Modelling of the manufacturing system objects interactions

• Autorzy: Madejski J.
• Języki publikacji: EN

Abstrakty

EN

Purpose: Modelling of the agent based systems is presented along with a brief description of the relevant software toolkit. Design/methodology/approach: Areas of activity of the agent systems are presented, split into their internal and external domains, recognition of their world's state of affairs as well as planning of actions to affect their environment. Findings: Overview of the approach to development of the agent based systems from the general goal notion to its constituent elements, like plans and tasks. The proposed hybrid control structure allows both the horizontal level negotiations among the local agents and the vertical intervention by supervisory agents; therefore, such attitude makes also possible the multi-task and many-to-many negotiations. The result is the global control and the possibility of the decentralized negotiation. Research limitations/implications: Modelling LPA Chimera toolkit is based on Prolog which supports mainly backward chaining. Originality/value: Selection of a powerful and flexible agent systems modeling tool has been made, exemplary analysis of the agent based system model design has been presented. There agents representing the physical system elements, like a humans, machine, production line, shop floor system, the entire plant, or simply a workpiece; it may also be the part-oriented scheduling, or even the complete scheduling process.

Słowa kluczowe

EN

artificial intelligence methods; distributed artificial intelligence; modelling; analysis; CAMS; holonic manufacturing systems

PL

metody sztucznej inteligencji; rozproszona sztuczna inteligencja; modelowanie; analiza; CAMS; holonowe systemy produkcyjne

• Wydawca: International OCSCO World Press
• Czasopismo: Journal of Achievements in Materials and Manufacturing Engineering
• Rocznik: 2007
• Tom: Vol. 24, nr 2
• Strony: 167--170
• Opis fizyczny: Bibliogr. 20 poz., rys., tab.

Twórcy

autor

Madejski J.

• Division of Materials Processing Technology, Management and Computer Techniques in Materials Science, Institute of Engineering Materials and Biomaterials, Silesian University of Technology, ul. Konarskiego 18 a, 44-100 Gliwice, Poland,

Bibliografia

• [1] J. Madejski, Survey of the agent-based approach to intelligent manufacturing, Journal of Achievements in Materials and Manufacturing Engineering 21/1 (2007) 67-70.
• [2] J. Madejski, Agents as building blocks of responsibility-based manufacturing systems, Journal of Materials Processing Technology 106 (2000) 219-222.
• [3] J. Reaidy, P. Massotte, D. Diep, Comparison of negotiation protocols in dynamic agent-based manufacturing systems, Elsevier, International Journal of Production Economics 99 (2006) 117-130.
• [4] T.N. Wong, C.W. Leung, K.L. Mak, R.Y.K. Fung, Dynamic shopfloor scheduling in multi-agent manufacturing systems, Expert Systems with Applications 31/3 (2006), 486-494.
• [5] D. Wang, S.V. Nagalingam, G.C.I. Lin, Development of an agent-based Virtual CIM architecture for small to medium manufacturers, Robotics and Computer-Integrated Manufacturing 23/1 (2007) 1-16.
• [6] M.D. Reimann, J. Sarkis, An Intelligent System for Automating the Inspection of Manufacturing Parts, in Design and Implementation of Intelligent Manufacturing systems. From Expert Systems, Neural; Networks, to Fuzzy Logic ed. by H.R. Parsaei, M. Jamshidi, Prentice Hall PTR, 1995,19-38.
• [7] F.P.M. Biemans, Manufacturing Planning and Control. A Reference Model, Elsevier, 1990.
• [8] LPA Win-Prolog - Thinking Software, Tutorial, Logic Programming Associates Ltd, London, 2005.
• [9] W.F. Clocksin, C.S. Mellish, Programming in Prolog, Springer 1994.
• [10] P.H. Winston, Artificial Intelligence, Addison-Wesley Publishing Company, 1993.
• [11] Ed. L.R. Nyman, Making Manufacturing Cells Work, Society of Manufacturing Engineers in cooperation with the Computer and Automated Systems, 1992.
• [12] S. Ossowski, Co-ordination in Artificial Agent Societies, Social Structure and Its Implications for Autonomous Problem-Solving Agents, Springer 1999.
• [13] J.P. Müller, The Design of Intelligent Agents. A Layered Approach, Springer, 1996.
• [14] J. Madejski, The autonomous agent-based manufacturing systems architecture, Proceedings of the Scientific Conference on the Occasion of the 55th Anniversary of the Faculty of Mechanical Engineering of the Silesian University of Technology in Gliwice, Poland, M2E=2000, 293-302.
• [15] J. Madejski, Fuzzy logic approach to the autonomous agent task utility function evaluation, Proceedings of the 8th International Conference Achievements in Mechanical and Materials Engineering AMME'99, Rydzyna, 1999.
• [16] H. Van Brussel, L. Bongaerts, J. Wyns, P. Valckenaers, T. Van Ginderachter, A conceptual framework for holonic manufacturing: Identification of manufacturing holons, Journal of Manufacturing Systems, Journal of Manufacturing Systems, 1999 w http://findarticles.com/p/articles/mi_qa3685/is_199901/ai_n8841020/pg_l .
• [17] B. Krupińska, D. Szewieczek, Computer assistance in the technological process efficiency analysis, Journal of Achievements in Materials and Manufacturing Engineering 20 (2007) 543-546.
• [18] M. Musztyfaga, B. Skołud, Advisory system assisting selection of project structures and project team, Journal of Achievements in Materials and Manufacturing Engineering 20 (2007) 551-554.
• [19] B. Krupińska, D. Szewieczek, Analysis of technological process on the basis of efficiency criterion, Journal of Achievements in Materials and Manufacturing Engineering 17 (2006) 421-424.
• [20] A. Dobrzańska-Danikiewicz, D. Krenczyk, The selection of the production route in the assembly system, Journal of Achievements in Materials and Manufacturing Engineering 17 (2006) 417-420.