Complementary learning-team machines to enlighten and exploit human expertise-Reference-Cited by-同舟云学术

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Complementary learning-team machines to enlighten and exploit human expertise

Published:2022 Issue:1 Volume:71 Page:417-420
ISSN:0007-8506
Container-title:CIRP Annals
language:en
Short-container-title:CIRP Annals

Author:

Li Xingyu^ORCID,Koren Yoram^ORCID,Epureanu Bogdan I^ORCID

Publisher

Elsevier BV

Subject

Industrial and Manufacturing Engineering,Mechanical Engineering

Reference16 articles.

1. Mass-Individualisation–the Twenty First Century Manufacturing Paradigm;Gu;International Journal of Production Research,2022

2. The Local Factory of the Future for Producing Individualized Products;Koren;Bridge (Kans City),2021

3. Smart Manufacturing;Kusiak;International Journal of Production Research,2018

4. Industry 4.0: Adoption Challenges and Benefits for SMEs;Masood;Computers in Industry,2020

5. Mapping Requirements and Roadmap Definition for Introducing I 4.0 in SME Environment;Modrak,2019

Cited by 6 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Human Digital Twin in the context of Industry 5.0;Robotics and Computer-Integrated Manufacturing;2024-02

2. Smart Reconfigurable Manufacturing: Literature Analysis;Procedia CIRP;2024

3. Preliminary Results of Lightweight Reinforcement Learning Using FEMC for Human-Robot Collaboration;2023 Fifth International Conference on Transdisciplinary AI (TransAI);2023-09-25

4. Towards Industry 5.0 Challenges for The Textile and Apparel Supply Chain for The Smart, Sustainable, and Collaborative Industry in Emerging Economies;Information Systems Frontiers;2023-09-19

5. Human-centric manufacturing for human-system coevolution in Industry 5.0;CIRP Annals;2023

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