​Exploring the Use of AI and Industry 4.0 in Malting: A Case Study of an Extract AI Prediction Project 

​MBAA TQ https://doi.org/10.1094/TQ-60-4-1215-01​  | VIEW A​​R​​TI​CL​E
Yin Li. Department of Data Science, Research and Innovation, Malteurop North America, Milwaukee, WI, USA ​

Abstract
 
The advent of big data, artificial intelligence (AI), and machine deep learning (MDL) has the potential to revolutionize malting processes, including barley procurement, process optimization, quality assurance and control, new product development, predictive maintenance, and customer experience. This article explores the transformative potential of AI and Industry 4.0 technologies in the malting industry, with a specific focus on a case study of an AI project for malt extract prediction. The application of AI in these areas is discussed, highlighting how AI can improve efficiency, reduce costs, and increase profitability. The Malteurop case study demonstrates the practical application of AI and MDL in predicting malt extract levels, providing valuable insights for stakeholders in the barley and beer production supply chains. The results show that the use of AI and MDL can significantly enhance the predictability of malt quality and process optimization, thereby offering substantial business value to the malting industry. 

Keywords: artificial intelligence, Industry 4.0, machine deep learning, malt extract, malting, predictive maintenance, process optimization, quality assurance​