelines”. Engineering Computations, 37, 2559–2573, 2021.
  • [32] Plotnikov, L. “Preparation and analysis of experimental findings on the thermal and mechanical characteristics of pulsating gas flows in the intake system of a piston engine for modelling and machine learning”. Mathematics, 11, 1967, 2023.
  • [33] Zhang, D., Zhang, J., Yang, M., Wang, R., Wu, Z. “An enhanced finite step length method for structural reliability analysis and reliability-based design optimization”. Structural and Multidisciplinary Optimization, 65, 231, 2022.
  • [34] Dui, H., Song, J., Zhang, Y.A. “Reliability and service life analysis of airbag systems”. Mathematics, 11, 434, 2023.

Vinç bom kaldırma mekanizmasının optimum boyutlarını elde etmek için güvenilirlik tabanlı parçacık sürü optimizasyonu

Yıl 2026, Sayı: Advanced Online Publication
https://doi.org/10.5505/pajes.2025.27860
https://izlik.org/JA35XP48PA

Öz

Araç üstü mobil vinçler, farklı ağırlık ve boyutlardaki yükleri kaldırmak ve taşımak amacıyla özel olarak tasarlanmış sistemlerdir. Bu sistemlerin fiziksel boyutları, kullanım alanlarına ve farklı teknik isteklere bağlı olarak değişkenlik gösterebilir. Bu durum hem kaldırma kapasitesi üzerinde hem de hareket hızı üzerinde önemli etkiler yaratabilir. Boyutsal değişimler, tasarım aşamasında belirlenmiş güvenlik sınırları içerisinde istenmeyen sapmalara neden olabilir. Bu yüzden, bu mekanizmaların boyutlarını optimize etmek için üretim ve ölçüm hatalarının istatistiksel doğasının dikkatli biçimde değerlendirilmesi gerekir. Bu çalışmada, vinç bom kaldırma mekanizmalarının boyutsal optimizasyonu amacıyla Monte Carlo simülasyonu ile Parçacık Sürü Optimizasyonu yöntemi birlikte kullanılarak, mekanizmanın optimum boyutları güvenilirlik temelli olarak belirlenmiştir. Elde edilen sonuçlara gore, farklı çalışma modları için lambda değerlerinin, öncelikle geometri parametresinden (ψ) ve daha az ölçüde silindir hızından (vc) etkilendiği ve seçilen parametrelere gore lambda değerinin 0,35-0,55 arasında değiştiği tespit edilmiştir.

