A Meta-Heuristic Approach for Dynamic Process Planning in Reconfigurable Manufacturing Systems

Abstract

Reconfigurable Manufacturing Systems (RMS) is a paradigm to flexibly deal with frequent changing demand and technologies. With the advancement of technology and more and more sensors and machines are connected, the world quickly enter the era of Internet of Things (IoT), which provides infrastructure for RMS. However existing studies lack a formalism that provides a framework for the development of RMS, from modeling, design to implementation. In particular, an important issue is design of dynamic process planner for RMS. This paper focuses on the development of a dynamic process planning method for the development of RMS. Modeling and managing RMS in manufacturing sector are challenging issues due to the complex workflows in the system. Recent progress in artificial intelligence and bio-inspired optimization technology provides a solid background to develop a framework to provide dynamic process planning for RMS in IoT-enabled manufacturing environment. In this paper, we propose a process planning method based on multi-agent systems (MAS) using Petri Nets to specify the workflows and capabilities of resources in the system and develop a solution algorithm based on a meta-heuristic method to solve the process planning problem based on discrete Particle swarm optimization (DPSO) approach The proposed method is illustrated by a several examples.