Tranforming Process Data into Process Solutions What Every Engineer Should Know About Predictive Analytics and Process Data

Tranforming Process Data into Process Solutions

Today, using the process data in a simple and practical way should be the primary knowledge of every chemical engineer. 

Being able to recognize and use all the potential hidden in the process data is of immense importance in order to be able to operate the process in a more stable, efficient, and optimized way.

Industry 4.0,  Industrial Internet of Things, Big data - these are all the fancy words that have entered chemical engineering stage, but in fact are only standing in front of the raw, real and huge amount of process data stored behind every industrial process. Those data will remain only a pure potential if not transformed into process solution. 

Engineers need to learn the process to be able to use the modeling tools which enable turning process data into solutions. That isn't easy to be tought, as most courses and lectures are focused on teaching tools, instead of teaching approches and principles that start from being able to recognize opportunities, turn them into exact plans, develop them and finaly estimate their financial and other effects. 

Process Optimization with Predictive Analytics is one of the courses that teaches just that. It, as well, has a short preview video.