Operational Analytics and Process Optimization

With the emergence of modern digital instrumentation, control platforms and IOT enabled devices, ever growing volumes of industrial data have become readily available.

As quantities are so vast and growing exponentially, organizations are looking to leverage cloud computing platforms to glean insights, from data sets too large for traditional client-server architectures, heavily relying on IT professionals in the management and analytics of this data.

The process industries have begun to recognized the importance of subject matter knowledge and expertise in resolution to many of the challenges these industry face. Both IT and OT professionals have important roles to play in the digital transformation of our customers organizations.

In recent years, reinforcement learning (RL) has attracted significant attention from both industry and academia due to its success in solving some complex problems. This paper provides an overview of RL along with tutorials for practitioners who are interested in implementing RL solutions into process control applications.