With the rapid growth of AI and Big Data, reducing energy consumption in data centers has become a significant challenge. Small-scale server rooms, which often depend on standalone cooling units instead of specialized infrastructure, are especially vulnerable to airflow inefficiencies and localized hotspots. While traditional HVAC theory can estimate total cooling loads, it does not effectively predict the local thermal distributions that depend on equipment placement. This study employs Computational Fluid Dynamics (CFD) to address these limitations. It focuses on a server room containing five HPCs and three cooling units, comparing theoretical HVAC calculations with 3D thermal fluid analysis conducted using Ansys Fluent. The research evaluates the thermal performance of the existing layout (Model 1) and suggests an improved configuration (Model 2). The findings reveal that strategic equipment placement can eliminate hotspots and stabilize operations while reducing the necessary cooling capacity. This research provides a practical framework for enhancing energy efficiency in small-scale server environments.
As the global manufacturing industry moves toward carbon neutrality, improving energy efficiency of machine tools has become essential. Although machine tools contribute significantly to industrial energy consumption, systematic methods for evaluating their energy consumption remain insufficient. To address this issue, this study developed an energy consumption evaluation system based on ISO 14955, the international standard for machine tool energy efficiency. The proposed system enabled a detailed analysis of energy usage patterns in different operating states, identifying key areas for energy reduction. The developed system could measure energy consumption of individual machine tool components in various operating states using power meters and automatically generates reports. This allows users to identify which components and operating states consume the most energy. We tested and validated this system on three different machine tools and analyzed strategies for reducing energy consumption. The developed evaluation system can help machine tool manufacturers integrate it into their equipment, develop energy-efficient technologies, and contribute to sustainable manufacturing.
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Recent Advances in CNC Technology: Toward Autonomous and Sustainable Manufacturing Jong-Min Lim, Wontaek Song, Joon-Soo Lee, Ji-Myeong Park, Hee-Min Shin, In-Wook Oh, Soon-Hong Hwang, Seungmin Jeong, Sangwon Kang, Chan-Young Lee, Byung-Kwon Min International Journal of Precision Engineering and Manufacturing.2025; 26(9): 2311. CrossRef
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