Autor: Martin Manns

Applied AI for Human-Centric Assembly Workplace Design

Applied AI for Human-Centric Assembly Workplace Design

An ethics-informed approach
Tadele Belay Tuli ORCID Icon, Michael Jonek ORCID Icon, Sascha Niethammer, Henning Vogler, Martin Manns ORCID Icon
Artificial intelligence (AI) can enhance smart assembly by predicting human motion and adapting workplace design. Using probabilistic models such as Gaussian Mixture Models (GMMs), AI systems anticipate operator actions to improve coordination with robots. However, these predictive systems raise ethical concerns related to safety, fairness, and privacy under the EU AI Act, which classifies them as high-risk. This paper presents a conceptual method integrating probabilistic motion modeling with ethical evaluation via Z-Inspection®. An industrial case study using the Smart Work Assistant (SWA) demonstrates how multimodal sensing (motion, gaze) and interpretable models enable anticipatory assistance. The approach moves from ethics evaluation to ethics-informed work design, yielding transferable principles and a configurable assessment matrix that supports compliance-by-design in collaborative assembly.
Industry 4.0 Science | Volume 42 | 2026 | Edition 1 | Pages 60-68 | DOI 10.30844/I4SE.26.1.58
Boosting Competitiveness in Small Batch Production

Boosting Competitiveness in Small Batch Production

Scalable and flexible body-in-white production line with collaborative mobile robots
Walid Elleuch, Tadele Belay Tuli ORCID Icon, Martin Manns ORCID Icon
Due to the higher customization of products to customer groups and needs, body-in-white manufacturing industries are facing higher variant assembly at the later stages of the production line, thus increasing production costs per unit. Flexible production processes that involve flexible material flows, non-rigid manufacturing sequences, and the automatic reconfiguration of tools are regarded as the pillars of a resilient production system. This article presents a conceptual solution for flexible Body-in-White sheet metal production with autonomous collaborative robotic systems to make product costs affordable for a higher competitive advantage.
Industry 4.0 Science | Volume 41 | Edition 2 | Pages 60-67
Automated Detection of Fragile Production Behavior

Automated Detection of Fragile Production Behavior

Simple early detection of deterministic-chaotic behavior in highly available production systems
Martin Manns ORCID Icon, Denny Höhnen
Routing flexibility enables a robust, resilient design of production. However, in highly available, decentralized controlled production systems with cyclic material flow, it can reduce efficiency due to undesired deterministic-chaotic behavior. An automated method for measuring such behavior is presented. It is tested with a double conveyor belt laboratory system. An embedded system simplifies data acquisition. Results indicate that the method is usable for manual and automatic production systems. It has the potential to recognize modeling deficiencies in Industry 4.0 control with IEC 61499. (Only in German)
Industrie 4.0 Management | Volume 39 | 2023 | Edition 5 | Pages 17-21