The Human in the Smart Factory Human-in-The-Loop: A Human-centered Approach to Knowledge Augmentation with Machine Learning

被引:0
|
作者
Lück M. [1 ]
Hornung T. [1 ]
Teklezgi J. [1 ]
机构
[1] Fraunhofer-Institut für Arbeitswirtschaft und Organisation IAO, Universität Stuttgart, Institut für Arbeitswissenschaften und Technologiemanagement IAT, Nobelstr. 12, Stuttgart
来源
关键词
Explainability; Industrial Manufacturing; Machine Learning; Process Knowledge; Quality Assurance;
D O I
10.1515/zwf-2024-1064
中图分类号
学科分类号
摘要
The seamless merging of the physical and digital worlds, has led to an unprecedented increase in the speed at which automation can be introduced into production. can be introduced. Smart manufacturing systems will, at a fundamental level, enable the use of artificial intelligence (AI) through machine learning (ML). This involves the alignment of information flows through suitable interfaces to humans is essential. is indispensable. This human-centered approach is referred to as Industry 5.0 (I5.0) or the human-centered approach (HCA) [1, 2]. The prioritization of people can be achieved prioritization can be achieved by placing the process-related interests of people at the at the center of production monitoring and relying on technologies that help employees by developing knowledge and skills, initiate optimizations. © 2024 Walter de Gruyter GmbH, Berlin/Boston, Germany.
引用
收藏
页码:456 / 459
页数:3
相关论文
共 50 条
  • [1] A Survey of Human-Centered Evaluations in Human-Centered Machine Learning
    Sperrle, F.
    El-Assady, M.
    Guo, G.
    Borgo, R.
    Chau, D. Horng
    Endert, A.
    Keim, D.
    COMPUTER GRAPHICS FORUM, 2021, 40 (03) : 543 - 567
  • [2] A survey of human-in-the-loop for machine learning
    Wu, Xingjiao
    Xiao, Luwei
    Sun, Yixuan
    Zhang, Junhang
    Ma, Tianlong
    He, Liang
    FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE, 2022, 135 : 364 - 381
  • [3] Human-in-the-loop Applied Machine Learning
    Brodley, Carla E.
    2017 IEEE INTERNATIONAL CONFERENCE ON BIG DATA (BIG DATA), 2017, : 1 - 1
  • [4] Human-centered knowledge acquisition: A structural learning theory approach
    Hale, DP
    Sharpe, S
    Haworth, DA
    INTERNATIONAL JOURNAL OF HUMAN-COMPUTER STUDIES, 1996, 45 (04) : 381 - 396
  • [5] Design concept towards a human-centered learning factory
    Mattsson, Sandra
    Salunke, Omkar
    Fast-Berglund, Asa
    Li, Dan
    Skoogh, Anders
    PROCEEDINGS OF THE 8TH SWEDISH PRODUCTION SYMPOSIUM (SPS 2018), 2018, 25 : 526 - 534
  • [6] Human-centered artificial intelligence and machine learning
    Riedl, Mark O.
    HUMAN BEHAVIOR AND EMERGING TECHNOLOGIES, 2019, 1 (01) : 33 - 36
  • [7] Toward Practices for Human-Centered Machine Learning
    Chancellor, Stevie
    COMMUNICATIONS OF THE ACM, 2022, 66 (03) : 78 - 85
  • [8] Emerging Perspectives in Human-Centered Machine Learning
    Ramos, Gonzalo
    Suh, Jina
    Ghorashi, Soroush
    Meek, Christoper
    Banks, Richard
    Amershi, Saleema
    Fiebrink, Rebecca
    Smith-Renner, Alison
    Bansal, Gagan
    CHI EA '19 EXTENDED ABSTRACTS: EXTENDED ABSTRACTS OF THE 2019 CHI CONFERENCE ON HUMAN FACTORS IN COMPUTING SYSTEMS, 2019,
  • [9] 4 Perspectives in Human-Centered Machine Learning
    Guestrin, Carlos
    KDD'19: PROCEEDINGS OF THE 25TH ACM SIGKDD INTERNATIONAL CONFERENCCE ON KNOWLEDGE DISCOVERY AND DATA MINING, 2019, : 3162 - 3162
  • [10] Visual Analytics for Human-Centered Machine Learning
    Andrienko, Natalia
    Andrienko, Gennady
    Adilova, Linara
    Wrobel, Stefan
    IEEE COMPUTER GRAPHICS AND APPLICATIONS, 2022, 42 (01) : 123 - 133