Study of manufacturing resource perception and process control of a radio-frequency-identification-enabled decentralized flexible manufacturing system

Abstract

The fusion of mechatronics, communication, control, and information technologies has introduced new automation paradigms into the production environment. Plug-and-play flexible manufacturing systems will become suitable approaches in the future for the development of modular, flexible, and reconfigurable manufacturing systems, addressing the requirements of global markets. This article introduces a Petri Net model-driven methodology for the development, validation, and operation of a radio-frequency identification-enabled decentralized flexible manufacturing system. After analyzing the manufacturing processes and resources of a flexible manufacturing system, the manufacturing resources are classified into active and passive resources. Each active resource is equipped with a radio-frequency identification reader and each passive resource is banded with a radio-frequency identification tag. Real-time state and behavior logic models are built for manufacturing resources based on extended Petri Nets; the models are translated into XML and integrated with the manufacturing resources. In this fashion, each manufacturing resource becomes an autonomous agent, and it can make self-decisions and update its status through the twinned models. In this manner, automatic perception and process control are realized. Finally, the effectiveness and feasibility of the method are verified in an experimental system.