Artificial Intelligence, Advanced Process Controls
Facilitator:
Atique Malik, AIControl LLC
Speaker:
Yangdong Pan, Delek US
Toni Adetayo, Imubit, Inc.
Multi-unit optimization has long been a complex issue in the oil and gas industry. Despite efforts using first-principle models or empirical approaches, challenges persist. However, the emergence of machine learning and AI technologies offers an alternative solution. In particular, AI-based process control technology has shown promise for multi-unit optimization. This session will delve into an example using a distillate system optimizer to understand how these AI models address large-scale optimization challenges and how parent and child models collaborate.
Participants will learn:
The strength of the technology and its high flexibility of handling core issues
How the technology deals with the availability of individual units, and cooperates with unit controllers from other advanced control technologies
How to sustain the technology’s performance and benefits
This session will highlight Phillips 66’s focus on the need to go beyond the vibration signature and understand the root cause of the component failure. We will also discuss leveraging new technologies like machine learning and artificial intelligence to prevent inherent issues.
See related presentations on MI on the AFPM Safety Portal at https://safetyportal.afpm.org/
Motiva’s 2.0 Tank Division journey leveraged time-tested technology that has consistently delivered success in our industry. Innovative robotic cleaning not only enhances safety compared to manual blasting but also boosts efficiency and reduces waste disposal costs. This means a safer, more cost-effective solution. To further elevate our tank maintenance process, we introduced “Pneumatic Roof Raising” technology, which significantly minimizes human exposure to negative ergonomics, pinch points, and the need for extensive scaffolding which translates to quicker project completion, reduced downtime, and enhanced overall safety.
See related presentations on the AFPM Safety Portal at https://safetyportal.afpm.org/
In this session, we will present a case study on wash water reliability, examining the critical role a well-designed water wash plays in maintaining the mechanical integrity of a system. We will also discuss lessons learned from investigations into excessive accelerated corrosion in an overhead system.
Check out the 2024 Summit Session Inspection and Reliability of Wash Water Systems https://safetyportal.afpm.org/
Discussion of the basics of good data collection, appropriate methods for filtering data, database requirements and the supporting infrastructure for possible Machine Learning applications.
Speakers:
Chris Harrison, Marathon Petroleum Corporation
This session will discuss the project development and workflow, implementation, and application maintenance of an Imubit DLPC that was used to reduce giveaway on drum cycles on a delayed coker unit. The DLPC was successful in reducing the number of cycles in which the target level was not achieved in the fixed cycle time period. This resulted in an overall reduction in the number of barrels given away in each cycle. The application has achieved great acceptance by Operations.
Participants will:
Gain an understanding of the Imubit DLPC application to reduce giveway on Coker Drum cycles
Gain an understanding of the workflow for an Imubit DLPC project
Gain an understanding of unique challenges and lessons learned from the project