How can one utilize data analytics and various in-process analytical tools to optimize extraction operations? Cannabis extraction at its current status is inefficient and uncontrolled, even if the artist tells you that they make the best s**t.
Aside from regulatory testing, there are a multitude of other analytical tools and testing points in the extraction value chain, where testing will offer a more comprehensive picture for the operator.
Even with all this data, little can be done to improve the extraction process. For this data science is need. From simple linear regressions, via multifactorial optimization, all the way to Machine Learning and AI, those tools become more important and slowly find their way onto the production floor.
We want to discuss the current problems and needs of a cannabis producer and present possible solutions that Machine Learning can bring.