The concept of intellectual manufacturing agents and the specifications of its implementation

Authors

  • Олександр Михайлович Цимбал Kharkiv National University of Radio Electronics. Lenin Ave. 14, Kharkiv, Ukraine, 61166, Ukraine
  • Артем Ігорович Бронніков Kharkiv National University of Radio Electronics. Lenin Ave. 14, Kharkiv, Ukraine, 61166, Ukraine
  • Олег Ігорович Куценко Kharkiv National University of Radio Electronics. Lenin Ave. 14, Kharkiv, Ukraine, 61166, Ukraine
  • Євген Сергійович Шеін Kharkiv National University of Radio Electronics. Lenin Ave. 14, Kharkiv, Ukraine, 61166, Ukraine

DOI:

https://doi.org/10.15587/1729-4061.2014.20109

Keywords:

manufacturing system, intelligent agent, decisionmaking

Abstract

The architecture of agent-based manufacturing systems is considered, a conceptual model of a manufacturing agent (MA) is described. The required operation features of manufacturing agent systems is self-learning, self-organization and self-adapting. The purpose of multi-agent systems is achieved by the interaction of manufacturing agents. In practice, it is offered to implement a manufacturing agent as an intelligent robotic system, which can move within the manufacturing area, carry out transport, auxiliary and separate manufacturing operations.

One of the peculiar features of the MA operation at the workspace is the determination of the process equipment position and indetermination of the transport system position, other agents and humans. Therefore, a peculiar feature of the manufacturing agent control system should be the adaptability of a decision-making system, which can create and, if necessary, modify plans of the MA operation in conditions of changing the workspace of a flexible integrated manufacturing. It is offered to observe the MA workspace by using advanced sensor systems. Herewith, one of the methods of setting assignments for the MA can be the setting by visual methods and thus, the implementation of the MA visual control. It should take into account the possible multi-zone nature of MA workspaces. The paper results were used in developing the intelligent robotic system of assembling

Author Biographies

Олександр Михайлович Цимбал, Kharkiv National University of Radio Electronics. Lenin Ave. 14, Kharkiv, Ukraine, 61166

Cand. of Tech. Sciences, Associate Professor, Academy Secretary

Артем Ігорович Бронніков, Kharkiv National University of Radio Electronics. Lenin Ave. 14, Kharkiv, Ukraine, 61166

Assistant

Technology and Manufacturing Automation Department for radio-electronic and computerizes devices

Олег Ігорович Куценко, Kharkiv National University of Radio Electronics. Lenin Ave. 14, Kharkiv, Ukraine, 61166

4th-year student

Automation and Computerized technologies Faculty

Євген Сергійович Шеін, Kharkiv National University of Radio Electronics. Lenin Ave. 14, Kharkiv, Ukraine, 61166

