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Bridging the Skills Gap of Workers in Industry 4.0 by Human Performance Augmentation Tools: Challenges and Roadmap

Published: 21 June 2017 Publication History

Abstract

Industry 4.0 is a coordinated push for automation in Smart Factories and other Cyber-Physical Systems (CPS). The increasing complexity of frequently changing production environments challenges shop floor workers to perform well. The tasks they work on are getting less routine and ask for continuous knowledge and skills development. For example, the skills portfolio of workers likely requires improved higher-order thinking and decision-making skills. A wide range of research and development efforts already today sets focus on different areas of workplace learning, including performance appraisals, pedagogy and education, technology, and business economics. Bridging the skills gap, however, requires novel user-facing technologies -- such as Augmented Reality (AR) and wearables -- for human performance augmentation to improve efficiency and effectiveness of staff delivered through live guidance. AR branches out beyond mobile apps with 3D-object superimposition for marketing purposes to rather complex use cases delivered by a rapidly growing innovation ecosystem of hard- and software providers collaborating closely with R&D organisations. This paper provides a first shared vision on how AR can tackle four different challenges related to handling complexity in a CPS environment: develop intelligent assistance systems for learning and performance assessment at the workplace, adapt job profiles accordingly, and last but not least to address also the issue of work-life balance. The paper concludes with an outline of a research roadmap.

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      cover image ACM Other conferences
      PETRA '17: Proceedings of the 10th International Conference on PErvasive Technologies Related to Assistive Environments
      June 2017
      455 pages
      ISBN:9781450352277
      DOI:10.1145/3056540
      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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      • NSF: National Science Foundation
      • CSE@UTA: Department of Computer Science and Engineering, The University of Texas at Arlington

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      Published: 21 June 2017

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      Author Tags

      1. Augmented Reality
      2. Industry 4.0
      3. Job Profiles
      4. Performance Augmentation

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      • (2024)6D Pose Estimation of Unseen Objects for Industrial Augmented Reality2024 IEEE 20th International Conference on Intelligent Computer Communication and Processing (ICCP)10.1109/ICCP63557.2024.10792989(1-8)Online publication date: 17-Oct-2024
      • (2024)Empowering Operator 5.0: human-centric design of an augmented reality tool for a learning factoryIFAC-PapersOnLine10.1016/j.ifacol.2024.08.11758:8(180-185)Online publication date: 2024
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