AI-Powered Energy Efficiency for ASEAN's Industrial Robots

A New Era of Energy Efficiency in Industrial Automation for ASEAN Factories \\[A recent collaboration between ABB’s Machine Automation Division – B&R – and the Salzburg University of Applied Sciences has resulted in a groundbreaking patent application. This joint effort aims to leverage artificial intelligence (AI) to enhance energy efficiency in industrial drive systems, including robots, machine tools, and automated production lines. The implications for ASEAN factories, particularly in countries like Thailand, Vietnam, Indonesia, and Malaysia, are significant.\\[In these rapidly industrializing nations, energy costs are a major concern for manufacturers. Traditional control methods, while precise, often fail to account for real-world energy losses that can be measured but not fully modeled. This gap is where the new AI-driven approach comes into play. By using reinforcement learning (RL), the system can learn directly from the physical behavior of the machines, adapting its control strategy to minimize energy consumption. This innovative method requires less data and learns faster, making it more practical for industrial applications.\\[The collaboration, anchored in the Josef Ressel Center for Intelligent and Secure Industrial Automation (JRZ ISIA), has been ongoing since 2020. Initial work was part of the EU Interreg project KI-Net, and since 2022, the research has been further developed with industry partners such as COPA-DATA. The key innovation lies in a new mathematical formulation of the learning strategy, which allows for more efficient and effective deployment in cyber-physical systems.\\[For ASEAN factories, this means a potential reduction in operational costs and a more sustainable manufacturing process. In Thailand, for example, where the automotive and electronics industries are booming, the adoption of such AI-driven solutions could lead to significant energy savings. Similarly, in Vietnam, where the textile and footwear sectors are growing, the technology could help optimize energy use in highly dynamic motion sequences, such as positioning, acceleration, and deceleration. In Indonesia and Malaysia, where the food packaging and semiconductor industries are expanding, the AI system could improve the efficiency of automated production lines, reducing both energy consumption and environmental impact.\\[Stefan Huber, head of research at Salzburg University of Applied Sciences, emphasizes the importance of translating academic research into tangible technological innovations. “Our goal is to ensure that research does not stop at the laboratory but results in real-world applications that benefit the industry,” he says. Martin Haidacher, innovation manager at B&R, adds, “Close cooperation with Salzburg University of Applied Sciences allows us to bring innovative research methods into practical industrial applications at an early stage.”\\[For factory buyers in ASEAN, the takeaway is clear: investing in AI-driven energy optimization can lead to substantial cost savings and a more sustainable future. As the region continues to grow and industrialize, adopting such advanced technologies will be crucial for maintaining competitiveness and reducing environmental impact.\\[