In an era of rapid technological advancement, achieving positive reliability outcomes requires a strategic blend of innovation and foundational maintenance practices. This presentation explores how organizations can harness emerging technologies to enhance awareness and enable early anomaly detection. By integrating data-driven insights with proven maintenance strategies, companies can improve operational reliability and efficiency. Through an open discussion, we will explore the real-world challenges and opportunities that arise when merging traditional maintenance with cutting-edge technology.
The session is designed as an introductory-level discussion that highlights the value of combining traditional hands-on maintenance practices with modern monitoring tools to support a more comprehensive and reliable approach to decision-making. Together we aim to uncover practical strategies for building a resilient, future-ready maintenance culture. Participants will be encouraged to share experiences and insights on navigating common pitfalls—such as over-reliance on digital tools, integration complexities, and maintaining a balance between automation and human expertise.
Moderator:
Dean Roberts, Ergon Refining, Inc.
Speakers:
Jaxson O'Brien, CHS Inc.
Mark Sannes, Flint Hills Resources, LLC
Facilitator:
Andy Woods, Chevron Phillips Chemical Company LP
Speakers:
Jim Griffin, San Jacinto College
Ferril Onyett, BrandSafway
Brian Novicki, Valero Energy Corporation
Will the energy industry have enough operating and design & construction personnel to operate and maintain existing assets and build and operate the infrastructure planned for the future? How can we address the changing needs of the generation about to enter the workforce? Are companies adopting and implementing advanced technologies to enhance safety, quality, and efficiency on each jobsite?
The panel, consisting of owners, EPCs, academia, and construction workforce training and development experts, will discuss how we can develop, engage, train and sustain enough personnel to meet the projected energy and infrastructure needs across the country.
Speakers:
Darin Foote, CHS Inc.
Chuck Johnston, Marathon Petroleum Corporation LP
Vidyashankar Kuppuraj, Marathon Petroleum Corporation
Johnny Serafin, Phillips 66
Nic Tognetti, CHS Inc.
Advanced process control (APC) has been employed in FCC applications for 40 years. Despite the similarities of FCC Technology and APC platforms the success of these applications varies widely. In this session we will discuss common threads that lead to poor outcomes and how to build a successful APC program on a modern FCC.
Facilitator:
Andy Woods, Chevron Phillips Chemical Company LP
Speakers:
Jim Griffin, San Jacinto College
Ferril Onyett, BrandSafway
Brian Novicki, Valero Energy Corporation
Will the energy industry have enough operating and design & construction personnel to operate and maintain existing assets and build and operate the infrastructure planned for the future? How can we address the changing needs of the generation about to enter the workforce? Are companies adopting and implementing advanced technologies to enhance safety, quality, and efficiency on each jobsite?
The panel, consisting of owners, EPCs, academia, and construction workforce training and development experts, will discuss how we can develop, engage, train and sustain enough personnel to meet the projected energy and infrastructure needs across the country.
Speakers:
Tieraney Celestine, Motiva Enterprises, LLC
Andrew Martindale, Motiva Enterprises, LLC
David Midkiff, Motiva Enterprises, LLC
This session will discuss the evolution and ability of a successful materials management system that prepares for events at a time when rising material, labor costs and availability is due to inflation and supply chain interruptions.
In this session we will discuss in detail the continuous improvement in plant profitability achieved by having a holistic approach for advanced automation where applications such as procedural automation, Artificial Intelligence Plant Control (AIPC), control strategy in distributed control system and safety instrumented system all work together in harmony. AIPC, leveraging Reinforcement Learning (RL), offers a transformative approach to process plant optimization, addressing key limitations of traditional Model Predictive Control (MPC).
While MPC has been a cornerstone of advanced process control for decades, its reliance on linear models and manual tuning often struggles to effectively handle complex, nonlinear process dynamics, particularly in scenarios with frequent disturbances or changing operating conditions. AIPC overcomes these limitations by continuously learning and adapting to the plant's behavior. We will share our motivation to develop this product in-house and how easy it is to maintain the application and sustain the benefits by existing operations staff without the need of any AI or MPC expertise.
Participants will:
Understand the benefits of using AIPC over conventional MPC
Learn how Linde has successfully implemented AIPC on their Air Separation Units that include cryogenic distillation and very complex heat integration and recovery process.
Realize the importance of embracing this cutting-edge technology for improving profitability and safety of their plant and also for their personal and professional growth.
What is basic process control?
How is it done? Why is it important for the refinery engineer to be familiar with the basics?
In this foundational session, the discussion will focus on the workings of everyday loops and instrumentation that a refinery engineer is likely to encounter.
Moderator:
Sriram Ramaganesan, Phillips 66
Speakers:
Joe Boyce, Marathon Petroleum Corporation
Scott Flanagan, Marathon Petroleum Corporation
Tim Olsen, Emerson Automation Solutions
This session covers the complete spectrum of process optimization methods at a refinery or petrochemical plant. From models predictive control to real time optimization via process models and onto machine learning methods via neural networks. The attendee will gain an understanding of when to apply these methods in practice and the organizational support needed to succeed long term.
First principles models with adjustable parameters alongside parameterised neural networks are applied in a commercial package to a refinery product train. This method offers simplicity of implementation as compared to the more conventional real time first principles models and the entirely machine learning approaches. The implementation is at a commercial refinery and organizational, implementation and design details are discussed.
Moderator:
Rob Confair, Marathon Petroleum Corporation