AI-driven process monitoring enhances the qualification of additively manufactured stainless-steel parts. By analysing high-frequency welding current and voltage signals in both the time and frequency ...

It’s not, “You say ‘tomato’ and I say ‘tomahto.’ ” With advanced process controls (APCs), you either know what they are or you don’t. If you do know, you know they give for-real, money-in-your-pocket ...

Thermal power plants, nuclear and fossil-fueled, rely on cooling water intake structures (CWIS) to withdraw water for rejecting waste heat. The CWIS serves as a critical interface between engineered ...

Translating regenerative medicine from lab research to large-scale clinical and commercial production requires robust, scalable, and tightly controlled ...

A recent study shows the radio frequency (RF) filter market growing steadily by nearly $16 billion from 2019 to 2024 at a compound annual growth rate (CAGR) of approximately 20%, according to ...

These models can be used either offline to provide the optimal process cycle, or online to provide optimal, real-time process control [3]. This is the target of the iREMO project (www.iremo.eu), an EC ...

Chipmakers are relying on machine learning for electroplating and wafer cleaning at leading-edge process nodes, augmenting traditional fault detection/classification and statistical process control in ...

In wastewater treatment, monitoring organic loads, particularly Total Organic Carbon (TOC), has become critical to maintaining efficient and effective operations. This is especially true in industries ...

Editor’s note: This article is the third in a series to help practitioners learn about the AICPA’s new quality management standards and prepare to implement them. The new final standards on quality ...

This article outlines improvements and changes to non‐viable particle monitoring (NVP), sometimes referred to as total particulate monitoring, which during aseptic processing, is a regulatory ...