Intelligent Manufacturing and Business Processes

The Group is involved in research and elaboration of techniques applicable for handling complex production and business systems working in an uncertain, changing environment, with special emphasis on artificial intelligence and machine learning approaches.

Description

Introduction

The activities of the group can be mapped in the complex framework of Digital Enterprises research domain. Digital enterprise technology (DET) can be defined as "the collection of systems and methods for the digital modeling of the global product development and realization process, in the context of lifecycle management".

The four main research areas of the laboratory can defined as follows:

• Techniques enabling the realisation of digital factories
• Distributed shop-floor systems
• Distribute, agent-based production systems, production networks
• Knowledge management in distributed production environments

The results of the group which were achieved in the past 2-3 years were all achieved in the framework of national and international R&D projects. The research topics of our colleagues are partly overlapping, partly complementary. The key research, development and educational themes of the laboratory are as follows:

• Discrete event simulation of production and logistic systems
• Agent-based scheduling and control of manufacturing systems
• Development of agent-based, adaptive, learning systems
• Modelling, monitoring and optimisation of complex production systems
• Development of universal artificial intelligence, simulation and search techniques
• Kinematical and dynamical modelling of robotic systems
• Scheduling and control in extended enterprises
• Adaptation of e-learning approaches in the education of production systems

Scientific events

On 19-21 May 2004 the 37th CIRP International Seminar on Manufacturing Systems will take place in Budapest. The main topic of the Seminar is Digital Enterprises, Production Networks. Please find further information on www.sztaki.hu/CIRP-ISMS2004/.

The week following the above conference, on 24 and 25 May the institute will host the 5th International Workshop on Emergent Synthesis (IWES'04, www.sztaki.hu/IWES04).

Teaching

Prof. László Monostori is the leader of the University Department of Production Informatics, Management and Control Faculty of Mechanical Engineering, Budapest University of Technology and Economics. The colleagues of the laboratory regularly give lectures at the Budapest University of Technology and Economics.

Consultancy Services

Te IMBP group was the initiator of the Institute for Production and Business Management (http://www.ipbm.sztaki.hu) which was founded by the Fraunhofer Institute for Manufacturing Engineering and Automation (IPA, http://www.ipa.fhg.de) and the Computer and Automation Research Institute, Hungarian Academy of Sciences (MTA SZTAKI, http://www.sztaki.hu). The partly overlapping, partly complementary knowledge, know-how and experience accumulated in these leading institutions created a unique potential for supporting enterprises acting in the production and service industries in Hungary.

Selected Publications

Kádár, B.; Monostori, L.: Approaches to increase the performance of agent-based production systems, Lecture Notes in Computer Science; 2070: Lecture Notes in Artificial Intelligence, Engineering of Intelligent Systems, Springer, 2001, pp. 612-621.

Monostori, L.; Viharos, Zs.J.: Hybrid, AI- and simulation-supported optimisation of process chains and production plants, Annals of the CIRP, Vol. 50, No. 1, 2001, pp. 353-356.

Ilie-Zudor, E.; Monostori, L.: Modeling and management of production networks, in: Digital Enterprise Challenges, Life-cycle approach to management and production, Proceedings of the IFIP TC5 / WG5.2 & WG5.5 Eleventh International PROLAMAT Conference, November 7-10, 2001, Budapest, Hungary, Kluwer Academic Publishers, Boston, Dordrecht, London, pp. 60-71.

Ilie-Zudor, E.; Monostori, L.; Kádár, B.; Cavalieri, S.; Von Cieminski, G.; Di Mascolo, M.; Campi, A.: Integration of on-line and face-to-face learning at an international platform for teaching and research, Proceedings of the 18^{th International Conference on Advanced Science and Technology, ICAST 2002}, August 17, 2002, Chicago, Illinois, USA, pp. 133-139.

Monostori, L.; Váncza, J.; Márkus, A.; Kádár, B.; Viharos, Zs.J.: Towards the realisation of Digital Enterprises, Proceedings of the 36th CIRP International Seminar on Manufacturing Systems, Progress in Virtual Manufacturing Systems, June 3-5, 2003, Saarbrücken, Germany, pp. 99-106.

Csáji, B.Cs.; Kádár, B.; Monostori, L.: Improving multi-agent-based scheduling by neurodynamic programming, Lecture Notes in Computer Science; 2744: Lecture Notes in Artificial Intelligence, Holonic and Mult-Agent Systems for Manufacturing, Springer, 2003, pp. 110-123.

Monostori, L.: AI and machine learning techniques for managing complexity, changes and uncertainties in manufacturing, Engineering Applications of Artificial Intelligence, Elsevier, The Netherlands, Vol. 16, No. 4, 2003, pp. 277-291.

Monostori, L.; Váncza, J.; Márkus, A.; Kádár, B.; Viharos, Zs.J.: Digital Enterprises: First results of a national R&D project, Proceedings of IROS 2003, 2003 IEEE/RSJ International Conference of Intelligent Robots and Systems, October 27-31, 2003, Las Vegas, Nevada, U.S.A., IEEE, ISBN: 0-7803-7861-X, pp. 2335-2340.

Viharos, Zs. J.; Monostori, L.; Csongrádi, Z.: Realizing the digital factory: monitoring of complex production systems, Intelligent Manufacturing Systems 2003, Elsevier, 2003, pp. 29-34.

Kovács, A.; Váncza, J.; Kádár, B.; Monostori, L.; Pfeiffer, A.: Real-life scheduling using constraint programming and simulation, Intelligent Manufacturing Systems 2003, Elsevier, 2003, pp. 213-218.