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Esnek Üretim Sistemlerinin Dinamik Çizelgelenmesi için Çoklu Etmen Yaklaşımı ve Yönlendirme Kurallarının Karşılaştırılması

Year 2023, Volume: 38 Issue: 1, 61 - 72, 30.03.2023
https://doi.org/10.21605/cukurovaumfd.1273705

Abstract

Üretim ortamlarında, makineler ve otomatik yönlendirmeli araçlar gibi sistem öğelerinin kontrol edilmesi zor olabilmektedir. Etmen tabanlı sistemler, üretim ortamlarında iş kesintileri, makine arızaları gibi dinamik olaylar meydana geldiğinde operasyonları yönetmek için etkili yöntemler sunmaktadır. Bu çalışmada, Çoklu Etmen Sistemi (MAS) mimarisi aracılığıyla esnek bir üretim sistemindeki AGV’lerin ve makinelerin dinamik çizelgeleme problemine uygulanmış ve elde edilen sonuçları literatürde yaygın olarak kullanılan yönlendirme kurallarıyla karşılaştırılmıştır. Çoklu etmen tabanlı yaklaşımlar dağıtılmış, stokastik, sürekli ve yüksek hesaplama karmaşıklığına sahiptir. Etmenler arasında yapılan müzakereler ve teklif verme sonucunda uygun çizelgeler ortaya çıkar. Literatürden alınan bir vaka çalışması etmen mimarisine uygulanmış ve çevrimiçi çizelgeleme kuralları (yönlendirme/sevk kuralları) ile karşılaştırılmıştır. Elde edilen sonuçlara göre, MAS gerçek zamanlı olarak iyi çizelgeler üretebildiği ve makespan performans metriği açısından yaygın olarak kullanılan yönlendirme kuralları ile karşılaştırılabilir olduğu bulunmuştur.

