Thomas Bergs

TL;DR: This article reviews the current state of the art of model-based predictive control including theory, historic evolution, and practical considerations to create intuitive understanding and lays special attention on applications in order to demonstrate what is already possible today.

TL;DR: This work creates a blueprint for an infrastructure acting as an enabler for an IoP, and identifies three orthogonal research objectives: real-time control of tightly integrated production processes to offer seamless low-latency analysis and execution, storing and processing heterogeneous production data to support scalable data stream processing and storage, and secure privacy-aware collaboration in production to provide a basis for secure industrial collaboration.

TL;DR: In this publication, a deep learning approach for image processing is investigated in order to quantify the tool wear state using machine tool integrated microscopes in the scientific and industrial environment.

TL;DR: A new definition of the concept Digital Twin (DT) and Digital Shadow (DS) is given within the field of manufacturing technology and shows specific applications.

TL;DR: This paper identifies and illustrates envisioned inter-organizational dataflows and the participating entities alongside two real-world use cases from the production domain: a fine blanking line and a connected job shop and proposes next steps for future research.