From automation to intelligent autonomy: AI and Edge Control in sustainable heat treatment

Sherwin Peter - Eurotherm by Watlow (United States)

The heat treatment industry has long utilized automation technologies—such as PID control, setpoint programming, and supervisory systems like SCADA—to enhance efficiency and consistency. Today, we stand at the threshold of a new transformation: moving from conventional automation to intelligent autonomous systems powered by Artificial Intelligence (AI), Machine Learning (ML), and Machine Teaching (MT).

This paper examines how the integration of AI, ML, MT, and advanced thermal-loop components is revolutionizing heat treatment processes. Utilizing the Edge Process Management (EPM), we showcase how real-time data analytics and edge solutions are optimizing thermal processes and significantly reducing energy consumption. The EPM platform facilitates immediate, localized decision-making, improving response times and data security compared to cloud-based systems.

Machine Learning algorithms enable predictive maintenance and adaptive control, enhancing process stability and efficiency. Simultaneously, Machine Teaching (MT) allows industry experts to embed their knowledge directly into AI models, accelerating the development of intelligent systems. By uniting these technologies, we achieve unprecedented levels of process optimization.

Through case studies and experimental results, we highlight substantial improvements in energy efficiency, process consistency, and overall operational sustainability. This advancement marks a critical step in the industry’s evolution—from standard automation to intelligent, self-optimizing systems.