References

  • 1. Gou, L., Luh, P.B., Kyoya, Y., 1998. Holonic Manufacturing Scheduling: Architecture, Cooperation Mechanism, and Implementation. Computers in Industry, 37(3), 213-231.
  • 2. Jerald, J., Asokan, P., Saravanan, R., Delphin Carolina Rani A., 2006. Simultaneous Scheduling of Parts and Automated Guided Vehicles in an FMS Environment Using Adaptive Genetic Algorithm. The International Journal of Advanced Manufacturing Technology, 29(5), 584-589.
  • 3. Wang, J., Deng, Y., 1999. Incremental Modeling and Verification of Flexible Manufacturing Systems. Journal of Intelligent Manufacturing, 10(6), 485-502.
  • 4. Veeravalli, B., Rajesh, G., Viswanadham, N., 2002. Design and Analysis of Optimal Material Distribution Policies in Flexible Manufacturing Systems Using a Single AGV. International Journal of Production Research, 40(12), 2937-2954.
  • 5. Lun, M., Chen, F., 2000. Holonic Concept Based Methodology for Part Routing on Flexible Manufacturing Systems. The International Journal of Advanced Manufacturing Technology, 16(7), 483-490.
  • 6. Babiceanu, R.F., Chen, F.F., Sturges, R.H., 2005. Real-Time Holonic Scheduling of Material Handling Operations in A Dynamic Manufacturing Environment. Robotics and Computer-Integrated Manufacturing, 21(4-5), 328-337.
  • 7. MacCarthy, B., Liu, J., 1993. A New Classification Scheme for Flexible Manufacturing Systems. The International Journal of Production Research, 31(2), 299-309.
  • 8. De Toni, A., Tonchia, S., 1998. Manufacturing Flexibility: A Literature Review. International Journal of Production Research, 36(6), 1587-1617.
  • 9. Ross, E.A., Mahmoodi, F., Mosier, C.T., 1996. Tandem Configuration Automated Guided Vehicle Systems: A Comparative Study. Decision Sciences, 27(1), 81-102.
  • 10. Seo, Y., Egbelu, P.J., 1999. Integrated Manufacturing Planning for an AGV-Based FMS. International Journal of Production Economics, 60, 473-478.
  • 11. Farling, B., Mosier, C., Mahmoodi, F., 2001. Analysis of Automated Guided Vehicle Configurations in Flexible Manufacturing Systems. International Journal of Production Research, 39(18), 4239-4260.
  • 12. Haq, A.N., Karthikeyan, T., Dinesh, M., 2003. Scheduling Decisions in FMS Using A Heuristic Approach. The International Journal of Advanced Manufacturing Technology, 22(5), 374-379.
  • 13. Hall, N.G., Sriskandarajah, C., Ganesharajah, T., 2001. Operational Decisions in AGV-Served Flowshop Loops: Scheduling. Annals of Operations Research, 107(1), 161-188.
  • 14. Ganesharajah, T., Hall, N.G., Sriskandarajah, C., 1998. Design and Operational Issues in AGV-Served Manufacturing Systems. Annals of Operations Research, 76, 109-154.
  • 15. Shen, Y.-C., Kobza, J.E., 1998. A Dispatching-Rule-Based Algorithm for Automated Guided Vehicle Systems Design. Production Planning & Control, 9(1), 47-59.
  • 16. Reveliotis, S.A., 2000. Conflict Resolution in AGV Systems. Iie Transactions, 32(7), 647-659.
  • 17. Qiu, L., Hsu, W.J., Huang, S.Y., Wang, H., 2002. Scheduling and Routing Algorithms for Agvs: A Survey. International Journal of Production Research, 40(3), 745-760.
  • 18. Dotoli, M., Fanti, M., 2004. Coloured Timed Petri Net Model for Real-Time Control of Automated Guided Vehicle Systems. International Journal of Production Research, 42(9), 1787-1814.
