Fachforen LogiMAT 2020

Chaired by: Prof. Dr. Dr. h. c. Michael ten Hompel, Managing Director of the Fraunhofer Institute of Material Flow and Logistics (IML), Chair of Materials Handling and Warehousing, TU Dortmund University

In intralogistics, digitalization and artificial intelligence will be the first to break through. Swarms of autonomous guided vehicles that organize themselves, connect to their platforms and pay for their journeys via blockchain, will become the symbol of the coming Silicon Economy in intralogistics. New business models will be created that require open and federal eco-systems, cooperations with industry and coopetition with market players. These hypotheses are discussed in this forum.

Chaired by: Prof. Dr.-Ing. Wolfgang Echelmeyer, Logistics, Material Flow Design, Operations Research, Reutlingen University, ESB Business School, member of the Intralogistics Network in Baden-Württemberg e. V.

How fast and efficiently can you react to changes in your business goals or in your order situation? What means can be used to gradually increase levels of freedom and productivity in intralogistics?
Flexibility is not an end in itself – it should give you and your company better scope for action. Applied at the right place in your processes, innovative technology gives more reaction capability, without tying up too much capital or personnel. In the I.N. Forum practitioners report on their experiences from automation projects.

Chaired by: Sandra Lehmann, Editor, LOGISTIK HEUTE, HUSS-VERLAG GmbH, Munich

Generation Greta is making it clear: When it comes to climate protection and sustainability, declarations of intent are no longer enough. So, in these times of plastic shaming and the throw-away society, packaging logistics has also had to look very closely at the theme of sustainability and develop initial solutions for packaging that are environmentally friendly and secure - for storage, transport and dispatch. What these new applications look like, what they bring and whether they are made of plastic, paper or another material entirely, will be discussed by experts from business and research.

Chaired by: Alexandra Kornacher, Head of Design, Research Group for Optimizing Added Value at the University of Augsburg (HSA_ops)

Reducing emissions is an urgent concern, if we are to meet the Climate Action Plan 2050. Commercial logistics is responsible for a part of these emissions in the transport and industrial sectors, but changes since 1990 have been marginal. The goal is still to reduce emissions in comparison to today´s levels by 55% (in transport) and 34% (in industry) by the intermediate date of 2030. In this forum experts will be exploring how this goal can still be achieved, in Pecha-Kucha-style presentations and in discussions with the audience.

Chaired by: Prof. Dr.-Ing. Philipp Gölzer, Head of the Business Area “Digitalized Production“, Fraunhofer SCS and Professor at the Technical University of Nuremberg

A great deal of data are generated in logistics processes. But when companies decide to leverage these valuable data using data analytics, they often meet problems, because of poor data quality, fragmented or incorrect data, or different formats. Or, for a particular application, the correct data may simply not be available. We show examples from practical applications, where we have overcome these hurdles and generated real added value from data for process optimization or the development of new services. The Fraunhofer SCS and partners deliver an AI reality check.

Chaired by: Prof. Dr.-Ing. Johannes Fottner, Chair in Materials Handling, Material Flow, Logistics at the Dept. of Mechanical Engineering, Technical University of Munich

Trouble-free cooperation between man and machine is one of the main pillars of Industry 4.0. The demands on logistics systems are steadily rising, driven by an increasing number of variants and rising pressure on costs and time. The latest technologies and intuitive operating concepts are offering new freedom to design the workplace of the future for a changing society. In this forum experts from business and research explain how assistance systems support human workers and in doing so, help reduce errors.

Chaired by: Waldemar Osterhoff, Senior Consultant Forum-FTS GmbH, Voerde

Smart digital factories need intelligent AGV systems that are intuitive to operate and have standardized interfaces on innovative platforms. Transport robotics in fast 5G networks are leading to intelligent and much more flexible material flow solutions. Themes covered include how 5G is bringing the vision of cyber-physical systems much closer in Industry 4.0. New system approaches in AGVs will be illustrated using an example that also integrates 5G data transmission and processing in the Edge Cloud. An example with open innovative architecture in warehouse logistics shows the new trends.

Chaired by: Peter Altes, Director, AIM-D e. V., Lampertheim

Production, the supply chain and logistics are in a process of digital transformation and are becoming ever more closely intertwined. Automatic identification systems (AutoID) form the basis of this process and of communication between people, machines and objects. Integration with software systems, Cloud connectivity (IoT/IIoT) – in particular security – present major challenges. AIM experts will demonstrate and explain to you the contribution of AutoID to digital transformation and thereby more efficient control and optimization of company processes.

Chaired by: Dr.-Ing. Kai Pfeiffer, Group Director, Service Robotics for Industry and Commerce, Fraunhofer IPA, Dortmund

Reliability and short delivery times play an ever more important role in purchase decisions. Commissioning therefore needs to be fast and efficient. Whether that job is done by a human operative or a machine, intelligent algorithms have the overview. They gather orders together in batches, plan the routes and allocate warehouse space. Artificial intelligence enables robots to reliably identify goods, grasp them securely and lay them in an ordered way in shipping cartons. By means of “deep learning”, AGVs identify the best route and adapt their driving behavior to suit the situation.