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MULTI-OBJECTIVE ASSEMBLY LINE BALANCING WITH HUMAN-ROBOT COLLABORATION

Year 2022, , 10 - 36, 14.04.2022

Mihrimah Özmen , Ayşe Nur Karacan , Halil İbrahim Şahin

https://doi.org/10.54365/adyumbd.960059
Cited By: 1

Abstract

Since the Industrial Revolution, robots have started to take their place alongside humans in production and assembly lines in order to adapt to the increasing competition. Since human and robot are two different structures with very different dynamics, the assembly line balancing (ALB) problem becomes much more complex. Wıth the human-robot collaboration ALB problem is a new fıeld of study and yet there are limited studies on this subject. in this study; a new mathematical model has been proposed to solve the problem of the ALB with the human/robot cooperation. In the proposed model it is paid attention to situation of human and robot working together in addition to the unfavorable situations of human/robot cooperation. In real life, the performance of assembly lines is evaluated for many conflicting objectives. Considering all these, a multi-objective solution approach is proposed in which Multi-Criteria Decision Making (MCDM)and goal programming techniques are integrated to the human-robot co-operation for ALB problem. In the proposed approach, it is aimed to minimize the robot/human employee cost, cycle time and number of workstations. The order of priority of these objectives differs for reasons of the product produced, the company, etc. Therefore the optimal ALB solution was found regardless of the importance of three points. The results have been obtained using the GAMS software solving with respect to the model, of the combination of objectives’ all different importance order. The results determined the best ALB option based on the results with the perspective of BWM-MABAC MCDM approaches of six criteria (robot/human worker cost, cycle time, number of workstations, line efficiency, smoothness index, and balance delay). Sensitivity analysis of criterion weights examined the robustness of the results of criterion weights. The proposed approach was applied on the sample data set and the results were analyzed.

Keywords

Multi-objective optimization Human- Robot Mixed Assembly Line Multi-Criteria Decision Making BWM-MABAC