  • 19. Singh, N., Sarngadharan, P., Pal, P.K., 2011. AGV Scheduling for Automated Material Distribution: A Case Study. Journal of Intelligent Manufacturing, 22(2), 219-228.
  • 20. Komma, V.R., Jain, P.K., Mehta, N.K., 2011. an Approach for Agent Modeling in Manufacturing on JADE™ Reactive Architecture. The International Journal of Advanced Manufacturing Technology, 52, 1079-1090.
  • 21. Erol, R., Şahin, C., Baykasoğlu, A., Kaplanoğlu, V., 2012. A Multi-Agent Based Approach to Dynamic Scheduling of Machines and Automated Guided Vehicles in Manufacturing Systems. Applied Soft Computing, 12(6), 1720-1732.
  • 22. Sahin, C., Demirtaş, M., Erol, R., Baykasoğlu, A., Kaplanoğlu, V., 2017. A Multi-Agent Based Approach to Dynamic Scheduling with Flexible Processing Capabilities. Journal of Intelligent Manufacturing, 28, 1827-1845.
  • 23. Ricardo Rodríguez, A.R., Benítez, I.F., González Yero, G., Núñez Alvarez, J.R., 2022. Multi-Agent System for Steel Manufacturing Process. International Journal of Electrical and Computer Engineering (IJECE), 12(3), 2441-2453.
  • 24. Azeroual, M., Boujoudar, Y., Aljarbouh, A., Fayaz, M., Qureshi, M.S., El Moussaoui, H., El Markhi, H., 2022. Advanced Energy Management and Frequency Control of Distributed Microgrid Using Multi-Agent Systems. International Journal of Emerging Electric Power Systems, 23(5), 755-766.
  • 25. Padgham, L., Winikoff, M., 2005. Developing Intelligent Agent Systems: A Practical Guide. John Wiley & Sons, England, 221.
  • 26. Padgham, L., Lambrix, P., 2005. Formalisations of Capabilities for BDI-Agents. Autonomous Agents and Multi-Agent Systems, 10(3), 249-271.
  • 27. Cil, I., Mala M., 2010. A Multi-Agent Architecture for Modelling and Simulation of Small Military Unit Combat in Asymmetric Warfare. Expert Systems with Applications, 37(2), 1331-1343.
  • 28. Wooldridge, M., Jennings, N.R., 1995. Intelligent Agents: Theory and Practice. The Knowledge Engineering Review, 10(2), 115-152.
  • 29. Farahvash, P., Boucher, T.O., 2004. A Multi-Agent Architecture for Control of AGV Systems. Robotics and Computer-Integrated Manufacturing, 20(6), 473-483.
  • 30. Evertsz, R., Fletcher, M., Jones, R., Jarvis, J., Brusey, J., Dance, S., 2003. Implementing Industrial Multi-Agent Systems Using JACKTM. In Programming Multiagent Systems, First International Workshop (ProMAS’03), 3067, 18-48.
  • 31. Bellifemine, F.L., Caire, G., Greenwood, D., 2007. Developing Multi-Agent Systems with JADE. John Wiley & Sons, England, 312.
  • 32. Komma, V.R., Jain, P.K., Mehta, N.K., 2011. An Approach for Agent Modeling in Manufacturing on JADE™ Reactive Architecture. The International Journal of Advanced Manufacturing Technology, 52(9), 1079-1090.
  • 33. Bordini, R.H., Braubach, L., Dastani, M., Seghrouchni, A.E.F., Gomez-Sanz, J.J., Leite, J., O’Hare, G., Pokahr, A., Ricci, A., 2006. A Survey of Programming Languages and Platforms for Multi-Agent Systems. Informatica, 30(1).
  • 34. Şahin, C., 2010. Multi-Agent Approach for the Scheduling of Manufacturing Systems. Doktora Tezi, Çukurova Üniversitesi, Fen Bilimleri Enstitüsü, Endüstri Mühendisliği Anabilim Dalı, Adana, 116.
  • 35. Bilge, Ü., Ulusoy, G., 1995. A Time Window Approach to Simultaneous Scheduling of Machines and Material Handling System in an FMS. Operations Research, 43(6), 1058-1070.

