Modern Monitoring Chemical

MODERN MONITORING

CHEMICAL ENGINEERING

In the era of smart manufacturing, the importance of detecting and identifying the root cause of any deviation in the manufacturing environment can’t be overemphasized. Controlled systems are growing more complex, feature more sensors and are closer than ever to autonomous operation. That’s why faculty members Peter He and Jin Wang are researching ways to create manufacturing intelligence from real-time data for process monitoring. Their strategy combines systems engineering principles such as dynamic modeling and optimization with data analytics techniques such as statistical approaches, artificial neural networks and deep learning algorithms. The result, says Wang, “is an integrated human intelligence and artificial intelligence approach that takes advantages of the latest advancements in these fields.” The National Science Foundation funded project is a synergistic collaboration between Auburn and Praxair, an industrial gases company that annually spends more than $1 billion on energy just to power its facilities. For Praxair, decreasing operating costs related to energy usage is a high priority. If successful, He and Wang’s project will enhance Praxair’s ability to monitor different plants worldwide from a centralized operating center in the U.S. “The outcome of this project has the potential to help shape the future of smart manufacturing,” He said. “It will expose Auburn graduate and undergraduate students to current and future industrial needs, and provide opportunities for interacting with industrial researchers.”

PETER HE

Associate Professor of Chemical Engineering 334-844-7602 qzh0004@auburn.edu Website: aub.ie/PHe

JIN WANG

Walt and Virginia Woltosz Professor of Chemical Engineering 334-844-2020 jzw0001@auburn.edu Website: aub.ie/jzw0001