Agent architecture for intelligent manufacturing systems

Purpose: Analysis is made of requirements posed by tasks of agents operating in the intelligent manufacturing systems and their resulting architecture is presented. Design/methodology/approach: Architecture of agent systems for industrial environment is presented, making it possible to generate the particular agents customised for the specific tasks, based on the automatic analysis of its required features. Findings: Extension of cellular automata approach underlying the conventional agent behaviour specification using the Fuzzy Cognitive Maps is presented in conjunction with the neural networks providing learning capability of the agents designed for the various levels of the manufacturing supervisory and execution systems. Adding reaction time specification to FCM makes it possible to analyse and design systems with the required behaviour. Research limitations/implications: Specific features of the designed agent architecture have been tested as separate mechanisms which can be merged into the final comprehensive at a later stage. Originality/value: Agent architecture is proposed for the industrial applications of single agents and their groups that can collaborate to achieve the individual and joint goals specified in reaction to changing environment conditions and into their agendas in XML format. Automatic generation of custom agent reactions models can be carried out based on a set of requirements that may be specified in the if-then rules form.