References

  • J. Krüger, T. Lien ve A. Verl, “Cooperation of human and machines in assembly lines” CIRP annals, pp. 628-646, 2009.
  • J. Tan, F. Duan, Y. Zhang, R. Kato ve T. Arai, “Task modeling approach to enchance man-machine collaboration in cell production” %1 içinde İnternational Conference on Robotics and Automation, 2009.
  • F. Wallhoff, J. Blume, A. Bannat, W. Rösel, C. Lenz ve A. Knoll, “A skill-based approach towards hybrid assembly” Advanced Engineering Informatics, pp. 329-339, 2010.
  • F. Chen, K. Sekiyama, J. Huang, B. Sun, H. Sasaki ve T. Fukuda, “An assembly strategy scheduling method for human and robot coordinated cell manufacturinf” International Journal of Intelligent Computing and Cybernetics, 2011.
  • S. Takata ve T. Hirano, “Human and robot allocation method for hybrid assembly systems” CIRP annals, pp. 9-12, 2011.
  • P. Tsarouchi, A. Matthaiakis, S. Makris ve G. Chryssolouris, “On a human-robot collaboration in an assembly cell” International Journal of Computer Intergrated Manufacturing, pp. 580-589, 2017.
  • Z. Çil, Z. Li, S. Mete ve E. Özceylan, “Mathematical model and bee algorithms for mixed-model assembly line balancing problem with physical human-robot collaboration” Applied Soft Computing, p. 106394, 2020.
  • H. M. Alağaş, M. Pınarbaşı, M. Yüzükırmızı ve B. Toklu, “Karma modelli tip-2 montaj hattı dengeleme problemi için bir kısıt programlama modeli” Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi, pp. 340-348, 2016.
  • H. Altunay, H. Özmutlu ve S. Özmutlu, “Paralel görev atamalı montaj hattı dengeleme problemi için yeni bir matematiksel model önerisi” Cumhuriyet Üniversitesi İktisadi ve İdari Bilimler Dergisi, pp. 15-33, 2017.
  • Ş. Topaloğlu Yıldız, G. Yıldız ve E. Cin, “Bir Elektronik Firmasındaki İşçi Atamalı Montaj Hattı Dengeleme Problemine Matematiksel Programlama Ve Benzetim Modelleme Tabanlı Bir Çözüm Yaklaşımı” Afyon Kocatepe Üniversitesi İktisadi Ve İdari Bilimler Fakültesi Dergisi, pp. 57-73, 2020.
  • S. Gemici, B. Geniş, İ. Koçyiğit, E. Otuzbir, M. Özer, S. Pekelli ve A. Öztop, “Çok Taraflı ve Çok Modelli Soğutucu Montaj Hattı Dengeleme” Sistem Tasarımı Proje Özetleri, p. 60, 2020.
  • J. Rubinovitz, “Design and balancing of robotic assembly lines” %1 içinde In Proceedings of the Fourth World Conference on Robotics Research, Pittsburgh, 1991.
  • H. Kim ve S. Park, “A Strong Cutting Plane Algorithm for the Robotic Assembly Line Balancing Problem” International Journal of Production Reearch, pp. 2311-2323, 1995.
  • D. S. Hong ve H. Cho, “Generation of robotic assembly sequences with consideration of line balancing using simulated annealing” Robotica, pp. 663-673, 1997.
  • G. Levithin, J. Rubinovitz ve B. Shnits, “A Genetic Algorithm for Robotic Assembly Line Balancing” European Journal of Operational Research, pp. 811-825, 2006.
  • J. Gao, L. Sun, L. Wang ve M. Gen, “An Efficient Approach for type 2 Robotic Assembly Line Balancing Problem” Computers & Industrial Engineering, pp. 1065-1080, 2009.
  • J. M. Nilakantan ve S. G. & Ponnambalam, “An efficient PSO for type 2 robotic assembly line balancing problem” %1 içinde IEEE international conference on automation science and engineering, 2012.
  • A. Yoosefelahi, M. Aminnayeri, H. Mosadegh ve H. Ardakani, “Type 2 robotic assembly line balancing problem: An evolution strategies algorithm for a multi-objective model” Journal of Manufacturing Systems, pp. 139-151, 2012.
  • S. Daoud, H. Chehade, F. Yalaoui ve L. Amodeo, “Solving a robotic assembly line balancing problem using efficient hybrid methods” Journal of Heuristics, pp. 235-259, 2014.
  • M. Aghajani, R. Ghodsi ve B. Javadi, “Balancing of robotic mixed- model two- sided assembly line with robot setup times” The internationaljournal of advanced Manufacturing Technology, pp. 1005-1016, 2014.
  • J. Nilakantan, G. Q. Huang ve S. Ponnambalam, “An investigation on minimizing cycle time and total energy consumption in robotic in assembly line systems” Journal of Cleaner Production, pp. 311-325, 2015a.
  • J. Nilakantan, S. Ponnambalam, N. Jawahar ve G. Kanagaraj, “Bio-inspired search algorithms to solve robotic assembly line balancing problems” Neural Computing and Applications, pp. 1379-1393, 2015b.
  • J. Nilakantan Mukund ve S. G. Ponnambalam, “Robotic U-shaped assembly line balancing using particle swarm optimization” Engineering Optimization, pp. 231-251, 2016.
  • M. Rabbani, Z. Mousavi ve H. Farrokhi-Asl, “Multi-objective metaheuristics for solving a type 2 robotic mixed-model assembly line balancing problem.” Journal of Industrial and Production Engineering, pp. 472-484, 2016.