4th-year student

Automation and Computerized technologies Faculty

References

  1. Kerak, P. Novel trends in the intelligent manufacturing systems [Electronic resourse] / P. Kerak, R. Holubek, P. Kostal // Proc. Of 8th International Baltic Conference “Industrial Engineering”, 19-21 Apr., 2012, Tallinn, 2012. Access mode: http://innomet.ttu.ee/daaam/proceedings/pdf/Kerak.pdf.
  2. Qiao, Bing. Agent-based Intelligent Manufacturing System for the 21st Century [Electronic resourse] / Bing Qiao, Jianying Zhu // International Forum for Graduates and Young Researches of EYPO, Hannover, The World Exposition in German, 2000. Access mode: http://www.graco.unb.br/alvares/DOUTORADO/ papers_omega/www.shaping-the-future.de/pdf_www/152_paper.pdf.
  3. Parker, Chris Cooperative Decision-Making in Decentralized Multiple-Robot Systems: the Best-of-N Problem [Electronic resourse] / Chris A. C. Parker, Hong Zhang. 2009. - 12 p. - Access mode: http://ieeexplore.ieee.org/xpls/abs_all. jsp?arnumber=4801702.
  4. Цимбал, О. М. Адаптивні методи та їх використання у робототехніці [Текст] / І. Ш. Невлюдов, О. М. Цимбал, С. С. Мілютіна, А. І. Бронніков // Технология приборостроения. Харьков. – 2011. – № 1. – С. 8-12.
  5. Макарычев, В. П. Метод переменных стратегий построения траекторий движения роботов в среде с препятствиями [Текст] / В. П. Макарычев // Штучний інтелект. – 2008. – № 3. – С. 451-461.
  6. Литвин, В. В. Мультиагентні системи підтримки прийняття рішень, що базуються на прецендентах та використовують адаптивні онтології [Текст] / В. В. Литвин // Штучний інтелект. – 2009. – № 2. – С. 24-33.
  7. Atrash, Amin. Probabilistic Planning for Behavior-Based Robots [Теxt] / Amin Atrash, Sven Koenig // Proceedings of FLAIRS Conference. – 2001. – P. 531-535.
  8. Thrun, S. Probabilistic Robotics [Теxt] / S. Thrun, W. Burgard, D. Fox. – The MIT Press, 2005. – 667 p.
  9. Ross, S. Online Planning Algorithms for POMDPs [Теxt] / S. Ross, J. Pineau, S. Paquet, B. Chaib-draa // Journal of Artificial Intelligence Research. – 2008. – Vol. 32. – P. 663-704.
  10. Tsymbal, A. M. Decision-making in Robotics and adaptive tasks [Теxt] / A. M. Tsymbal, A. I. Bronnikov // Proceedings of IEEE East-West Design & Test Symposium (EWDTS’2012), Kharkov, Sept. 14-17, 2012. – P. 417-420.
  11. Bing, Qiao, Jianying, Zhu. (2000). Agent-based Intelligent Manufacturing System for the 21st Century. International Forum for Graduates and Young Researches of EYPO, Hannover, The World Exposition in German, 2000. Available at: http://www.graco.unb.br/alvares/DOUTORADO/ papers_omega/www.shaping-the-future. de/pdf_www/152_paper.pdf.
  12. Kerak, P., Holubek, R., Kostal P. (2012). Novel trends in the intelligent manufacturing systems. Proc. Of 8th International Baltic Conference “Industrial Engineering”, 19-21 Apr., 2012. Available at: http://innomet.ttu.ee/ daaam /proceedings /pdf /Kerak.pdf.
  13. Parker, Chris, Zhang, Hong (2009). Cooperative Decision-Making in Decentralized Multiple-Robot Systems: the Best-of-N Problem. - 12 p. - Available at: http://ieeexplore.ieee.org/xpls/abs_all. jsp?arnumber=4801702.
  14. Bonomi, Flavio, Milito, Rodolfo, Zhu Jiang, Sateesh Addepali (2012). Fog computing and its role in the Internet of things. MCC’12 Proceedings of the First edtion of the MCC workshop on Mobile cloud computing, 13-16.
  15. Makarychev, V. P. (2008). Metod peremennyh strategiy peremennyh strategiy postroeniya traektoriy dvigeniya robotov v srede s prepyatstviyami, Shtuchnij Intelect. Vol 3, 451-461.
  16. Litvin, V. V. (2009). Multiagentni systemy pidtrimky pryiynyattya rishen, shcho bazuyutsya na precedentah ta vykorystovuyut adaptyvni ontologiyi. Shtuchniy intelekt, Vol 2, 24-33.
  17. Atrash, Amin, Koenig, Sven (2001). Probabilistic Planning for Behavior-Based Robots. FLAIRS Conference, 531-535.
  18. Thrun, S., Burgard, W., Fox D., (2005). Probabilistic Robotics. The MIT Press, 667.
  19. Ross, S., Pineau, J., Paquet, S., Chaib-draa, B., (2008). Online Planning Algorithms for POMDPs. Journal of Artificial Intelligence Research, Vol. 32., 663-704.
  20. Tsymbal, A. M., Bronnikov, A. I., (2012). Decision-making in Robotics and adaptive tasks Proceedings of IEEE East-West Design & Test Symposium (EWDTS’2012), 417-420.

Published

2014-02-17

How to Cite

Цимбал, О. М., Бронніков, А. І., Куценко, О. І., & Шеін, Є. С. (2014). The concept of intellectual manufacturing agents and the specifications of its implementation. Eastern-European Journal of Enterprise Technologies, 1(2(67), 9–13. https://doi.org/10.15587/1729-4061.2014.20109