Florian Steiner

Mr. Florian Steiner


Research Focus & Metrics

Academic Career Length

2Years (2025-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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18 November 2025 in Applied Sciences
Verified
Journal Article
Open access
PDF file
HZHelmut Zörrer
Helmut Zörrer
AHAlexander Hämmerle
Alexander Hämmerle
MKMartin J. Kollingbaum
Martin J. Kollingbaum
GEGerhard Ebenhofer
Gerhard Ebenhofer
FSFlorian Steiner
Florian Steiner
APAndreas Pichler
Andreas Pichler
In this paper, we present enabling concepts for Zero Defect Manufacturing (ZDM) based on flexible human–robot interaction. We introduce the Human–Robot Multistation System (HRMS) as a novel framework for flexible, human-initiated task allocation across multiple workstations. A HRMS is defined as one or more workstations that support human–robot collaborative task execution and integrate intelligent perception and interaction systems with coordination logic, enabling alternating or collaborative task execution. These components allow human workers to interact with the system through a gesture-based modality and to receive task assignments. An agent-based task scheduler responds to human-initiated ‘Ready’ signals to pace activities ergonomically. We built a laboratory demonstrator for an Industry 5.0 ZDM final inspection/rework use case and conducted a first pilot study (n = 5, internal participants) to evaluate system usability (SUS), perception (Godspeed), mental workload (NASA-TLX), completion times, and error rates. Results indicated technical feasibility under laboratory conditions and acceptable usability, with SUS 70.5 ± 22 (‘OK’ toward ‘Good’), overall GQS 3.2 ± 0.8, RAW NASA-TLX 37 ± 16.3, mean job throughput time 232.5 ± 46.5 s, and errors in 9/10 jobs (E1–E4). In simulation, a proximity-aware shortest-path heuristic reduced walking distance by up to 70% versus FIFO without productivity loss. We conclude that HRMS is feasible with acceptable user experience under lab constraints, while recurrent task-level failures require mitigation and larger-scale validation.