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Learning and performing assembly processes: an overview of learning and adaptivity in digital assistance systems for manufacturing

Authors:

Hendrik Oestreich,

Sebastian Wrede,

Britta WredeAuthors Info & Claims

PETRA '20: Proceedings of the 13th ACM International Conference on PErvasive Technologies Related to Assistive Environments

Article No.: 42, Pages 1 - 8

https://doi.org/10.1145/3389189.3397977

Published: 30 June 2020 Publication History

Abstract

Due to digitalization and Industry 4.0, the use of assistance systems on the shop floor has become commonplace nowadays. Besides the economical reasons of increasing productivity and quality, the educational functionalities offer new possibilities. Workers can use the systems to learn new skills, new assembly processes and further more. To offer a good user experience along the learning path, assistance systems should be adaptive and must adjust their level of support according to the current user state and experience. In addition, the application of the systems can become more versatile and they may be used productively beyond the training phase as well. Therefore it is important to consider fundamental principles of learning and different levels of adaptivity along given dimensions. In this paper an overview about both topics is presented and summarized in two morphologic boxes. To realize adaptivity within the software architecture of assistance systems three different approaches were identified. The work was based on an extensive literature review and should be beneficial for the future development and research in this domain.

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Cited By

de Paiva Lareiro P(2024)Algorithmisches Management jenseits der Plattformökonomie. Digitale Assistenzsysteme in Industrie und LogistikDigitalisierung der Arbeitswelten10.1007/978-3-658-44458-7_12(269-286)Online publication date: 1-Sep-2024
https://doi.org/10.1007/978-3-658-44458-7_12
Pimminger SKurschl WSchonbock J(2022)Mixed Reality Workplace Training Systems for Smart Factories: Challenges and Future Directions2022 IEEE 3rd International Conference on Human-Machine Systems (ICHMS)10.1109/ICHMS56717.2022.9980642(1-6)Online publication date: 17-Nov-2022
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Horst RNaraghi-Taghi-Off RDorner R(2022)An Assistance System Framework for Virtual Reality Self-Service E-Learning Kiosks2022 IEEE Games, Entertainment, Media Conference (GEM)10.1109/GEM56474.2022.10017801(1-6)Online publication date: 27-Nov-2022
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Index Terms

Learning and performing assembly processes: an overview of learning and adaptivity in digital assistance systems for manufacturing

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PETRA '20: Proceedings of the 13th ACM International Conference on PErvasive Technologies Related to Assistive Environments

June 2020

574 pages

ISBN:9781450377737

DOI:10.1145/3389189

Conference Chair:
Fillia Makedon
University of Texas at Arlington

Copyright © 2020 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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CSE@UTA: Department of Computer Science and Engineering, The University of Texas at Arlington
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Published: 30 June 2020

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PETRA '20: The 13th PErvasive Technologies Related to Assistive Environments Conference

June 30 - July 3, 2020

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Cited By

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https://doi.org/10.1007/978-3-658-44458-7_12
Pimminger SKurschl WSchonbock J(2022)Mixed Reality Workplace Training Systems for Smart Factories: Challenges and Future Directions2022 IEEE 3rd International Conference on Human-Machine Systems (ICHMS)10.1109/ICHMS56717.2022.9980642(1-6)Online publication date: 17-Nov-2022
https://doi.org/10.1109/ICHMS56717.2022.9980642
Horst RNaraghi-Taghi-Off RDorner R(2022)An Assistance System Framework for Virtual Reality Self-Service E-Learning Kiosks2022 IEEE Games, Entertainment, Media Conference (GEM)10.1109/GEM56474.2022.10017801(1-6)Online publication date: 27-Nov-2022
https://doi.org/10.1109/GEM56474.2022.10017801
Oestreich Hda Silva Bröker YWrede SMakedon F(2021)An Adaptive Workflow Architecturefor Digital Assistance SystemsProceedings of the 14th PErvasive Technologies Related to Assistive Environments Conference10.1145/3453892.3458046(177-184)Online publication date: 29-Jun-2021
https://dl.acm.org/doi/10.1145/3453892.3458046
Maier MVernim S(2021)Requirements for an Assistance System to Support Human Resource Development in Manual Assembly2021 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM)10.1109/IEEM50564.2021.9673033(1372-1376)Online publication date: 13-Dec-2021
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Späker LMark BRauch E(2021)Development of a Morphological Box to Describe Worker Assistance Systems in ManufacturingProcedia Manufacturing10.1016/j.promfg.2021.10.02455(168-175)Online publication date: 2021
https://doi.org/10.1016/j.promfg.2021.10.024
Pimminger SKurschl WPanholzer LSchönböck J(2021)Exploring the Learnability of Assembly Tasks Using Digital Work Instructions in a Smart FactoryProcedia CIRP10.1016/j.procir.2021.11.117104(696-701)Online publication date: 2021
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