Real-time distributed scheduling of heterarchical manufacturing systems

Duffie, Neil A.; Prabhu, Vittaldas V.

doi:10.1016/0278-6125(94)90025-6

Cited by 170 publications

(62 citation statements)

References 16 publications

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“…In multi-agent scheduling, agents manipulate resource and/or order variables under their own authority. Potential job interactions are handled by agents telling each other their aggregate workloads and free capacities [110] [111]. Since global consistency can hardly be guaranteed, constraint checking or simulation is needed.…”

Section: Market-based Approachesmentioning

confidence: 99%

Agent-Based Systems for Manufacturing

2006

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The emerging paradigm of agent-based computation has revolutionized the building of intelligent and decentralized systems. The new technologies met well the requirements in all domains of manufacturing where problems of uncertainty and temporal dynamics, information sharing and distributed operation, or coordination and cooperation of autonomous entities had to be tackled. In the paper software agents and multi-agent systems are introduced and through a comprehensive survey, their potential manufacturing applications are outlined. Special emphasis is laid on methodological issues and deployed industrial systems. After discussing open issues and strategic research directions, we conclude that the evolution of agent technologies and manufacturing will probably proceed hand in hand. The former can receive real challenges from the latter, which, in turn, will have more and more benefits in applying agent technologies, presumably together with well-established or emerging approaches of other disciplines.

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Section: Market-based Approachesmentioning

confidence: 99%

Agent-Based Systems for Manufacturing

2006

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“…An advantage of hierarchical control is that it allows the control problem to be divided to limit the complexity of the entire structure [32]. These implicit assumptions are the cause of the main drawbacks of hierarchical architectures such as long lead times, high inventory, tardiness, and handling of runtime errors [33].…”

Section: Shop Floor Controlmentioning

confidence: 99%

A data mining integrated architecture for shop floor control

Srinivas

Harding

2008

Proceedings of the Institution of Mechanical Engineers, Part B:

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The dynamics of the market are forcing shop floor control systems to enhance their intelligence and reactivity to change. The control system must also have mechanisms to process the vast amount of data, which is generated with the application of cheap data logging systems and should also incorporate a mechanism for continuous learning. Data mining provides a mechanism for analysing data and generating new knowledge. This paper presents an intelligent knowledge-based decision support system for shop floor control, which incorporates data mining techniques and intelligent agent technology to provide useful information, knowledge, and a mechanism for continuous learning. The functioning of the system is described and the architecture of different agents that constitute the system has been discussed in terms of the different modules required. A process to integrate the individual data mining agents associated with the different processes has also been described. Finally a prototype of the system is presented to demonstrate the application of this agent-based system.

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“…This system design resulted in reduced complexity, higher fault tolerance, shorter development times and lower development costs [18]. Based on this and further preliminary work, Duffie et al developed and enhanced distributed scheduling heuristics and analysed their performances using both simulation models and different experimental manufacturing systems [19], [20]. The already mentioned Holonic Manufacturing paradigm mostly focuses on the control level and, more specifically, on the concept of autonomous cooperating agents (holons) operating in the shop floor (Figure 4).…”

Section: Scheduling and Controlmentioning

confidence: 99%

Autonomous Processes in Assembly Systems

2007

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Today's assembly systems have to be flexible to adapt quickly to an increasing number and variety of products and changing demand volume. To manage these dynamics, flexible, reconfigurable, and autonomous assembly systems were proposed and partly realised in the last two decades. The flexibility and adaptability is realised by clustering the assembly system into subsystems and modules which get a certain degree of autonomy and control themselves in a decentralised way. This keynote paper will present the general principles of autonomy and the proposed concepts, methods and technologies to realise autonomous processes in assembly systems. Different approaches for design and autonomous operation of assembly will be explained and future trends towards fully autonomous components of an assembly system as well as autonomous parts and products will be discussed.

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Real-time distributed scheduling of heterarchical manufacturing systems

Cited by 170 publications

References 16 publications

Agent-Based Systems for Manufacturing

Agent-Based Systems for Manufacturing

A data mining integrated architecture for shop floor control

Autonomous Processes in Assembly Systems

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