Research library / 2024 / Award-winning essay
Leveraging generative AI for smart maintenance: navigating technological tipping points in manufacturing
World Manufacturing Report 2024 · 2024
Article overview
This award-winning essay examines opportunities and barriers for generative AI in industrial maintenance. It discusses synthetic data, workforce learning, implementation costs, data quality and governance.
Essay on pages 98–99 of the World Manufacturing Report 2024. This page provides an editorial summary; the original essay has no separate abstract.
In brief
This award-winning essay examines opportunities and barriers for generative AI in industrial maintenance. It discusses synthetic data, workforce learning, implementation costs, data quality and governance.
Key points
- Discusses synthetic data as a response to scarce anomaly examples.
- Explores personalized learning and upskilling for maintenance workers.
- Examines financial, data-quality, privacy and compliance barriers to industrial adoption.
Cite this work
Siyuan Chen (2024). Leveraging generative AI for smart maintenance: navigating technological tipping points in manufacturing. World Manufacturing Report 2024, pp. 98–99.
@incollection{Chen2024GenerativeAiSmart,
title = {{Leveraging generative AI for smart maintenance: navigating technological tipping points in manufacturing}},
author = {Chen, Siyuan},
year = {2024},
booktitle = {World Manufacturing Report 2024: New Perspectives for the Future of Manufacturing, Outlook 2030},
publisher = {World Manufacturing Foundation},
pages = {98--99},
url = {https://worldmanufacturing.org/report/report-2024-new-perspectives-for-the-future-of-manufacturing-outlook-2030/}
}
Essay on pages 98–99 of the World Manufacturing Report 2024. This page provides an editorial summary; the original essay has no separate abstract.