Monday (Sep 22) 1:30PM - 3:10PM
Houston Room North Perimeter
Chairs
Jim Brigman, Principal and Managing Director, Ingenero
Mark Darby, Principal Consultant, CMiD Solutions
Session Description
Applications of AI in the process industries continue to increase, providing a greater role in improving process insights, reliability and operator effectiveness. This session explores how AI-driven models are being deployed to optimize complex systems, reduce downtime, and support smarter decision-making across operations.
From predictive maintenance and process anomaly detection to control strategies and yield optimization, machine learning is enabling plants to move from reactive to proactive operations. By training models on historical and real-time data, AI can uncover patterns too complex for traditional methods—delivering faster insights and actionable recommendations.
This session will highlight real-world applications and success, along with key challenges in implementation, such as data quality, model explainability, and integration with legacy systems.
Paper 1
From Principles to Practice: Governing AI Responsibly in Manufacturing. Kaytlin Henderson, Analytics & AI Leader, Dow
Paper 2
From Data to Decisions: AI-Powered Operational Excellence in Chemical Manufacturing. Girish Thenkurissi, Regional Manager-Process Analytics, Ingenero
Meet the Sponsor: Ingenero
Paper 3
Optimizing Industrial Energy Use with AI-Driven Battery Storage: A Case Study of Imperial Oil’s Sarnia Facility. Angel Lanza Soto, ExxonMobil
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