  • Z. Li, M. N. Janardhanan, Q. Tang ve P. Nielsen, “Mathematical model and metaheuristics for simultaneous balancing and sequencing of a robotic mixed-model assembly line” Engineering Optimization, cilt 50, no. 5, pp. 877-893, 2018.
  • C. Müller, M. Grunewald ve T. Spengler, “Redundant configuration of robotic assembly lines with stochastic failures” International Journal of Production Research, cilt 56, no. 10, pp. 3662-3682, 2018.
  • Z. Zhang, Q. Tang, Z. Li ve L. Zhang, “Modelling and optimisation of energy-efficient U-shaped robotic assembly line balancing problems” International Journal of Production Research, pp. 5520-5537, 2019.
  • J. Pereira, M. Ritt ve Ó. C. Vásquez, “A memetic algorithm for the cost-oriented robotic assembly line balancing problem” Computers & Operations Research, cilt 99, pp. 249-261, 2018.
  • J. Q. Li ve Y. Q. Han, “A hybrid multi-objective artifical bee colony algorithm for flexible task schedulling problems in cloud computing system” Cluster Computing, pp. 2483-2499, 2020.
  • B. ZHOU ve Q. Wu, “Decomposition-based bi-objective optimization for sustainable robotic assembly line balancing problems” Journal of Manufacturing Systems, cilt 55, pp. 30-43, 2020.
  • B. Zhang, L. Xu ve J. Zhang, “Balancing and sequencing problem of mixed- model U-shaped robotic assebly line: Mathematical model and dragonfly algorithm based approach” Applied soft computing, p. 106739, 2021.
  • A. Charnes ve W. Cooper, “Management models and industrial applications of linear programming” Management Science, pp. 38-91, 1957.
  • H. Gokcen ve E. Erel, “A goal programming approach to mixed-model assembly line balancing problem” International Journal of Production Economics, pp. 177-185, 1997.
  • H. Gökçen ve K. Ağpak, “A goal programming approach to simple U-line balancing problem” European Journal of Operational Research, pp. 577-585, 2006.
  • Z. Cil, S. Mete ve K. Ağpak, “A goal programming approach for robotic assembly line balancing problem” IFAC-PapersOnLine, pp. 938-942, 2016.
  • M. Rauf, Z. Guan, S. Sarfraz, J. Mumtaz, E. Shebab, M. Jahanzaib ve M. Hanif, “A smart algorithm for multi-criteria optimization of model sequencing problem in assembly lines” Robotics and Computer-Integrated Manufacturing, p. 101844, 2020.
  • F. Jolai, M. Rezaee ve A. Vazifeh, “Multi-criteria decision making for assembly line balancing” Journal of Intelligent Manufacturing, pp. 113-121, 2009.
  • U. Özcan ve B. Toklu, “Multiple-criteria decision-making in two-side assembly line balancing: A goal programming and a fuzzy goal programming models” Computers & Operations Research, pp. 1955-1965, 2009.
  • N. Hamta, S. Ghomi, F. Jolai ve U. Bahalke, “Bi-criteria assembly line balancing by considering flexible operation times” Applied Mathematical Modelling, pp. 5592-5608, 2011.
  • A. Guitouni ve J. Martel, “Tentative guidelines to help choosing an appropriate MCDA method” European journal of operational reserch, p. 501521, 1998.
  • J. Figuera, S. Greco ve M. Ehrgott, “Multiple criteria decision analysis: State of the art surveys” New York: Springer Science&Business Media, 2005.
  • Y. Siskos, E. Grigoroudis, N. Matsatsinis, J. Figueira, S. Greco ve M. Ehrgott, “Multiple criteria decision analysis: State of the art surveys” Figueira, J., Greco, S., Ehrgott M., pp. 297-344, 2005.
  • T. Saaty, “The modern science of multi criteria decision making and its practical applications: The AHP/ANP approach.” Operation Research, pp. 1101-1118, 2013.
  • W. Ho, X. Xu ve P. Dey, “Multi-criteria decision making approaches for supplier evaluation and selection: A literature review” European Journal of Operational Research, cilt 202, no. 1, pp. 16-24, 2010.
  • B. Malakooti, “Assembly line balancing with buffers by multiple criteria optimization” The internaonal journal of production research, pp. 2159-2178, 1994.
  • M. Kabir ve M. Tabucanon, “Batch-model assembly line balancing: A multiattribute decision making approach” International Journal of Production Economics, pp. 193-201, 1995.
  • Z. Çil, S. Mete, E. Özceyla ve K. Ağpak, “A beam search approach for solving type-2 robotic assembly line balancing problem” Applied Sowft Computing, pp. 129-138, 2017.
  • J. Rezai, “Best-worst multi-criteria decision-making method.” Omega, pp. 49-57, 2015.
  • J. Rezaei, “Best-worst multi-criteria decision-making method: Some properties and a linear model” Omega, pp. 126-130, 2016.
  • D. Pamučar ve G. Ćirovič, “The selection of transport and handling resources in logistic centers using Multi-Attributive Border Approximation area Comparison (MABAC)” Expert systems with applications, pp. 3016-3028, 2015.
  • E. Triantaphyllou, “A sensitivity analysis approach for MCDM methods” Multi-criteria Decision Making Methods: A Comparative Study, pp. 131-175, 2000.

