COUNTRY FOCUS : NETHERLANDS
Images on this page courtesy of Amalthea days . As innovation is in Amalthea ’ s nature , that was the next logical step .
By applying Infor Coleman Artificial Intelligence to past manufacturing orders / batches and other production attributes , the Machine Learning model detects batches that deviate from the target yield , along with an explanation of the main contributors to the yield value . This process runs daily , and insights are delivered through flexible interfaces depending on the end-user – CloudSuite Food & Beverage Homepages for Operators and Infor Birst dashboards for management . Amalthea ’ s AI-driven yield deviation detection and explanation is now fully automated – from data collection to processing and presentation . Implemented in less than 90 days , the solution helps in decision-making to stabilise the process for future manufacturing orders by :
• Adjusting the target yield
• Understanding yield drivers and potentially fixing the input variations
It is easy to use and understand , so we can improve our process and yields , which makes my life easier .
• Updating the process parameters of the cheese-making
“ What we also saw and learned is that for some cheese batches , we did not have the correct target value ,” Aarts said . “ Infor Coleman AI showed us the average milk yield of all the cheese batches since go-live , and we used this information to change the target value to the correct value , so that the right parameters are in place for the best outcome possible .”
With Infor Coleman AI , Amalthea can now steer the cheese production process faster , and with more accuracy :
• Seven times faster ( from weekly to daily ) identification of yield deviations
• Identification of main contributors to the yield , for subsequent action to optimise yields
• More accurate target yields
• Stabilises the variability in the process for more predictable yield and quality
• € 500,000 annual savings for every 1 % increase in yield
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