(182d) Big Data Analytics: Solving for Optimization and Efficiency in Process Manufacturing

The chemical industry is embracing a digital future. With what we call Chemical 4.0, customer demands are evolving at an unprecedented rate and their priorities are shifting just as quickly. As desire for more versatile products increases, addressing sustainability challenges becomes an integral part of doing business. This shift represents a tremendous challenge for chemical companies—but it is also a great opportunity. With millions spent per day on unplanned outage of assets, and over 175 million metric tons of greenhouse gases released every year, chemical companies are employing ‘digitalized’ business processes and leveraging the increasing convergence between OT and IT. Most chemical companies will say they are data rich and information poor. Manufacturing environment architectures that run the plants are made up of unstructured disparate data that was impossible to leverage. With the advent of cloud, large storage, big compute, ease of visualization or the ability to aggregate data from unstructured environments is now possible in a fast and inexpensive way. What used to be limited to the four-walls of the plant is now securely and safely shared across many internal or external organizations reducing cost, improving efficiencies and accelerating competitiveness in the new ecosystem. This session will talk about how applying AI and advanced analytics techniques such as machine learning and cognitive services provide new insights to help optimize performance and prevent problems.