cognitive assistance systems

Cognitive Assistance Systems in Intralogistics

Cognitive Assistance Systems in Intralogistics

User studies with augmented reality and an AI chatbot
Hendrik Stern ORCID Icon, Michael Freitag ORCID Icon
Assistance systems improve work processes, shorten learning times and increase flexibility in the workplace. Human-centered, resilient and sustainable production approaches where user acceptance is of the utmost importance play a crucial role in the digitized Industry 5.0. Two user studies investigate how useful the support of technologies like augmented reality and AI chat actually is. In the context of cognitive assistance systems in intralogistics, artificial intelligence and augmented reality have a great potential and can contribute to an improvement in process performance. The usability of these systems in terms of human-centricity of Industry 5.0 is crucial. This article describes the results and findings of two user studies conducted in the laboratory for intralogistics work processes (picking and packing). The assistance systems used were evaluated using the System Usability Scale.   Cognitive assistance systems in intralogistics Assistance systems make a ...
Industry 4.0 Science | Volume 40 | 2024 | Edition 5 | Pages 67-72 | DOI 10.30844/I4SE.24.5.66
AI-Based Assistance Systems in Corporate Learning Processes

AI-Based Assistance Systems in Corporate Learning Processes

Gergana Vladova, Norbert Gronau ORCID Icon
Assistance systems are being used increasingly in the context of digital transformation. They can support employees in industrial production processes both in the learning phase and in the active work phase. In this way, competencies can be built up in a way that is close to the workplace and the process as well as demand-oriented. This paper discusses the current state of research on the possible applications of these assistance systems and illustrates them with examples. Among other things, the current challenges are also highlighted. At the end of the paper, focal points for the future development of AI in industrial learning processes and research on this are identified.
Industrie 4.0 Management | Volume 38 | 2022 | Edition 2 | Pages 11-14