The Deployment and Implementation of Cloud Platform for Remote Automatic Correction of Artificial Intelligence Models
Je Chiao Ku, Shang-Liang Chen · IEEE Transactions on Industrial Informatics · 2025
Despite the advanced research in artificial intelligence (AI) technology within the academic community, enterprises have yet to fully integrate this technology into practical applications. In the manufacturing sector, deploying professional IT personnel to implement AI for just a few machines is not ideal, posing a significant challenge for traditional factories. Additionally, the rising consumer demand for highly personalized and high-value-added products necessitates increased flexibility in production design and implementation. This study aims to establish an AI model cloud service platform that possesses the following features: 1) remote dynamic model adjustment, 2) automated continuous integration, 3) automated continuous deployment, 4) administrator web status display interface, 5) data security protection mechanism, 6) global remote deployment, and 7) multiscenario operations including deployment mechanisms, model adjustment mechanisms, server setup mechanisms, and more. The platform aims to address the issue of production lines struggling to integrate AI into practical applications. The innovation of this research lies in the proposed system architecture and platform for introducing AI into the manufacturing industry. Enterprises can use this study to establish their AI integration systems and deploy relevant technologies, or they can directly apply the research outcomes to their industrial control environments. This approach reduces the difficulties enterprises face when introducing AI technology, accelerates the transition from production automation to intelligent manufacturing, enhances production efficiency and sustainability, and improves the operational performance and management of the manufacturing industry, thereby strengthening global competitiveness.