İNSAN-ROBOT İŞ BİRLİĞİ İLE ÇOK AMAÇLI MONTAJ HATTI DENGELEME

Year 2022, , 10 - 36, 14.04.2022

Mihrimah Özmen , Ayşe Nur Karacan , Halil İbrahim Şahin

https://doi.org/10.54365/adyumbd.960059
Cited By: 1

Abstract

Sanayi Devriminden itibaren, artan rekabete uyum sağlamak için robotlar üretimde ve montaj hatlarında insanların yanında yer almaya başlamıştır. İnsan ve robot birbirinden çok farklı dinamiklere sahip iki farklı yapı oldukları için montaj hattı dengeleme (MHD) problemi daha karmaşık hale gelmektedir. Robotik montaj hattı dengeleme (RMHD) literatürde güncel olarak çalışılan konular arasında yer almaktadır fakat insan robot iş birliği ile MHD problemi yeni bir çalışma alanıdır. Bu çalışmada insan-robot iş birliği ile montaj hattı dengeleme probleminin çözümü için yeni bir matematiksel model önerilmiştir. Önerilen modelde, literatürdeki RMHD çalışmalarından farklı olarak insanın ve robotun birlikte çalışması durumuna ek olarak aynı istasyona insan ve robot birlikte çalışmasının sakıncalı olduğu durumlar da dikkate alınmıştır. Gerçek hayatta montaj hatlarının performansı birbirleriyle çelişen birçok amaçla değerlendirilmektedir. Bütün bunlar göz önünde bulundurularak, insan robot iş birliği ile MHD problemine Çok Kriterli Karar Verme (ÇKKV) ve hedef programlama tekniklerinin entegre edildiği çok amaçlı çözüm yaklaşımı önerilmiştir. Önerilen yaklaşımda, robot/insan çalışan maliyeti, çevrim süresi ve iş istasyonu sayısının minimize edilmesi amaçlanmıştır. Bu amaçların öncelik sıralamaları üretilen ürüne, firmaya vb. sebeplerden dolayı farklılık göstermektedir. Bu nedenle üç amacın önem sırasından bağımsız olarak optimal MHD çözümü bulunmuştur. Amaçların bütün farklı önem sırasının kombinasyonu için model sırasıyla GAMS yazılımı ile çözdürülerek sonuçlar elde edilmiştir. Sonuçlar, altı kriter (robot/insan çalışan maliyeti, çevrim süresi, iş istasyonu sayısı, hat etkinliği, düzgünlük indeksi ve denge gecikmesi) açısından ÇKKV yaklaşımları olan BWM- MABAC sonuçlarına göre en iyi MHD seçeneği belirlenmiştir. Kriter ağırlıklarının duyarlılık analizi yapılarak, kriter ağırlıklarının sonuçlarının sağlamlığı incelemiştir. Önerilen yaklaşım örnek veri seti üzerinde uygulanmış ve sonuçları analiz edilmiştir.