Kaynakça

  • [1] Kennedy, J., Eberhart, R. “Particle swarm optimization”. Proceedings IEEE International Conference Neural Networks, IEEE, Perth, WA, Australia, 27 November–1 December 1995.
  • [2] Naka, S., Genji, T., Yura, T., Fukuyama, Y. “A hybrid particle swarm optimization for distribution state estimation”. IEEE Transactions on Power Systems, 18, 60–68, 2003.
  • [3] Ratnaweera, A., Halgamuge, S.K. “Self-organizing hierarchical particle swarm optimizer with time-varying acceleration coefficient”. IEEE Transactions on Evolutionary Computation, 8, 240–255, 2004.
  • [4] Shi, Y., Eberhart, R.C. “A modified particle swarm optimizer”. Proceedings of the IEEE International Conference on Evolutionary Computation, Anchorage, Alaska, 4–9 May 1998.
  • [5] Clerc, M. “The Swarm and the Queen: Towards the deterministic and adaptive particle swarm optimization”. Proceedings of the Congress on Evolutionary Computation, IEEE Service Center, Washington, DC, USA, 6–9 July 1999.
  • [6] Arumugam, M.S., Rao, M.V.R., Tan, A.W.C. “A novel and effective particle swarm optimization-like algorithm with extrapolation technique”. Applied Soft Computing, 9, 308–320, 2009.
  • [7] Fateh, M.M., Zirkohi, M.M. “Adaptive impedance control of a hydraulic suspension system using particle swarm optimisation”. Vehicle System Dynamics, 49(12), 1951–1965, 2011.
  • [8] Lu, H., Dong, Y. “A reliability index computation method based on particle swarm optimization”. International Conference on Advances in Energy, Environment and Chemical Engineering (AEECE-2015).
  • [9] Elegbede, C. “Structural reliability assessment based on particle swarm optimization”. Structural Safety, 27, 171–186, 2005.
  • [10] Wu, P., Gao, L., Zou, D., Li, S. “An improved particle swarm optimization algorithm for reliability problems”. ISA Transactions, 50, 71–81, 2011.
  • [11] Chengming, L., Hui, L. “Structural reliability and sensitivity analysis of random variables based on PSO”. Journal of Xi'an University of Architecture & Technology, 38, 614–618, 2006.
  • [12] Kuo, W., Prasad, V.R. “An annotated overview of system-reliability optimization”. IEEE Transactions on Reliability, 49, 176–187, 2000.
  • [13] Gaby, G., Prayogo, D., Wijaya, B.H., Wong, F.T., Tjandra, D. “Reliability-based design optimization for structures using particle swarm optimization”. Journal of Physics: Conference Series, 1625, 012016, 2020.
  • [14] Prayogo, D., Cheng, M.Y., Wong, F.T., Tjandra, D., Tran, D.H. “Optimization model for construction project resource leveling using a novel modified symbiotic organisms search”. Asian Journal of Civil Engineering, 19, 625–638, 2018.
  • [15] Coelho, L.S. “An efficient particle swarm approach for mixed-integer programming in reliability–redundancy optimization applications”. Reliability Engineering and System Safety, 94(4), 830–837, 2009.
  • [16] Liu, Z., Zhu, C., Zhu, P., Chen, W. “Reliability-based design optimization of composite battery box based on modified particle swarm optimization algorithm”. Composite Structures, 204, 239–255, 2018.
  • [17] Liu, Y., Qin, G. “A modified particle swarm optimization algorithm for reliability redundancy optimization problem”. Journal of Computers, 9(9), September 2014.
  • [18] Malhotra, R., Negi, A. “Reliability modeling using particle swarm optimization”. International Journal of System Assurance Engineering and Management, 4, 275–283, 2013.
  • [19] Sun, G., Zhang, H., Fang, J., Li, G., Li, Q. “A new multi-objective discrete robust optimization algorithm for engineering design”. Applied Mathematical Modelling, 53, 602–621, 2018.
  • [20] Xu, X., Chen, X., Liu, Z., Yang, J., Xu, Y., Zhang, Y., Gao, Y. “Multi-objective reliability-based design optimization for the reducer housing of electric vehicles”. Engineering Optimization, 1–17, 2021.
  • [21] Xu, X., Chen, X., Liu, Z., Xu, Y., Zhang, Y. “Reliability-based design for lightweight vehicle structures with uncertain manufacturing accuracy”. Applied Mathematical Modelling, 95, 22–37, 2021.
  • [22] Fang, J., Gao, Y., Sun, G., Xu, C., Li, Q. “Multiobjective robust design optimization of fatigue life for a truck cab”. Reliability Engineering & System Safety, 135, 1–8, 2015.
  • [23] Dawood, T., Elwakil, E., Novoa, H.M., Delgado, J.F.G. “Soft computing for modeling pipeline risk index under uncertainty”. Engineering Failure Analysis, 117, 104949, 2020.
  • [24] Li, W., Gao, L., Xiao, M. “Multidisciplinary robust design optimization under parameter and model uncertainties”. Engineering Optimization, 52, 426–445, 2020.
  • [25] Chen, Z., Li, T., Xue, X., Zhou, Y., Jing, S. “Fatigue reliability analysis and optimization of vibrator baseplate based on fuzzy comprehensive evaluation method”. Engineering Failure Analysis, 127, 105357, 2021.
  • [26] Yuan, R., Tang, M., Wang, H., Li, H. “A reliability analysis method of accelerated performance degradation based on Bayesian strategy”. IEEE Access, 7, 169047–169054, 2019.
  • [27] Xian, J., Su, C. “Stochastic optimization of uncertain viscous dampers for energy-dissipation structures under random seismic excitations”. Mechanical Systems and Signal Processing, 164, 108208, 2022.
  • [28] Tan, Y., Zhan, C., Pi, Y., Zhang, C., Song, J., Chen, Y., Golmohammadi, A.M. “A hybrid algorithm based on social engineering and artificial neural network for fault warning detection in hydraulic turbines”. Mathematics, 11, 2274, 2023.
  • [29] Xue, Y., Deng, Y. “Extending set measures to orthopair fuzzy sets”. International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, 30, 63–91, 2022.
  • [30] Zhu, S.P., Keshtegar, B., Bagheri, M., Hao, P., Trung, N.T. “Novel hybrid robust method for uncertain reliability analysis using finite conjugate map”. Computer Methods in Applied Mechanics and Engineering, 371, 113309, 2020.
  • [31] Bagheri, M., Zhu, S.P., Ben Seghier, M.E.A., Keshtegar, B., Trung, N.T. “Hybrid intelligent method for fuzzy reliability analysis of corroded X100 steel pipelines”. Engineering Computations, 37, 2559–2573, 2021.
  • [32] Plotnikov, L. “Preparation and analysis of experimental findings on the thermal and mechanical characteristics of pulsating gas flows in the intake system of a piston engine for modelling and machine learning”. Mathematics, 11, 1967, 2023.
  • [33] Zhang, D., Zhang, J., Yang, M., Wang, R., Wu, Z. “An enhanced finite step length method for structural reliability analysis and reliability-based design optimization”. Structural and Multidisciplinary Optimization, 65, 231, 2022.
  • [34] Dui, H., Song, J., Zhang, Y.A. “Reliability and service life analysis of airbag systems”. Mathematics, 11, 434, 2023.
Toplam 34 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Makine Mühendisliği (Diğer)
Bölüm Araştırma Makalesi
Yazarlar

