A Cognitive Assistant for Operators: AI-Powered Knowledge Sharing on Complex Systems

被引:7
|
作者
Freire, Samuel Kernan [1 ]
Panicker, Sarath Surendranadha [2 ]
Ruiz-Arenas, Santiago [3 ]
Rusak, Zoltan [1 ]
Niforatos, Evangelos [1 ]
机构
[1] Delft Univ Technol, NL-2628 CD Delft, Netherlands
[2] Cognizant Technol Solut, NL-1096 BK Amsterdam, Netherlands
[3] Univ EAFIT, Medellin 3300, Antioquia, Colombia
基金
欧盟地平线“2020”;
关键词
Production facilities; Artificial intelligence; Training; Manufacturing; Machine components; Cameras; Best practices; TACIT KNOWLEDGE;
D O I
10.1109/MPRV.2022.3218600
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Operating a complex and dynamic system, such as an agile manufacturing line, is a knowledge-intensive task. It imposes a steep learning curve on novice operators and prompts experienced operators to continuously discover new knowledge, share it, and retain it. In practice, training novices is resource-intensive, and the knowledge discovered by experts is not shared effectively. To tackle these challenges, we developed an AI-powered pervasive system that provides cognitive augmentation to users of complex systems. We present an AI cognitive assistant that provides on-the-job training to novices while acquiring and sharing (tacit) knowledge from experts. Cognitive support is provided as dialectic recommendations for standard work instructions, decision-making, training material, and knowledge acquisition. These recommendations are adjusted to the user and context to minimize interruption and maximize relevance. In this article, we describe how we implemented the cognitive assistant, how it interacts with users, its usage scenarios, and the challenges and opportunities.
引用
收藏
页码:50 / 58
页数:9
相关论文
共 50 条
  • [31] Evaluating the Effectiveness of AI-Powered Adaptive Learning Systems in Secondary Schools
    Alenezi, Abdullah
    INTERNATIONAL JOURNAL ON STUDIES IN EDUCATION, 2024, 6 (04):
  • [32] Paradoxical Tensions Related to AI-Powered Evaluation Systems in Competitive Sports
    Elena Mazurova
    Willem Standaert
    Esko Penttinen
    Felix Ter Chian Tan
    Information Systems Frontiers, 2022, 24 : 897 - 922
  • [33] The VesselAI Methodology for AI-Powered Decision Support Systems for the Maritime Industry
    Kontzinos, Christos
    Mouzakitis, Spiros
    Agostinho, Carlos
    Figueiras, Paulo
    Askounis, Dimitris
    INTELLIGENT SYSTEMS AND APPLICATIONS, VOL 1, INTELLISYS 2023, 2024, 822 : 201 - 211
  • [34] Paradoxical Tensions Related to AI-Powered Evaluation Systems in Competitive Sports
    Mazurova, Elena
    Standaert, Willem
    Penttinen, Esko
    Tan, Felix Ter Chian
    INFORMATION SYSTEMS FRONTIERS, 2022, 24 (03) : 897 - 922
  • [35] The First ACM Workshop on AI-Powered Question Answering Systems for Multimedia
    Mai, Tai Tan
    Tran, Quang-Linh
    Tran, Ly-Duyen
    Ninh, Tu
    Dang-Nguyen, Duc-Tien
    Gurrin, Cathal
    PROCEEDINGS OF THE 4TH ANNUAL ACM INTERNATIONAL CONFERENCE ON MULTIMEDIA RETRIEVAL, ICMR 2024, 2024, : 1328 - 1329
  • [36] FPGA/AI-Powered Architecture for Anomaly Network Intrusion Detection Systems
    Pham-Quoc, Cuong
    Bao, Tran Hoang Quoc
    Thinh, Tran Ngoc
    ELECTRONICS, 2023, 12 (03)
  • [37] Harnessing Disagreement to Create AI-Powered Systems That Reflect Our Values
    Gordon, Mitchell L.
    ADJUNCT PROCEEDINGS OF THE 34TH ANNUAL ACM SYMPOSIUM ON USER INTERFACE SOFTWARE AND TECHNOLOGY, UIST 2021, 2021, : 171 - 174
  • [38] AI and the path to envelopment: knowledge as a first step towards the responsible regulation and use of AI-powered machines
    Robbins, Scott
    AI & SOCIETY, 2020, 35 (02) : 391 - 400
  • [39] AI and the path to envelopment: knowledge as a first step towards the responsible regulation and use of AI-powered machines
    Scott Robbins
    AI & SOCIETY, 2020, 35 : 391 - 400
  • [40] Effect of AI Explanations on Human Perceptions of Patient-Facing AI-Powered Healthcare Systems
    Zhan Zhang
    Yegin Genc
    Dakuo Wang
    Mehmet Eren Ahsen
    Xiangmin Fan
    Journal of Medical Systems, 2021, 45