Keywords

Çok amaçlı optimizasyon İnsan-Robot İş Birliği ile Montaj Hattı ÇKKV BWM-MABAC

References

  • J. Krüger, T. Lien ve A. Verl, “Cooperation of human and machines in assembly lines” CIRP annals, pp. 628-646, 2009.
  • J. Tan, F. Duan, Y. Zhang, R. Kato ve T. Arai, “Task modeling approach to enchance man-machine collaboration in cell production” %1 içinde İnternational Conference on Robotics and Automation, 2009.
  • F. Wallhoff, J. Blume, A. Bannat, W. Rösel, C. Lenz ve A. Knoll, “A skill-based approach towards hybrid assembly” Advanced Engineering Informatics, pp. 329-339, 2010.
  • F. Chen, K. Sekiyama, J. Huang, B. Sun, H. Sasaki ve T. Fukuda, “An assembly strategy scheduling method for human and robot coordinated cell manufacturinf” International Journal of Intelligent Computing and Cybernetics, 2011.
  • S. Takata ve T. Hirano, “Human and robot allocation method for hybrid assembly systems” CIRP annals, pp. 9-12, 2011.
  • P. Tsarouchi, A. Matthaiakis, S. Makris ve G. Chryssolouris, “On a human-robot collaboration in an assembly cell” International Journal of Computer Intergrated Manufacturing, pp. 580-589, 2017.
  • Z. Çil, Z. Li, S. Mete ve E. Özceylan, “Mathematical model and bee algorithms for mixed-model assembly line balancing problem with physical human-robot collaboration” Applied Soft Computing, p. 106394, 2020.
  • H. M. Alağaş, M. Pınarbaşı, M. Yüzükırmızı ve B. Toklu, “Karma modelli tip-2 montaj hattı dengeleme problemi için bir kısıt programlama modeli” Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi, pp. 340-348, 2016.
  • H. Altunay, H. Özmutlu ve S. Özmutlu, “Paralel görev atamalı montaj hattı dengeleme problemi için yeni bir matematiksel model önerisi” Cumhuriyet Üniversitesi İktisadi ve İdari Bilimler Dergisi, pp. 15-33, 2017.
  • Ş. Topaloğlu Yıldız, G. Yıldız ve E. Cin, “Bir Elektronik Firmasındaki İşçi Atamalı Montaj Hattı Dengeleme Problemine Matematiksel Programlama Ve Benzetim Modelleme Tabanlı Bir Çözüm Yaklaşımı” Afyon Kocatepe Üniversitesi İktisadi Ve İdari Bilimler Fakültesi Dergisi, pp. 57-73, 2020.
  • S. Gemici, B. Geniş, İ. Koçyiğit, E. Otuzbir, M. Özer, S. Pekelli ve A. Öztop, “Çok Taraflı ve Çok Modelli Soğutucu Montaj Hattı Dengeleme” Sistem Tasarımı Proje Özetleri, p. 60, 2020.
  • J. Rubinovitz, “Design and balancing of robotic assembly lines” %1 içinde In Proceedings of the Fourth World Conference on Robotics Research, Pittsburgh, 1991.
  • H. Kim ve S. Park, “A Strong Cutting Plane Algorithm for the Robotic Assembly Line Balancing Problem” International Journal of Production Reearch, pp. 2311-2323, 1995.
  • D. S. Hong ve H. Cho, “Generation of robotic assembly sequences with consideration of line balancing using simulated annealing” Robotica, pp. 663-673, 1997.
  • G. Levithin, J. Rubinovitz ve B. Shnits, “A Genetic Algorithm for Robotic Assembly Line Balancing” European Journal of Operational Research, pp. 811-825, 2006.
  • J. Gao, L. Sun, L. Wang ve M. Gen, “An Efficient Approach for type 2 Robotic Assembly Line Balancing Problem” Computers & Industrial Engineering, pp. 1065-1080, 2009.
  • J. M. Nilakantan ve S. G. & Ponnambalam, “An efficient PSO for type 2 robotic assembly line balancing problem” %1 içinde IEEE international conference on automation science and engineering, 2012.
  • A. Yoosefelahi, M. Aminnayeri, H. Mosadegh ve H. Ardakani, “Type 2 robotic assembly line balancing problem: An evolution strategies algorithm for a multi-objective model” Journal of Manufacturing Systems, pp. 139-151, 2012.
  • S. Daoud, H. Chehade, F. Yalaoui ve L. Amodeo, “Solving a robotic assembly line balancing problem using efficient hybrid methods” Journal of Heuristics, pp. 235-259, 2014.
  • M. Aghajani, R. Ghodsi ve B. Javadi, “Balancing of robotic mixed- model two- sided assembly line with robot setup times” The internationaljournal of advanced Manufacturing Technology, pp. 1005-1016, 2014.
  • J. Nilakantan, G. Q. Huang ve S. Ponnambalam, “An investigation on minimizing cycle time and total energy consumption in robotic in assembly line systems” Journal of Cleaner Production, pp. 311-325, 2015a.
  • J. Nilakantan, S. Ponnambalam, N. Jawahar ve G. Kanagaraj, “Bio-inspired search algorithms to solve robotic assembly line balancing problems” Neural Computing and Applications, pp. 1379-1393, 2015b.
  • J. Nilakantan Mukund ve S. G. Ponnambalam, “Robotic U-shaped assembly line balancing using particle swarm optimization” Engineering Optimization, pp. 231-251, 2016.
  • M. Rabbani, Z. Mousavi ve H. Farrokhi-Asl, “Multi-objective metaheuristics for solving a type 2 robotic mixed-model assembly line balancing problem.” Journal of Industrial and Production Engineering, pp. 472-484, 2016.
