Keynote speakers

Abstract: The automotive industry is facing the transition to autonomous vehicles. This can mean novel challenges, but also chances for the redesign of assembly systems. This talk expands the idea of matrix production and explores how to exploit self-driving of autonomous cars already in an early assembly stage. Scrutinizing traditional assembly sequences, opens up potentials of up to 50% reduction of assembly takts requiring conveyor technology. This may result in a reduction of investments into material handling technology of up to 30% and may increase flexibility and changeability beyond the performance of AGV-based systems. The talk shows minimal technical and procedural requirements to exploit self-driving functions in assembly environments. Encompassing case studies from different green and brownfield assembly systems of one of the world leading OEMs serve as the basis to show the necessary reorganization of assembly sequences and consequences for assembly structures as well as assembly performance.

Prof. Dr. Julia Arlinghaus holds the Chair of Production Systems and Automation in the Department of Mechanical Engineering at Otto-von-Guericke University Magdeburg. Moreover, she is the Director of the Fraunhofer Institute for Factory Operation and Automation. After her studies of Management and Engineering at the University of Bremen, Germany and Tokyo University, Japan, she received her PhD degree in 2011 from the University of St.Gallen, Switzerland. She has worked as a consultant for operational excellence and lean management at Porsche before she accepted the appointment as a Professor of Network Optimization in Production and Logistics at Jacobs University Bremen, Germany in 2013 and 2017 as Chair of Management of Industry 4.0 at RWTH Aachen University. Together with her team, she consults companies in questions of digital and circular logistics and supply chain systems, smart and sustainable production, robotics and automation technologies as well as transformation digital transformation and innovation.

Abstract: The talk is about our search for an Industry 4.0 intelligent factory following a formal computer architecture and operating system. By so doing, computer hardware and software techniques can be adapted for high-performance factory production management. The breakthrough is achieved through a trilogy of innovations: (1) digitizing a factory with smart IoT devices into a “factory computer” (iFactory); (2) innovating iFactory visibility and traceability (VT) to enable “look around” techniques just as used in the “Out of Order Execution (OoOE)” algorithm by CPUs (Central Processing Units); and (3) developing novel models for iFactory shopfloor operations management. The iFactory architecture provides new opportunities to explore and study factory uncertainties through cyber-physical visibility and spatial-temporal traceability, and to develop brand-new data-driven decision models for factory operations planning, scheduling and execution. iFactory demonstrates a new approach to implement Industry 4.0 smart manufacturing systems for high performance, responsiveness and resilience.

George is Chair Professor of Smart Manufacturing at Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University. He gained BEng and PhD in Mechanical Engineering from Southeast University (China) and Cardiff University (UK) respectively. He has conducted research projects in areas of Smart Manufacturing, Logistics, and Construction Systems Analytics through IoT-enabled Cyber-Physical Internet with substantial government and industrial grants exceeding HK$120M. He collaborated closely with industries through joint projects and start-up companies. He has published extensively and his works have been widely cited by research communities. He serves as associate editors and editorial members for several international journals. He is Chartered Engineer (CEng), Fellow of IEEE, IISE, ASME, CILT, HKIE, and IET.

Abstract: In this talk, we discuss practical methods and digital tools to design and manage disruption-resistant supply chain networks to mitigate the ripple effects and shortages. We debate about extensions of supply chain resilience towards viability. We present the Viable Supply Chain model. Finally, we discuss the role of digital supply chain twins and platforms in managing resilience and viability, illustrate practical applications using industry examples, and project the lessons learned on possible future developments in supply chain management.

Prof. Dr. Dr. habil. Dmitry Ivanov is Professor of Supply Chain and Operations Management, director of the Digital-AI Supply Chain Lab (DAI), and faculty director M.A. Global Supply Chain and Operations Management at the Berlin School of Economics and Law. His research spans supply chain resilience and digital supply chain twins. Author of the Viable Supply Chain Model and founder of the ripple effect research in supply chains. He gained Dr., Dr. Sc., and Dr. habil. degrees and won several research excellence awards. His research record counts around 420 publications, with more than 150 papers in prestigious academic journals and the leading books “Global Supply Chain and Operations Management” (three editions), “Introduction to Supply Chain Resilience”, „Structural Dynamics and Resilience in Supply Chain Risk Management“, “Scheduling in Industry 4.0 and Cloud Manufacturing”, “Digital Supply Chain” and „Handbook of Ripple Effects in the Supply Chain“. He delivered invited plenary, keynote, panel and guest talks at the conferences of INFORMS, IFPR, IFIP, IFAC, DSI and POM, and over 30 universities worldwide. He has been Chairman, IPC Chair, and Advisory Board member for over 60 international conferences in supply chain and operations management, industrial engineering, control and information sciences. Recipient of several prestigious academic awards. Principal investigator in several research projects on resilience and digital twins including European projects ACCURATE and CERERE and the DFG Collaborative Research Cluster on Resilience of Global Supply Chains at HWR Berlin. Listed in several rankings as one of the most cited researchers in Business and Management. Chair of IFAC CC 5 “Cyber-Physical Manufacturing Systems”, Editor of International Journal of Integrated Supply Management, Associate Editor of International Journal of Production Research and OMEGA, guest editor and Editorial Board member in over 20 leading international journals including IISE Transactions, IJPE, IJPDLM, ANOR, to name a few.

Abstract: With the coming of the Industry 4.0 wave, digital representations of production systems have been promoted from marginal to central. Digital twins are not simply conceived as simulation models of their physical counterparts for offline what-if analysis, differently they are developed as self-adaptable and empowered decision-makers timely aligned with the dynamics of the real system. Enriched by these new features, digital twins are widely recognized as the key enablers for the implementation of the smart manufacturing paradigm. Despite this new role, there are significant barriers to the adoption of the digital twin concept in industrial applications. The creation and update of digital twin models is still a challenge because of the high skills required to use the simulation applications available in the market, the long development times, and their difficult integration with optimization and artificial intelligence packages. The frequent changes manufacturing systems encounter in their life cycle boost these issues. This talk describes data-driven approaches for generating multi-fidelity models for digital twins of manufacturing systems from data acquired from sensors. Application examples will also be presented.

Andrea Matta is Full Professor of Manufacturing and Production Systems at Department of Mechanical Engineering of Politecnico di Milano. He graduated in Industrial Engineering at Politecnico di Milano where he develops his teaching and research activities since 1998. He was Distinguished Professor at the School of Mechanical Engineering of Shanghai Jiao Tong University from 2014 to 2016 and Guest Professor between 2017-2019. He has been visiting professor at Ecole Centrale Paris (France), University of California at Berkeley (USA), and Tongji University (China). His research area includes analysis, design and management of manufacturing and health care systems. He is Editor in Chief of Flexible Services and Manufacturing Journal since 2017, past member of editorial board of OR Spectrum journal and IEEE Robotics and Automation Letters journal. He was Chair of the technical committee IEE RAS Sustainable Production Automation. He is member of scientific committee in several international conferences. Member of the Steering Committee of PhD on Mechanical Engineering. Member of the ADA University Advisory Board. He was awarded with the Shanghai One Thousand Talent and Eastern Scholar in 2013.