Enhancing transparency and trust in AI-powered manufacturing: A survey of explainable AI (XAI) applications in smart manufacturing in the era of industry 4.0/5.0

被引：1
|
作者：
Nikiforidis, Konstantinos [1 ]
Kyrtsoglou, Alkiviadis [1 ]
Kotsiopoulos, Thanasis [1 ,2 ]
Vafeiadis, Thanasis [1 ]
Nizamis, Alexandros [1 ]
Ioannidis, Dimosthenis [1 ]
Votis, Konstantinos [1 ]
Tzovaras, Dimitrios [1 ]
Sarigiannidis, Panagiotis [2 ]
机构：
[1] Informat Technol Inst, Ctr Res & Technol Hellas, Thessaloniki 57001, Greece
[2] Univ Western Macedonia, Dept Elect & Comp Engn, Karamanli & Ligeris St, Kozani 50100, Greece
来源：
ICT EXPRESS | 2025年 / 11卷 / 01期
关键词：
Explainable AI; Industry; 4.0; 5.0; Manufacturing application; CONVOLUTIONAL NEURAL-NETWORK; ARTIFICIAL-INTELLIGENCE; CHALLENGES;
D O I：
10.1016/j.icte.2024.12.001
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Explainable Artificial Intelligence (XAI) is crucial for the transition from the fourth to fifth industrial revolution, providing transparency and fostering user confidence in Artificial Intelligence (AI) powered systems. Since 2020, XAI applications demonstrate potential to transform manufacturing. This paper provides an extensive overview of XAI-based applications in Industries 4.0 and 5.0 by highlighting the trends regarding methods used, connecting XAI methods with important parameters and presenting XAI visualization approaches. The survey provides valuable insights for researchers, practitioners and industry leaders as it underscores the potential of XAI in shaping the future of manufacturing by enhancing transparency and user acceptance of AI-powered applications.
引用
收藏
页码：135 / 148
页数：14
相关论文
共 8 条
  • [1] Enhancing Manufacturing with AI-powered Process Design
    Genalti, Gianmarco
    Corbo, Gabriele
    Bianchi, Tommaso
    Missaglia, Marco
    Negri, Luca
    Sala, Andrea
    Magri, Luca
    Boracchi, Giacomo
    Miragliotta, Giovanni
    Gatti, Nicola
    PROCEEDINGS OF THE THIRTY-THIRD INTERNATIONAL JOINT CONFERENCE ON ARTIFICIAL INTELLIGENCE, IJCAI 2024, 2024, : 8665 - 8668
  • [2] Integrating AI with Lean Manufacturing in the Context of Industry 4.0/5.0: Current Trends and Applications
    Boursali, Aze-Eddine
    Benderbal, Hichem Haddou
    Souier, Mehdi
    ADVANCES IN PRODUCTION MANAGEMENT SYSTEMS-PRODUCTION MANAGEMENT SYSTEMS FOR VOLATILE, UNCERTAIN, COMPLEX, AND AMBIGUOUS ENVIRONMENTS, APMS 2024, PT IV, 2024, 731 : 206 - 217
  • [3] AI-powered deep learning for sustainable industry 4.0 and internet of things: Enhancing energy management in smart buildings
    Alijoyo, Franciskus Antonius
    ALEXANDRIA ENGINEERING JOURNAL, 2024, 104 : 409 - 422
  • [4] A Survey on AI-Driven Digital Twins in Industry 4.0: Smart Manufacturing and Advanced Robotics
    Huang, Ziqi
    Shen, Yang
    Li, Jiayi
    Fey, Marcel
    Brecher, Christian
    SENSORS, 2021, 21 (19)
  • [5] A Digital Twin-Based Distributed Manufacturing Execution System for Industry 4.0 with AI-Powered On-The-Fly Replanning Capabilities
    Vyskocil, Jiri
    Douda, Petr
    Novak, Petr
    Wally, Bernhard
    SUSTAINABILITY, 2023, 15 (07)
  • [6] When Embodied AI Meets Industry 5.0: Human-Centered Smart Manufacturing
    Xu, Jing
    Sun, Qiyu
    Han, Qing-Long
    Tang, Yang
    IEEE-CAA JOURNAL OF AUTOMATICA SINICA, 2025, 12 (03) : 485 - 501
  • [7] When Embodied AI Meets Industry 5.0:Human-Centered Smart Manufacturing
    Jing Xu
    Qiyu Sun
    QingLong Han
    Yang Tang
    IEEE/CAA Journal of Automatica Sinica, 2025, 12 (03) : 485 - 501
  • [8] From Raw Data to Smart Manufacturing: AI and Semantic Web of Things for Industry 4.0
    Patel, Pankesh
    Ali, Muhammad Intizar
    Sheth, Amit
    IEEE INTELLIGENT SYSTEMS, 2018, 33 (04) : 79 - 86
1