  • Z. Li, M. N. Janardhanan, Q. Tang ve P. Nielsen, “Mathematical model and metaheuristics for simultaneous balancing and sequencing of a robotic mixed-model assembly line” Engineering Optimization, cilt 50, no. 5, pp. 877-893, 2018.
  • C. Müller, M. Grunewald ve T. Spengler, “Redundant configuration of robotic assembly lines with stochastic failures” International Journal of Production Research, cilt 56, no. 10, pp. 3662-3682, 2018.
  • Z. Zhang, Q. Tang, Z. Li ve L. Zhang, “Modelling and optimisation of energy-efficient U-shaped robotic assembly line balancing problems” International Journal of Production Research, pp. 5520-5537, 2019.
  • J. Pereira, M. Ritt ve Ó. C. Vásquez, “A memetic algorithm for the cost-oriented robotic assembly line balancing problem” Computers & Operations Research, cilt 99, pp. 249-261, 2018.
  • J. Q. Li ve Y. Q. Han, “A hybrid multi-objective artifical bee colony algorithm for flexible task schedulling problems in cloud computing system” Cluster Computing, pp. 2483-2499, 2020.
  • B. ZHOU ve Q. Wu, “Decomposition-based bi-objective optimization for sustainable robotic assembly line balancing problems” Journal of Manufacturing Systems, cilt 55, pp. 30-43, 2020.
  • B. Zhang, L. Xu ve J. Zhang, “Balancing and sequencing problem of mixed- model U-shaped robotic assebly line: Mathematical model and dragonfly algorithm based approach” Applied soft computing, p. 106739, 2021.
  • A. Charnes ve W. Cooper, “Management models and industrial applications of linear programming” Management Science, pp. 38-91, 1957.
  • H. Gokcen ve E. Erel, “A goal programming approach to mixed-model assembly line balancing problem” International Journal of Production Economics, pp. 177-185, 1997.
  • H. Gökçen ve K. Ağpak, “A goal programming approach to simple U-line balancing problem” European Journal of Operational Research, pp. 577-585, 2006.
  • Z. Cil, S. Mete ve K. Ağpak, “A goal programming approach for robotic assembly line balancing problem” IFAC-PapersOnLine, pp. 938-942, 2016.
  • M. Rauf, Z. Guan, S. Sarfraz, J. Mumtaz, E. Shebab, M. Jahanzaib ve M. Hanif, “A smart algorithm for multi-criteria optimization of model sequencing problem in assembly lines” Robotics and Computer-Integrated Manufacturing, p. 101844, 2020.
  • F. Jolai, M. Rezaee ve A. Vazifeh, “Multi-criteria decision making for assembly line balancing” Journal of Intelligent Manufacturing, pp. 113-121, 2009.
  • U. Özcan ve B. Toklu, “Multiple-criteria decision-making in two-side assembly line balancing: A goal programming and a fuzzy goal programming models” Computers & Operations Research, pp. 1955-1965, 2009.
  • N. Hamta, S. Ghomi, F. Jolai ve U. Bahalke, “Bi-criteria assembly line balancing by considering flexible operation times” Applied Mathematical Modelling, pp. 5592-5608, 2011.
  • A. Guitouni ve J. Martel, “Tentative guidelines to help choosing an appropriate MCDA method” European journal of operational reserch, p. 501521, 1998.
  • J. Figuera, S. Greco ve M. Ehrgott, “Multiple criteria decision analysis: State of the art surveys” New York: Springer Science&Business Media, 2005.
  • Y. Siskos, E. Grigoroudis, N. Matsatsinis, J. Figueira, S. Greco ve M. Ehrgott, “Multiple criteria decision analysis: State of the art surveys” Figueira, J., Greco, S., Ehrgott M., pp. 297-344, 2005.
  • T. Saaty, “The modern science of multi criteria decision making and its practical applications: The AHP/ANP approach.” Operation Research, pp. 1101-1118, 2013.
  • W. Ho, X. Xu ve P. Dey, “Multi-criteria decision making approaches for supplier evaluation and selection: A literature review” European Journal of Operational Research, cilt 202, no. 1, pp. 16-24, 2010.
  • B. Malakooti, “Assembly line balancing with buffers by multiple criteria optimization” The internaonal journal of production research, pp. 2159-2178, 1994.
  • M. Kabir ve M. Tabucanon, “Batch-model assembly line balancing: A multiattribute decision making approach” International Journal of Production Economics, pp. 193-201, 1995.
  • Z. Çil, S. Mete, E. Özceyla ve K. Ağpak, “A beam search approach for solving type-2 robotic assembly line balancing problem” Applied Sowft Computing, pp. 129-138, 2017.
  • J. Rezai, “Best-worst multi-criteria decision-making method.” Omega, pp. 49-57, 2015.
  • J. Rezaei, “Best-worst multi-criteria decision-making method: Some properties and a linear model” Omega, pp. 126-130, 2016.
  • D. Pamučar ve G. Ćirovič, “The selection of transport and handling resources in logistic centers using Multi-Attributive Border Approximation area Comparison (MABAC)” Expert systems with applications, pp. 3016-3028, 2015.
  • E. Triantaphyllou, “A sensitivity analysis approach for MCDM methods” Multi-criteria Decision Making Methods: A Comparative Study, pp. 131-175, 2000.
There are 51 citations in total.

