MengChu Zhou (Fellow of IEEE) joined the Department of Electrical and Computer Engineering, New Jersey Institute of Technology in 1990, and is now a Distinguished Professor. His interests are in intelligent automation, complex systems and networks, Petri nets, Internet of Things, edge/cloud computing, and big data analytics. He has over 900 publications including 12 books, over 600 journal papers including over 500 IEEE Transactions papers, 30 patents and 29 book-chapters. He is a recipient of Excellence in Research Prize and Medal from NJIT, Humboldt Research Award for US Senior Scientists from Alexander von Humboldt Foundation, and Franklin V. Taylor Memorial Award and the Norbert Wiener Award from IEEE Systems, Man, and Cybernetics Society, Distinguished Service Award from IEEE Robotics and Automation Society, and Edison Patent Award from the Research & Development Council of New Jersey. He is Fellow of International Federation of Automatic Control, American Association for the Advancement of Science, Chinese Association of Automation and National Academy of Inventors.
Talk #1
Transforming Manufacturing Industry from Automation to Intelligenization with Industry 4.0 Technologies
Industry 4.0 intends to address a fast-changing and challenging manufacturing environment with diverse demands, short order leadtime and product life cycle, limited capacities, and highly complex process technologies. A manufacturing system integrated with Industry 4.0 technologies, such as AI, machine learning, big data analytics, digital twin, and Internet of Things, is capable of performing real-time monitoring and optimization of manufacturing processes in various aspects from high level strategic resource and production planning down to real-time equipment-level smart dispatching and predictive maintenance. By fully using real-time data and AI, the system is able to help manufacturers shorten production and R&D processes, increase production capacity, reduce production cost, guarantee product quality, and improve product yield. It is suitable to help not only high-tech industries such as semiconductor wafer fabrication, but also conventional labor-intensive sectors. This talk illustrates the transformation of semiconductor manufacturing activities from automation to intelligenization by using Industry 4.0 technologies through real-life wafer fabrication applications.
Talk #2
Modeling, Scheduling and Real-time Control of Cluster Tools in Semiconductor Manufacturing
This talk intends to present Petri nets as a modeling, analysis, optimal scheduling and real-time control tool for single and multicluster tools that are widely used in semiconductor manufacturing industry. We illustrate how to use Petri nets to model various wafer production features involved in these highly expensive robotic manufacturing systems. Then we show how to use the resultant Petri net models to establish various schedulability conditions and derive extremely efficient algorithms that can compute optimal schedules for single and multi-cluster tools. When the bounded variation of activity time is caused in a fabrication process, we finally demonstrate how to adjust the scheduled robot wait time to offset such variation in order to achieve desired real-time optimal execution results. Our work focuses on those process-bounded cluster tools in which robots are fast enough such that they have some idle time in realizing an optimal schedule.