Connected Worker: Maximizing Worker Awareness, Engagement, and Contribution
Digital Transformation
Facilitator:
Bruce Taylor, FurtherTec
Panel:
Aishwariy Baheti, Bharat Petroleum Corporation Limited
Leandro Martins, Petrobras
Christian McDermott, Voovio Technologies
Wade Smith, Emerson Automation Solutions
A set of case studies are presented by operating companies that discuss Connected Worker initiatives as a vital component of the factory of the future, enabling their organizations to address the challenges of modern manufacturing while reaping the benefits of improved productivity, safety, and efficiency. The Connected Worker, also known as the augmented worker, is seamlessly immersed in their surroundings in an operating facility by the use of a suite of highly advanced digital tool to assist in performing their daily tasks more effectively. Panelists will present their approaches to enabling the Connected Worker in their environment along with what was learned, and benefits achieved.
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Topic
Implementing a Refinery Diesel Pool Optimizer Using Neural Networks and Reinforcement Learning
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
- A site-wide AI adoption strategy
Speakers
Session Start End
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Implementing a Refinery Diesel Pool Optimizer Using Neural Networks and Reinforcement Learning
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
- A site-wide AI adoption strategy
Speakers
Session Start End
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Digital Transformation of Crude Supply, Planning, and Scheduling
Digital Transformation
Facilitator:
Bruce Taylor, FurtherTec
Speaker:
Moiz Sultan, Parkland Refining (B.C.) Ltd.
A case study of Parkland Refining’s transformation of their crude supply, scheduling and refinery demands across their supply system involving Edmonton tanks, transmountain pipeline, transmountain outlets and the refinery. This digitalization initiative allowed Parkland to have improved visibility on the full supply chain with different teams contributing to each aspect where Traders manage supply, schedulers manage pipeline movements, and the Refinery owns the demands.
Speakers
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Topic