(162a) Sustainable Machine Learning in the Process Industries

In recent years, there has been much attention to the use of machine learning for improving process manufacturing performance. And interest has been accelerating, as open source, big data, cloud architectures, low-cost sensors, wireless, virtualization, and IoT continue to mature. Areas of applications include predictive analytics, performance monitoring, reliability, and management by exception, to name a few.

But even for well-funded efforts with talented teams, pilot projects are often unsuccessful, and long-term sustained solutions are extremely rare. Seeq will identify challenges, failure modes, and critical success factors that are impeding innovation and adoption. Seeq will also demonstrate its environment designed for data scientists, along with the tools and strategies necessary to operationalize solutions in a truly sustainable manner.