Quality is one of the key variables in food and beverage production; however, it's often the most complex use case to solve because it involves several production steps and sub-processes.
An Intelecy customer wanted to identify unexpected behavior during the crucial phase of liquid cooling that may lead to quality issues with the product. Traditional alarm limits will not detect this behavior as all values are within normal operating ranges.
The customer created no-code AI models with Intelecy that monitor each subprocess in real-time and notify operators whenever any of these operate out of the "normal" modes. Operators can now make process adjustments or stop production to prevent energy waste and spending time on products that will not meet their quality standards.