Deep Learning-Based Action Detection for Continuous Quality Control in Interactive Assistance Systems

Besginow, Andreas; Büttner, Sebastian; Ukita, Norimichi; Röcker, Carsten

doi:10.1007/978-3-030-99235-4_5

Human-Technology Interaction 2022

DOI: 10.1007/978-3-030-99235-4_5

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Deep Learning-Based Action Detection for Continuous Quality Control in Interactive Assistance Systems

Andreas Besginow

Sebastian Büttner

Norimichi Ukita

et al.

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Cited by 2 publications

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A Knowledge - Augmented Socio-Technical Assistance System for Product Engineering

Mittel,

Hubert,

Srinivasan

et al. 2024

2024 IEEE 29th International Conference on Emerging Technologies and Factory Automation (ETFA)

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Manufacturing companies are exposed to increasingly complex products and shorter product engineering cycles. Unstructured data hinders the integration of knowledge over the different product engineering stages and complicates structured product development. However, combining an integrated view on relevant data sources following the Advanced Product Quality Planning (APQP) approach provides guidance for product engineers. In this paper, a semantic Knowledge Base (KB), a Process Execution System (PES), and a Computer Vision System (CVS) are introduced, which, in their interaction, compose a Socio-Technical Assistance System (STAS). We combine semantic models of production knowledge, APQP-guided product development, and ontology-based geometric representations of products and manufacturing resources. The PES coordinates the interaction with the user and other system components. The CVS tracks used tools and parts during the assembly and, therefore, enables traceability features and creates confidence in the quality of the assembly. As a result, the developed STAS prototype offers support from customer inquiry through product design and development to manufacturing and assembly, as well as aftersales support. The assistance system enables handling of complex products efficiently in order to reduce required times and costs.

show abstract

A Knowledge - Augmented Socio-Technical Assistance System for Product Engineering

Mittel,

Hubert,

Srinivasan

et al. 2024

2024 IEEE 29th International Conference on Emerging Technologies and Factory Automation (ETFA)

View full text Add to dashboard Cite

show abstract

A Microcontroller-based Lie Detection System Leveraging Physiological Signals

Erlina,

Ferdian,

Rizal

et al. 2023

2023 IEEE International Conference on Internet of Things and Intelligence Systems (IoTaIS)

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Deep Learning-Based Action Detection for Continuous Quality Control in Interactive Assistance Systems

Cited by 2 publications

References 35 publications

A Knowledge - Augmented Socio-Technical Assistance System for Product Engineering

A Knowledge - Augmented Socio-Technical Assistance System for Product Engineering

A Microcontroller-based Lie Detection System Leveraging Physiological Signals

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