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Prof. Birgit Vogel-Heuser is Chair Professor of Automation and Information Systems in Mechanical Engineering, Technical University of Munich. She received her Dipl. Ing. degree in electrical engineering in 1987 and her Dr.-Ing. degree in mechanical engineering in 1990 from the RWTH Aachen, Germany. She was involved in industrial automation with the machine and plant manufacturing industry for nearly ten years, including a position as technical director for the Siempelkamp Group. After various professorship positions in Hagen, Wuppertal, and Kassel, she was appointed to the Chair of Automation and Information Systems at TUM in 2009. Currently,   she is in the area of systems and software engineering as well as in the modeling of distributed and reliable embedded systems. Especially, her research foci are put on the challenges that result from the increasing demand to produce customer-specific products in the plant manufacturing domain. Engineering and education on the hybrid process and heterogeneous distributed and intelligent systems using a human-centered approach are also included in her research area. Prof.Vogel-Heuser has over 500 scientific publications and 72 book chapters and she is also an editor of the handbook Industrie 4.0. She is a Senior Member of the IEEE and a member of the National Academy of Science and Engineering (acatech). She serves as the editor of IEEE Transactions on Automation Science and Engineering (IEEE T-ASE) and IFAC Journal of Systems and Control. She was the Keynote speaker of the International Conference on Advanced Robotics and Intelligent Systems (ARIS 2020). She is also a member of various advisory boards, including the advisory board of the VDI/VDE-GMA and the board of trustees of the German Museum.

Talk # 1

Enabling and managing self-x manufacturing systems (for Industry 4.0)

As manufacturing systems need to be more flexible not only due to changed products but also due to crises and short-term changes in supply chains, a mechanism is required to enable this flexibility. Multi-agent systems will be introduced as a successful design paradigm to enable and manage self-x manufacturing systems. The talk will introduce the concept, industrial applications on the field level, and criteria for deciding where to run MAS.

Talk # 2

Forever young automated Production Systems - How can evolution of control software be managed and enable flexibility of automated production systems

To enable the flexibility of long-living automated Production Systems that are already in operation, changes to the control software are often the only feasible option. Consequently, it is necessary to manage variants and versions of control software in relation to its mechanical and electrical hardware and automation platforms of every machine or plant delivered for decades. To facilitate updates in the future, the legacy code should be refactored to achieve a higher degree of modularity and reuse. The talk will introduce the concepts of analyzing legacy code, measuring modularity and code quality, and the challenges of applying product line approaches to control software of automated Production Plants.

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.