Automatic remote deployment and remodeling of AI models for smart manufacturing

The application of artificial intelligence (AI) in the manufacturing sector is growing rapidly and diversely, with industries such as machinery manufacturing, semiconductor production, and automation integration actively incorporating AI technologies into their processes. Enterprises urgently require flexible remote deployment solutions that seamlessly integrate adaptive AI models into production lines, thereby increasing efficiency in model deployment and replacement while reducing overall costs. To address these needs, this study proposes a platform for remote, automated deployment, and remodeling of AI models, which not only enhances the adaptability of production line models but also minimizes downtime by resolving the time-consuming nature of traditional deployment practices. Leveraging containerization (packaging applications with their dependencies into portable units) and automated deployment mechanisms, the proposed platform enables remote updates and remodelings, effectively overcoming challenges associated with introducing AI in machine manufacturing, semiconductor manufacturing, and automation integration—especially in scenarios requiring online model adjustments. Compared to previous research, this study prioritizes industry-driven requirements, providing a remote automated AI model deployment solution that better aligns with enterprises’ operational goals. The findings underscore the potential for significantly reducing production costs and improving operational efficiency, paving the way for smarter, more responsive manufacturing processes.

Authors

Institutions

Publication Details

Journal
Proceedings of the Institution of Mechanical Engineers Part B Journal of Engineering Manufacture
Published
2026-03-04
DOI
https://doi.org/10.1177/09544054261420247
Primary Topic
Digital Transformation in Industry
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Automatic remote deployment and remodeling of AI models for smart manufacturing

Shang-Liang Chen, Tang-Yun Tung
Proceedings of the Institution of Mechanical Engineers Part B Journal of Engineering Manufacture
Digital Transformation in Industry
article

Automatic remote deployment and remodeling of AI models for smart manufacturing

Shang-Liang Chen, Tang-Yun Tung
article en

Abstract

The application of artificial intelligence (AI) in the manufacturing sector is growing rapidly and diversely, with industries such as machinery manufacturing, semiconductor production, and automation integration actively incorporating AI technologies into their processes. Enterprises urgently require flexible remote deployment solutions that seamlessly integrate adaptive AI models into production lines, thereby increasing efficiency in model deployment and replacement while reducing overall costs. To address these needs, this study proposes a platform for remote, automated deployment, and remodeling of AI models, which not only enhances the adaptability of production line models but also minimizes downtime by resolving the time-consuming nature of traditional deployment practices. Leveraging containerization (packaging applications with their dependencies into portable units) and automated deployment mechanisms, the proposed platform enables remote updates and remodelings, effectively overcoming challenges associated with introducing AI in machine manufacturing, semiconductor manufacturing, and automation integration—especially in scenarios requiring online model adjustments. Compared to previous research, this study prioritizes industry-driven requirements, providing a remote automated AI model deployment solution that better aligns with enterprises’ operational goals. The findings underscore the potential for significantly reducing production costs and improving operational efficiency, paving the way for smarter, more responsive manufacturing processes.

Proceedings of the Institution of Mechanical Engineers Part B Journal of Engineering Manufacture
National Cheng Kung University (TW)
Industry, innovation and infrastructure
Openalex Percentile: Top 30%
Digital Transformation in Industry
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.