Ömer Sinan Şahin

Ahmet Çatal Bu kişi benim

Kerem Çoban

Oğuzhan Taş

Gönderilme Tarihi 24 Nisan 2025
Kabul Tarihi 1 Eylül 2025
Erken Görünüm Tarihi 2 Kasım 2025
DOI https://doi.org/10.5505/pajes.2025.27860
IZ https://izlik.org/JA35XP48PA
Yayımlandığı Sayı Yıl 2026 Sayı: Advanced Online Publication

Kaynak Göster

APA Şahin, Ö. S., Çatal, A., Çoban, K., & Taş, O. (2025). Reliability based particle swarm optimization for obtaining optimal dimensions of boom crane lifting mechanism. Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi, Advanced Online Publication. https://doi.org/10.5505/pajes.2025.27860
AMA 1.Şahin ÖS, Çatal A, Çoban K, Taş O. Reliability based particle swarm optimization for obtaining optimal dimensions of boom crane lifting mechanism. Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi. 2025;(Advanced Online Publication). doi:10.5505/pajes.2025.27860
Chicago Şahin, Ömer Sinan, Ahmet Çatal, Kerem Çoban, ve Oğuzhan Taş. 2025. “Reliability based particle swarm optimization for obtaining optimal dimensions of boom crane lifting mechanism”. Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi, sy Advanced Online Publication. https://doi.org/10.5505/pajes.2025.27860.
EndNote Şahin ÖS, Çatal A, Çoban K, Taş O (01 Kasım 2025) Reliability based particle swarm optimization for obtaining optimal dimensions of boom crane lifting mechanism. Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi Advanced Online Publication
IEEE [1]Ö. S. Şahin, A. Çatal, K. Çoban, ve O. Taş, “Reliability based particle swarm optimization for obtaining optimal dimensions of boom crane lifting mechanism”, Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi, sy Advanced Online Publication, Kas. 2025, doi: 10.5505/pajes.2025.27860.
ISNAD Şahin, Ömer Sinan - Çatal, Ahmet - Çoban, Kerem - Taş, Oğuzhan. “Reliability based particle swarm optimization for obtaining optimal dimensions of boom crane lifting mechanism”. Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi. Advanced Online Publication (01 Kasım 2025). https://doi.org/10.5505/pajes.2025.27860.
JAMA 1.Şahin ÖS, Çatal A, Çoban K, Taş O. Reliability based particle swarm optimization for obtaining optimal dimensions of boom crane lifting mechanism. Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi. 2025. doi:10.5505/pajes.2025.27860.
MLA Şahin, Ömer Sinan, vd. “Reliability based particle swarm optimization for obtaining optimal dimensions of boom crane lifting mechanism”. Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi, sy Advanced Online Publication, Kasım 2025, doi:10.5505/pajes.2025.27860.
Vancouver 1.Ömer Sinan Şahin, Ahmet Çatal, Kerem Çoban, Oğuzhan Taş. Reliability based particle swarm optimization for obtaining optimal dimensions of boom crane lifting mechanism. Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi. 01 Kasım 2025;(Advanced Online Publication). doi:10.5505/pajes.2025.27860