Supply Chain Services SCS

The ADA Lovlace Center for Data, Analytics and Applications combines AI research with AI applications for business in Bavaria. In a conversation with Ada Lovelace, the ADA Lovelace Center's namesake, the experts talk about their work, their research projects and news from the partner network.

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How data recycling and clever use of the data life cycle lead to greater sustainability in business and industry.

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The human element plays a major role in the success and the productivity of Industry 4.0 technologies and applications. This is why we also look at each phase of digitalization from a behavioral and sociological perspective. In this interview with Stephanie Schmitt-Rüth, head of the Human Centered Innovation group, you can find out how we support companies as they plan and design the rollout and communication of their digital transformation to ensure it enhances motivation and productivity.

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In most companies, the efficiency of in-house transports with industrial trucks is recorded only manually and in a very incomplete manner. We tap the potential for optimization by developing “intelligence” for industrial trucks that enables analysis of individual intralogistics transport processes. In this interview, Christoph Hohmann, former deputy head of the Process Analytics group, uses the example of forklifts equipped with a specially developed system of mobile positioning technologies to demonstrate the recording of data and its subsequent analysis and use.

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In many cases, tightening procedures have an impact on quality during assembly – but monitoring them has been difficult up to now. Our key to quality monitoring and support in assembly is a wireless tool sensor module that detects and analyzes the screwdriver’s movement and position in real time. In this interview, Christian Nickel, Senior Engineer in the Machine Learning and Validation group, presents a retrofit solution that turns tools from any manufacturer into a cyber-physical, intelligent system.

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Every mistake in the picking process causes extra work. But installing assistance systems that alert the order picker to picking errors can be extremely complex. That is why we are developing a reliable picking monitoring system based on inductive near-field positioning. In this interview, Tobias Dräger, manager of the RFID and Inductive Sensor Systems group, explains how this system marks a fundamental departure from previous picking monitoring systems that work with optical sensors, light barriers or laser scanners.

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Wired pick-by-light systems are inflexible and costly when the picking area is redesigned. Our wireless information system makes it easy to install compartment displays, thus allowing for temporary storage setups and quick reconfiguration of pickup compartments. Stephan Oswald, a research fellow in the IoT Applications group, answers questions in this interview about how the system works, the value it adds for companies, and its customized implementation.

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Which conditions are important for the technological implementation of Industry 4.0 in SMEs?
Jasper Jahn, Advisor to the Head of the Positioning and Networks unit at Fraunhofer IIS, highlights different points where promising applications can be launched or used in existing intralogistics and industrial processes. In a video interview, he addresses the following questions:
• What do small and medium-sized enterprises (SMEs) need to consider from a technological perspective when it comes to digitalization?
• Do SMEs need to switch to completely new technical systems to keep up with the digital transformation?
• Which existing processes can be digitalized without major effort?

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Professor Andreas Harth, Head of Data Spaces and IoT Solutions in our Center for Applied Research on Supply Chain Services SCS, talks about the topic of data as well as data platforms and information exchange. He comments on the following questions:
• Why do I need better access to process data?
• How can data be made available as quickly and flexibly as possible?
• How can data be shared in a meaningful way?

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In the video interview, Professor Alexander Pflaum explains why a research project on digitalization and Industry 4.0 is particularly relevant for SMEs, and answers the following questions:

• Why is there a need for a project that focuses explicitly on digital value creation at SMEs?
• What approach did we take?
• What do SMEs need to keep in mind to make their own digital transformation a success?

• What can we do specifically to support SMEs?
• What essential advice can we give SMEs?

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Dr. Roland Fischer, managing director of the Fraunhofer Center for Applied Research on Supply Chain Services at Fraunhofer IIS, and Markus Weissenbäck, project manager for the FACE project, describe how a fast and equitable distribution of medical protective goods works based on mathematical methods. #WeKnowHow

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The "Bayerische Kompetenzzentrum Quanten Security and Data Science", or BayQS, was launched with a kickoff event on April 29, 2021. The center’s main objective is to research and develop fundamental concepts and solutions, and also to evaluate prototypes in the field of quantum computing. Prof. Alexander Martin and Markus Weissenbäck attended the event. Here, they explain how Fraunhofer IIS plans to use quantum computing to optimize methods and applications.

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Prof. Dr. Andreas Harth is head of the Data Spaces and IoT Solutions department at the Fraunhofer Center for Applied Research on Supply Chain Services at the Fraunhofer IIS. He seeks out hidden data that makes companies more resilient in a crisis and enables them to stay in control, and he researches technologies for decentralized information systems.

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Uwe Veres-Homm is Business Unit Coordinator for logistics, transport and mobility topics in the Fraunhofer Center for Applied Research on Supply Chain Services SCS. He explains how supply can work in times of crisis.

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Prof. Alexander Martin is head of the Fraunhofer IIS and also in charge of the co-located ADA Lovelace Center. He and his team are looking into ways to extract information from big data using artificial intelligence (AI).

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