MBAA TQ https://doi.org/10.1094/TQ-60-4-1214-01 | 
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Ed Montgomery and Eric Cohen. Siemens Digital Industries USA, Plano, TX, USA
Abstract
This article explores the transformative impact of artificial intelligence (AI) in brewing process control, with a particular focus on anomaly detection. It delves into the complexities of brewing, highlighting how AI models, developed through comprehensive data collection and sophisticated methodologies, are crucial in maintaining consistent quality and optimizing resource utilization. Several application examples demonstrating AI’s efficacy are presented, including monitoring mash tun parameters, analyzing lauter tun processes, and detecting anomalies in clean-in-place (CIP) systems. Ultimately, this integration of AI not only aligns with evolving market demands but also facilitates the high standards of quality in the brewing industry, illustrating a blend of modern technology with traditional brewing art and science.
