Advanced Process Control, AI & the Future of Oil & Gas Operations
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Model Predictive Control (MPC) is an advanced control technology that improves operational performance by predicting future process behavior and continuously optimizing control actions within defined operating constraints. By reducing process variability, MPC enables facilities to operate closer to production, quality, energy, and safety limits while maintaining stable and reliable operations.
- The basics of MPC and its role in optimizing complex industrial processes.
- How AI, ML, predictive analytics, and MPC work together to support more autonomous operations.
- How MPC can increase production, improve energy efficiency, and enhance profitability without major capital investments.
- An introduction to PEMS (Predictive Emissions Monitoring Systems) and how advanced analytics can support emissions monitoring and compliance initiatives
- Real-world examples of MPC applications across upstream, midstream, and LNG facilities.
Speaker:
Juliano De Goes Arantes
Consulting Mgr. - Model Predictive Control (MPC)
Rockwell Automation
Juliano de Goes Arantes is the MPC Sales Manager for EMEA at Rockwell Automation, responsible for helping industrial organizations achieve higher profitability, improved quality, greater operational efficiency, and sustainability through Model Predictive Control (MPC) and Advanced Process Control (APC).
With nearly three decades of experience in process industries, Juliano has a strong background in operations, maintenance, automation, project management, and hands-on APC implementation. His practical experience working directly with optimization projects enables him to bridge the gap between plant operations, process engineering, and business objectives.
Today, he leads MPC sales and pre-sales activities across EMEA and supports customers in industries including Oil & Gas, Chemicals, Petrochemicals, Mining, Power, and Cement.
