Cyber-Physical Machine Tools for Smart Manufacturing

Abstract

Machine tools play a vital role in any manufacturing system. The performance of machine tools directly affects the product quality and the production efficiency and effectiveness. Recent advancements in Cyber-Physical Systems (CPS), Internet of Things (IoT) and cloud computing have triggered the fourth industrial revolution (Industry 4.0), in which manufacturing systems are envisioned to become Cyber- Physical Production Systems (CPPS). Current machine tools, however, are not ready to be integrated in or even dominate the envisioned CPPS. There is an urgent need to advance existing machine tools to a higher level of connectivity, intelligence and autonomy. In this context, a novel concept that represents a new generation of complete CPSbased machine tools, i.e. Cyber-Physical Machine Tool (CPMT), is proposed. CPMT is the integration of the machine tool, machining processes, computation and networking, where embedded computations monitor and control the machining processes, with feedback loops in which machining processes can affect computations and vice versa. This research aims to provide both theoretical methodology and practical solutions for CPMT. A systematic development method for CPMT is proposed based on a generic system architecture, to provide strategic and technical guidelines for advancing current machine tools to CPMT. Focused on the data interoperability issue within CPMT as well as between CPMT and other systems, two practical solutions for the development of CPMT are proposed based on two open communication standards, i.e. MTConnect and OPC UA, respectively. The proposed system architectures and methodology are successfully validated through the practical development of two CPMT prototypes, i.e. Abstract ii MTConnect and OPC UA enabled CPMT prototypes. Software applications are developed to demonstrate the functions and advantages of the proposed CPMT. A consolidated CPMT Platform is also developed to establish an interoperable data communication environment for both MTConnect and OPC UA supported machine tools. The interoperability issue between MTConnect and OPC UA is addressed by developing an MTConnect to OPC UA Interface that can convert MTConnect information models and data to their OPC UA counterparts. Furthermore, two advanced Augmented Reality (AR)-assisted HMIs are developed to provide intuitive human-machine interactions and efficient decision-making assistance for CPMT. Realtime CNC feedback-based tracking method is applied to enable faster, more accurate and more reliable augmented graphics rendering. The research work in this thesis has been reported in two journal papers and presented at three international conferences.