Validating drug production processes need not be a headache, according to AI researchers who say machine learning (ML) could be a single answer to biopharma’s multivariate problem. The FDA defines ...

Recent advancements in machine learning have substantially transformed the optimisation of the steelmaking process. Traditional methods, often limited by complex thermodynamic interactions and ...

Recent advances in froth flotation optimisation have increasingly leaned on machine learning methodologies to improve process control and enhance mineral recovery. By integrating data‐driven ...

This system utilizes machine learning algorithms to optimize the operation of particle accelerators, reducing manual intervention and enhancing precision in real-time control. By integrating virtual ...

Machine learning reduces friction at every stage of a business, whether you’re coming up with new product ideas or getting the goods delivered to the client. It increases business efficiency, improves ...

In the age of digital transformation, machine learning (ML) is rapidly becoming a pivotal technology in various sectors. One of its most exciting applications is in the field of advanced materials ...

At the end of February, PICMG (PCI Industrial Computer Manufacturers Group)—the consortium for open hardware specifications—introduced InterEdge, a modular architecture for process control systems ...

Machine learning is a subfield of artificial intelligence, which explores how to computationally simulate (or surpass) humanlike intelligence. While some AI techniques (such as expert systems) use ...

A new machine-learning technique can efficiently learn to control a robot, leading to better performance with fewer data. Researchers from MIT and Stanford University have devised a new ...

AI can be added to legacy motion control systems in three phases with minimal disruption: data collection via edge gateways, non-interfering anomaly detection and supervisory control integration.