Pheromone Based Self-routing of Intelligent Products in Dynamic Manufacturing System

Abstract

This paper illustrates the capacity of a pheromone based self-routing control model for intelligent products to autonomously decide efficient processing operations and routing paths in dynamic manufacturing systems undergoing perturbations. This method is inspired by the behavior of foraging ants that leave a pheromone trail on their way to the food. Following ants use the pheromone trail with the highest concentration of pheromone to find the shortest path to the food. Self-routing of intelligent products in dynamic manufacturing systems imitates this behavior in a way that whenever a product leaves a manufacturing resource, i.e. machine, the product leaves information about the performance at the respective resource. The following products use the data from the past to render the routing decision. The discrete event simulations are analyzed by comparing statistics on throughput time data resulting from the system’s behavior in dynamic order arrival and machine breakdown situations.

This work is partially supported by the National Natural Science Foundation of China under Grant No.50805058, the Fundamental Research Funds for the Central Universities (HUST 2010MS083), and International S&T Cooperation Program of Hubei Province.