Details

Primary Language Turkish
Subjects Engineering
Journal Section Makaleler
Authors

Mihrimah Özmen 0000-0002-2648-5865

Ayşe Nur Karacan 0000-0003-3942-4831

Halil İbrahim Şahin 0000-0002-9649-816X

Publication Date April 14, 2022
Submission Date July 1, 2021
Published in Issue Year 2022

Cite

APA Özmen, M., Karacan, A. N., & Şahin, H. İ. (2022). İNSAN-ROBOT İŞ BİRLİĞİ İLE ÇOK AMAÇLI MONTAJ HATTI DENGELEME. Adıyaman Üniversitesi Mühendislik Bilimleri Dergisi, 9(16), 10-36. https://doi.org/10.54365/adyumbd.960059
AMA Özmen M, Karacan AN, Şahin Hİ. İNSAN-ROBOT İŞ BİRLİĞİ İLE ÇOK AMAÇLI MONTAJ HATTI DENGELEME. Adıyaman Üniversitesi Mühendislik Bilimleri Dergisi. April 2022;9(16):10-36. doi:10.54365/adyumbd.960059
Chicago Özmen, Mihrimah, Ayşe Nur Karacan, and Halil İbrahim Şahin. “İNSAN-ROBOT İŞ BİRLİĞİ İLE ÇOK AMAÇLI MONTAJ HATTI DENGELEME”. Adıyaman Üniversitesi Mühendislik Bilimleri Dergisi 9, no. 16 (April 2022): 10-36. https://doi.org/10.54365/adyumbd.960059.
EndNote Özmen M, Karacan AN, Şahin Hİ (April 1, 2022) İNSAN-ROBOT İŞ BİRLİĞİ İLE ÇOK AMAÇLI MONTAJ HATTI DENGELEME. Adıyaman Üniversitesi Mühendislik Bilimleri Dergisi 9 16 10–36.
IEEE M. Özmen, A. N. Karacan, and H. İ. Şahin, “İNSAN-ROBOT İŞ BİRLİĞİ İLE ÇOK AMAÇLI MONTAJ HATTI DENGELEME”, Adıyaman Üniversitesi Mühendislik Bilimleri Dergisi, vol. 9, no. 16, pp. 10–36, 2022, doi: 10.54365/adyumbd.960059.
ISNAD Özmen, Mihrimah et al. “İNSAN-ROBOT İŞ BİRLİĞİ İLE ÇOK AMAÇLI MONTAJ HATTI DENGELEME”. Adıyaman Üniversitesi Mühendislik Bilimleri Dergisi 9/16 (April 2022), 10-36. https://doi.org/10.54365/adyumbd.960059.
JAMA Özmen M, Karacan AN, Şahin Hİ. İNSAN-ROBOT İŞ BİRLİĞİ İLE ÇOK AMAÇLI MONTAJ HATTI DENGELEME. Adıyaman Üniversitesi Mühendislik Bilimleri Dergisi. 2022;9:10–36.
MLA Özmen, Mihrimah et al. “İNSAN-ROBOT İŞ BİRLİĞİ İLE ÇOK AMAÇLI MONTAJ HATTI DENGELEME”. Adıyaman Üniversitesi Mühendislik Bilimleri Dergisi, vol. 9, no. 16, 2022, pp. 10-36, doi:10.54365/adyumbd.960059.
Vancouver Özmen M, Karacan AN, Şahin Hİ. İNSAN-ROBOT İŞ BİRLİĞİ İLE ÇOK AMAÇLI MONTAJ HATTI DENGELEME. Adıyaman Üniversitesi Mühendislik Bilimleri Dergisi. 2022;9(16):10-36.

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