Comparison of Multi-Agent Approach and Dispatching Rules for Dynamic Scheduling of Flexible Manufacturing Systems

Year 2023, Volume: 38 Issue: 1, 61 - 72, 30.03.2023
https://doi.org/10.21605/cukurovaumfd.1273705

Abstract

In production environments, controlling system elements such as machines and automated guided vehicles can be challenging. Agent-based systems provide effective methods for managing operations when such dynamic events occur, such as job interruptions in production environments, machine breakdowns. Through a Multi-Agent System (MAS) architecture, this study attempts to solve the dynamic scheduling problem of AGVs and machines in a flexible manufacturing system, and compares it to dispatching rules commonly used in the literature. Multi-agent-based approaches are distributed, stochastic, continuous, and have high computational complexity. As a result of negotiations and bidding among agents, appropriate schedules emerge. A case study taken from the literature is applied to the architecture and compared to online scheduling rules (dispatching rules). Based on the results, it was found that the MAS is capable of generating good schedules in terms of makespan performance criteria in real time and is comparable to commonly used dispatching rules in terms of performance.

References

  • 1. Gou, L., Luh, P.B., Kyoya, Y., 1998. Holonic Manufacturing Scheduling: Architecture, Cooperation Mechanism, and Implementation. Computers in Industry, 37(3), 213-231.
  • 2. Jerald, J., Asokan, P., Saravanan, R., Delphin Carolina Rani A., 2006. Simultaneous Scheduling of Parts and Automated Guided Vehicles in an FMS Environment Using Adaptive Genetic Algorithm. The International Journal of Advanced Manufacturing Technology, 29(5), 584-589.
  • 3. Wang, J., Deng, Y., 1999. Incremental Modeling and Verification of Flexible Manufacturing Systems. Journal of Intelligent Manufacturing, 10(6), 485-502.
  • 4. Veeravalli, B., Rajesh, G., Viswanadham, N., 2002. Design and Analysis of Optimal Material Distribution Policies in Flexible Manufacturing Systems Using a Single AGV. International Journal of Production Research, 40(12), 2937-2954.
  • 5. Lun, M., Chen, F., 2000. Holonic Concept Based Methodology for Part Routing on Flexible Manufacturing Systems. The International Journal of Advanced Manufacturing Technology, 16(7), 483-490.
  • 6. Babiceanu, R.F., Chen, F.F., Sturges, R.H., 2005. Real-Time Holonic Scheduling of Material Handling Operations in A Dynamic Manufacturing Environment. Robotics and Computer-Integrated Manufacturing, 21(4-5), 328-337.
  • 7. MacCarthy, B., Liu, J., 1993. A New Classification Scheme for Flexible Manufacturing Systems. The International Journal of Production Research, 31(2), 299-309.
  • 8. De Toni, A., Tonchia, S., 1998. Manufacturing Flexibility: A Literature Review. International Journal of Production Research, 36(6), 1587-1617.
  • 9. Ross, E.A., Mahmoodi, F., Mosier, C.T., 1996. Tandem Configuration Automated Guided Vehicle Systems: A Comparative Study. Decision Sciences, 27(1), 81-102.
  • 10. Seo, Y., Egbelu, P.J., 1999. Integrated Manufacturing Planning for an AGV-Based FMS. International Journal of Production Economics, 60, 473-478.
  • 11. Farling, B., Mosier, C., Mahmoodi, F., 2001. Analysis of Automated Guided Vehicle Configurations in Flexible Manufacturing Systems. International Journal of Production Research, 39(18), 4239-4260.
  • 12. Haq, A.N., Karthikeyan, T., Dinesh, M., 2003. Scheduling Decisions in FMS Using A Heuristic Approach. The International Journal of Advanced Manufacturing Technology, 22(5), 374-379.
  • 13. Hall, N.G., Sriskandarajah, C., Ganesharajah, T., 2001. Operational Decisions in AGV-Served Flowshop Loops: Scheduling. Annals of Operations Research, 107(1), 161-188.
  • 14. Ganesharajah, T., Hall, N.G., Sriskandarajah, C., 1998. Design and Operational Issues in AGV-Served Manufacturing Systems. Annals of Operations Research, 76, 109-154.
  • 15. Shen, Y.-C., Kobza, J.E., 1998. A Dispatching-Rule-Based Algorithm for Automated Guided Vehicle Systems Design. Production Planning & Control, 9(1), 47-59.
  • 16. Reveliotis, S.A., 2000. Conflict Resolution in AGV Systems. Iie Transactions, 32(7), 647-659.
