Intelligent and collaborative Multi-Agent System to generate and schedule production orders

Abstract

The authors present a Multi-Agent System for constructing and releasing production orders. In a manufacturing enterprise, the generation of production orders consists in a set of coordinated tasks among departments. This has been achieved traditionally as amodule of the Production Activity Control (PAC) system. However, classic PAC modules lack collaborative techniques and intelligent behaviour. Moreover, in real-life situations experienced planners take over traditional PAC systems, since the range of possibilities to actually build production orders increases exponentially. To contribute to production planning, we present an intelligent and collaborative Multi-Agent System (MAS), having coordinated two forms to emulate intelligence. The learning capability is achieved by means of a Feed-forward Artificial Neural Network (FANN) with the back-propagation algorithm. The FANN is embedded within a machine agent whose objective is to obtain the appropriate machine in order to comply with requirements coming from the sales department. Also, an expert system is provided to a tool agent, which in turn is in charge of inferring the right tooling. The MAS also consists of a coordinator and a spy. The coordinator agent has the responsibility to control the flow of messages among the agents, whereas the spy agent is constantly reading the Enterprise Information System. Finally, a scheduler agent schedules the production orders. The resul-