wilamowski-b-m-irwin-j-d-industrial-communication-systems-2011

16
Industrial Agent
Technology
Aleksey Bratukhin
Austrian Academy
of Sciences
Yoseba Peña
Landaburu
University of Deusto
Paulo Leitão
Polytechnic Institute
of Bragança
Rainer Unland
University of
Duisburg-Essen
16.1 Introduction..................................................................................... 16-1
16.2 Agents and Multi-Agent Systems.................................................. 16-2
Intelligent Agents Definition. •. Multi-Agent Systems. •. .
Ontologies. •. Self-Organization and Emergence. •. .
The Holonic Paradigm. •. Holonic Multi-Agent Systems. •. .
How Agents Can Be Implemented
16.3 Agents and Multi-Agent Systems in Industry............................16-6
16.4 Application Areas............................................................................16-6
Resource Handling. •. Order Handling. •. Comparison. •. Challenges
of Industrial Agents’ Usage. •. Other Application Areas in Brief
16.5 Agents and Multi-Agent Systems in Industry: Conclusions......16-12
Abbreviations.............................................................................................16-13
References..................................................................................................16-13
16.1 Introduction
The conventional centralized, rigid information systems cannot serve the demands of modern (manufacturing)
industry adequately any longer. In order to stay competitive, industry needs to be highly
flexible, with shorter job sizes, variable product portfolios, and always changing shop floors. Although
centralized approaches can in the meantime provide highly sophisticated and efficient scheduling solutions,
the requirements imposed by novel manufacturing trends renders centralized control systems
more and more unfeasible (cf. [8]).
Against this background, multi-agent based industrial information systems seem to be a promising
and natural alternative. They provide decentralized architecture, modularity, robustness, and adaptability
to changes (cf. [9]). Moreover, the evolution of industry in the previous decades has rearranged
the principal goals, especially in manufacturing control. In the past, the main objective was achieving
an optimal scheduling algorithm. Nowadays, this aim has been sacrificed for the sake of long-term efficiency:
on the one hand, the scheduling problem usually cannot be solved in polynomial time. Modern
centralized control system can provide a good solution if they have enough time, but, in real time, this is
still unrealistic. On the other hand, possible variations that may occur include demand changes, apparition
of new products, changes on the physical layout, disturbances, and errors. Therefore, the stress is
currently set upon other desirable features of manufacturing control systems, such as robustness, adaptability,
and real-time ability.
Finally, recent or upcoming technologies like service-oriented architectures (SOA) and modern
trends in automation (e.g., mass customization), have completely redrawn the problem domain, bringing
a bunch of new demands, such as upgradeability, platform independence, scalability, or resilience.
16-1
© 2011 by Taylor and Francis Group, LLC