Reducing the standard deviation when integrating process planning and production scheduling through the use of expert systems in an agent-based environment

Abstract

The main objective of this work is the reduction of the standard deviation generated through the routing of production orders in manufacturing resources in a job shop environment. This reduction is obtained through the suggestion of the best machining route for each job order in a simulation, based upon historic simulation data (base of facts) and a set of rules. In order to generate these routes, an expert agent and the expert system were developed. This agent is responsible for processing the information and controlling the rule engine, whereas the expert system code is responsible for the rules that will be chosen to be loaded and applied by the agent. © 2008 Springer-Verlag London Limited.