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Explore the energy trade-offs of implementing artificial intelligence in manufacturing through this 14-minute conference talk that examines whether AI's efficiency gains justify its energy consumption. Learn how advanced AI systems using deep learning and predictive analytics can optimize manufacturing processes, detect anomalies, and enable real-time decision-making while potentially reducing overall energy usage compared to traditional control systems. Discover findings from a comprehensive literature review and detailed case study in the cement industry that analyzes the net energy impact of AI deployment by comparing energy savings against AI infrastructure electricity consumption across various server configurations. Understand the methodology behind modeling different AI system setups and conducting sensitivity analysis to evaluate the environmental and economic benefits of AI adoption in manufacturing contexts. Gain insights into how AI's broader sustainability benefits may outweigh concerns about its energy footprint, providing valuable perspectives for future manufacturing AI adoption strategies and policy development decisions.
