Articles Tagged with ''AI/ML''

Plants often have aging equipment that works fine, and it may have sensors, but in many cases that data never connects with data from other siloed processes. Why not connect all the data together with intelligent networks and use AI to get a better understanding of the whole process?

New research from FlexXray explores how food manufacturers detect and prevent contamination from foreign materials, as well as their future investments in inspection technologies.

While the mixing and blending of liquid ingredients into a liquid product is an exact, controlled process, combining dry ingredients has unique challenges that have been difficult to control with automation. Finally, sensors and automation are here to help.

The cultivated meat sector faces many challenges, especially in scaling production. AI — and in particular hybrid model digital twins — can help overcome critical hurdles to industry viability.

You don’t have to go it alone when searching for and maintaining the perfect batch. Through machine learning and AI-based batch control, the arduous search becomes easier to realize.

These apps are engineered around high-speed lines, thermal variability, CIP/SIP complexity, micro-stoppages, drift conditions and robotics.

Many food manufacturers may not know where to begin implementing AI, and new research from IFS shows they’re not alone. However, to realize gains and stay competitive, getting started is key. 

Combining advanced sensing technology, auto-learning capabilities and an intuitive touchscreen interface, the X8 aims to deliver accurate and reliable detection of ferrous, nonferrous and stainless-steel contaminants.

For its 10th annual State of Smart Manufacturing Report, Rockwell Automation surveyed 1,560 manufacturing leaders about the internal and external challenges they face and how they’re using technology to address them.

The TOMRA 4C is the first TOMRA machine to allow packers and processors to run multiple forms of artificial intelligence — including LUCAi Deep Learning and traditional machine learning — in tandem.