The introduction of CIM (Computer Integrated Manufacturing) systems in the 1980s, aiming at integrating automatic workstations into fully automated factories, was not successful. The root causes of this failure were that the subsystems to be integrated were not suitably designed for easy integration into a larger system. This situation stimulated the authors to embark on a research programme on ‘design for the unexpected’. It defined how subsystems have to be designed so that integration into larger systems becomes easier and how such an integrated system can be controlled so that it can cope with change and disturbances. In the paper, the design principles and salient features of holonic manufacturing systems (HMS) are outlined. The PROSA reference architecture, defining the basic structure of any HMS, is described. It is further explained how coordination and control of the HMS is achieved by a holonic manufacturing execution system (HMES), based on the combination of the PROSA reference architecture and a biologically inspired Delegate Multiagent System (DMAS). Finally, the power and universality of the PROSA/DMAS system is demonstrated by some case studies from manufacturing, robotics and open air engineering.
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Purpose: Summary of the state-of-the-art of the Distributed Artificial Intelligence applied to Intelligent Manufacturing. Main applications are presented along with different technologies applied in these areas. Design/methodology/approach: Intelligent Manufacturing area was split into many segments, which require different approach to intelligent problem solving. Multiagent systems negotiation needs were analysed and cooperation issues in the form of clustering, cloning, and learning were analysed in search for relevant tools. Findings: Detailed review of the approach to development of the agent based Intelligent Manufacturing from the fundamental considerations to the latest hands-on developments. Research limitations/implications: Many presented technologies call for detailed study before they can be implemented in practice. Originality/value: Thorough review of the Distributed Artificial Intelligence approach to current agile manufacturing needs. Key technologies are pointed out along with the main areas in which they can be implemented, and which require further research.
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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.
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