  • 17. Qiu, L., Hsu, W.J., Huang, S.Y., Wang, H., 2002. Scheduling and Routing Algorithms for Agvs: A Survey. International Journal of Production Research, 40(3), 745-760.
  • 18. Dotoli, M., Fanti, M., 2004. Coloured Timed Petri Net Model for Real-Time Control of Automated Guided Vehicle Systems. International Journal of Production Research, 42(9), 1787-1814.
  • 19. Singh, N., Sarngadharan, P., Pal, P.K., 2011. AGV Scheduling for Automated Material Distribution: A Case Study. Journal of Intelligent Manufacturing, 22(2), 219-228.
  • 20. Komma, V.R., Jain, P.K., Mehta, N.K., 2011. an Approach for Agent Modeling in Manufacturing on JADE™ Reactive Architecture. The International Journal of Advanced Manufacturing Technology, 52, 1079-1090.
  • 21. Erol, R., Şahin, C., Baykasoğlu, A., Kaplanoğlu, V., 2012. A Multi-Agent Based Approach to Dynamic Scheduling of Machines and Automated Guided Vehicles in Manufacturing Systems. Applied Soft Computing, 12(6), 1720-1732.
  • 22. Sahin, C., Demirtaş, M., Erol, R., Baykasoğlu, A., Kaplanoğlu, V., 2017. A Multi-Agent Based Approach to Dynamic Scheduling with Flexible Processing Capabilities. Journal of Intelligent Manufacturing, 28, 1827-1845.
  • 23. Ricardo Rodríguez, A.R., Benítez, I.F., González Yero, G., Núñez Alvarez, J.R., 2022. Multi-Agent System for Steel Manufacturing Process. International Journal of Electrical and Computer Engineering (IJECE), 12(3), 2441-2453.
  • 24. Azeroual, M., Boujoudar, Y., Aljarbouh, A., Fayaz, M., Qureshi, M.S., El Moussaoui, H., El Markhi, H., 2022. Advanced Energy Management and Frequency Control of Distributed Microgrid Using Multi-Agent Systems. International Journal of Emerging Electric Power Systems, 23(5), 755-766.
  • 25. Padgham, L., Winikoff, M., 2005. Developing Intelligent Agent Systems: A Practical Guide. John Wiley & Sons, England, 221.
  • 26. Padgham, L., Lambrix, P., 2005. Formalisations of Capabilities for BDI-Agents. Autonomous Agents and Multi-Agent Systems, 10(3), 249-271.
  • 27. Cil, I., Mala M., 2010. A Multi-Agent Architecture for Modelling and Simulation of Small Military Unit Combat in Asymmetric Warfare. Expert Systems with Applications, 37(2), 1331-1343.
  • 28. Wooldridge, M., Jennings, N.R., 1995. Intelligent Agents: Theory and Practice. The Knowledge Engineering Review, 10(2), 115-152.
  • 29. Farahvash, P., Boucher, T.O., 2004. A Multi-Agent Architecture for Control of AGV Systems. Robotics and Computer-Integrated Manufacturing, 20(6), 473-483.
  • 30. Evertsz, R., Fletcher, M., Jones, R., Jarvis, J., Brusey, J., Dance, S., 2003. Implementing Industrial Multi-Agent Systems Using JACKTM. In Programming Multiagent Systems, First International Workshop (ProMAS’03), 3067, 18-48.
  • 31. Bellifemine, F.L., Caire, G., Greenwood, D., 2007. Developing Multi-Agent Systems with JADE. John Wiley & Sons, England, 312.
  • 32. Komma, V.R., Jain, P.K., Mehta, N.K., 2011. An Approach for Agent Modeling in Manufacturing on JADE™ Reactive Architecture. The International Journal of Advanced Manufacturing Technology, 52(9), 1079-1090.
  • 33. Bordini, R.H., Braubach, L., Dastani, M., Seghrouchni, A.E.F., Gomez-Sanz, J.J., Leite, J., O’Hare, G., Pokahr, A., Ricci, A., 2006. A Survey of Programming Languages and Platforms for Multi-Agent Systems. Informatica, 30(1).
  • 34. Şahin, C., 2010. Multi-Agent Approach for the Scheduling of Manufacturing Systems. Doktora Tezi, Çukurova Üniversitesi, Fen Bilimleri Enstitüsü, Endüstri Mühendisliği Anabilim Dalı, Adana, 116.
  • 35. Bilge, Ü., Ulusoy, G., 1995. A Time Window Approach to Simultaneous Scheduling of Machines and Material Handling System in an FMS. Operations Research, 43(6), 1058-1070.
There are 35 citations in total.

Details

Primary Language Turkish
Subjects Engineering
Journal Section Articles
Authors

Cenk Şahin This is me 0000-0002-6076-7794

Rızvan Erol This is me 0000-0001-6914-5062

Publication Date March 30, 2023
Published in Issue Year 2023 Volume: 38 Issue: 1

Cite

APA Şahin, C., & Erol, R. (2023). Esnek Üretim Sistemlerinin Dinamik Çizelgelenmesi için Çoklu Etmen Yaklaşımı ve Yönlendirme Kurallarının Karşılaştırılması. Çukurova Üniversitesi Mühendislik Fakültesi Dergisi, 38(1), 61-72. https://doi.org/10.21605/cukurovaumfd.1273705