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Artificial Intelligence Techniques for Networked Manufacturing Enterprises Management pp 43–86Cite as

Agent-based System for Knowledge Acquisition and Management Within a Networked Enterprise

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Part of the book series: Springer Series in Advanced Manufacturing ((SSAM))

Abstract

The examination of tasks involved in the gathering and processing of fault information with enterprises has shown that there are several stages where human errors can occur and has also revealed inefficient and time-consuming operations, resulting in bottlenecks that can reduce the potential benefits of automatic rule generation. Therefore, these various tasks could themselves be automated through the use of agent-based systems and machine learning techniques. This chapter shows that it is possible to automate the gathering and manipulation of fault reports using an agent-based system. Such a system can remove the need for manual processing of fault reports and the problems that may result from this. It also shows that a finite state automata (FSA)-based agent architecture is suitable for application in this particular problem domain, due to the reactive nature of an FSA. An FSA and state-table approach coupled with the modularity of the system should also enable it to be modified readily for different applications.

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  1. Manufacturing Engineering Centre, Cardiff University, Queen’s Buildings, CF24 3AA, Cardiff, UK

    A. J. Soroka

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    Lyes Benyoucef

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    Bernard Grabot

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Soroka, A. (2010). Agent-based System for Knowledge Acquisition and Management Within a Networked Enterprise. In: Benyoucef, L., Grabot, B. (eds) Artificial Intelligence Techniques for Networked Manufacturing Enterprises Management. Springer Series in Advanced Manufacturing. Springer, London. https://doi.org/10.1007/978-1-84996-119-6_2

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