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Full Description
Refineries face persistent challenges in improving energy efficiency, ensuring crude availability, and maintaining process safety, with excessive energy consumption being particularly difficult to address. This book explores the integration of chemical engineering principles with Industrial Internet of Things (IIoT) technologies, including artificial intelligence (AI) and machine learning (ML), to optimize refinery operations. This book is organized into four sections - Introduction, Equipment Twin, Instrumentation, and Refinery Applications. This book emphasizes the use of digital tools and engineering fundamentals to enhance equipment design and operational efficiency.
Key Features:
Focuses on the intersection of chemical engineering, refinery operations, and digital technologies, particularly IIoT and Digital Twin (DT) applications.
Explains setup procedures, process simulation with feed characterization, thermodynamic model selection, and equipment specification.
Reviews current refinery challenges such as energy efficiency, predictive maintenance, and decarbonization goals.
Details the development of IIoT applications for three refinery units: sour water stripper unit, amine regeneration unit, and crude and vacuum distillation unit.
Includes case studies and first-principles-based simulation strategies
This book is intended for graduate students, chemical engineering researchers, and refinery professionals.
Contents
1. Introduction to IIoT 2. Introduction to Digital Twin 3. Centrifugal Pump Operation 4. Distillation Column Internals Operation 5. Fired Heaters. 6. Heat Exchanger 7. Instrumentation 8. Sour Water Stripper Unit 9. Amine Regeneration Unit 10. Crude and Vacuum Distillation Unit
