I have a couple of suggestions for the organization, and I've told them as well. Nowadays, time-series analysis for manufacturing units is a primary need. What they're looking for is the incorporation of artificial intelligence and machine learning into these tools and then getting some insights out of it, which is closed-loop. Till now, we have been facing open-loop solutions. But how to apply these insights or inferences into my manufacturing unit, which is running 24/7? Being an engineer and a person who comes from the industry, I would rather believe in first principles than a data science model. To break the ice, they need to come up with more of the predictive part of it using machine learning techniques, which can be closed-loop solutions, which can help operators and automation engineers to apply these insights into the units rather than keeping it open-loop.
