Using Generative AI in Process Design, Chemical Engineering & Process Safety
Consultant/Trainer: Jan van Opstal
This Petrogenium 2-day course introduces engineers to the practical use of generative AI in process design, chemical engineering, and process safety. Participants will learn how to apply generative AI for calculations, simulations, and documentation in real engineering workflows. The training covers process design fundamentals, control strategies, HAZOP/LOPA facilitation, and safety studies. Hands-on workshops with case studies in hydrogen, ammonia, methanol, and SAF ensure direct industry relevance. By the end, participants will be equipped to integrate generative AI effectively while validating results against engineering standards.
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Participants
- Process Engineers involved in process design, simulation, and optimization.
- Chemical Engineers working on equipment sizing, thermodynamics, and reaction engineering.
- Process Safety Engineers responsible for HAZOP, LOPA, C&E diagrams, and SIS/SRS development.
- Control & Automation Engineers working on P&IDs, control narratives, and process automation strategies.
- Project & Design Engineers in oil & gas, hydrogen, ammonia, methanol, and sustainable fuels projects.
- Engineering Managers & Consultants seeking productivity gains and standardization with generative AI.
Learning Objectives
Participants will learn how to apply generative AI in process design, chemical engineering, and process safety studies. They will develop skills in calculations, equipment sizing, control schemes, and documentation support. The course builds competence in HAZOP, LOPA, and safety instrumented system development with generative AI assistance. By the end, participants can integrate generative AI into engineering workflows while
ensuring validation against standards.
Day 1
Module 1: Introduction to generative AI in Process Engineering
1. Role of generative AI-powered tools in Chemical Engineering & Process Safety
2. Overview of generative AI capabilities, limitations, and reliability checks
3. Integrating generative AI with engineering workflows (simulation tools; HYSYS, UNISIM)
4. Importing Process Flow Scheme and P&ID in generative AI
Module 2: Process Design Fundamentals with generative AI
1. Material & Energy Balances (H&MB generation support)
2. Stream property predictions (enthalpy, phase, compositions)
3. Equipment design calculations:
- Heat exchangers (UA, LMTD, approach temperatures)
- Pumps & compressors (pump curves, surge line, NPSH)
- Distillation columns (McCabe-Thiele, shortcut distillation, tray efficiency)
Workshop: Using generative AI to draft a Heat & Material Balance for a Distillation column case study
Day 2
Module 3: Process Control & Automation
1. Control loop narratives (flow, pressure, temperature, level control)
2. P&ID development support and tag generation
3. Control valve sizing and pump minimum flow protection
4. Generative AI as Copilot for Dynamic Simulations in UNISIM/HYSYS
Module 4: Specialised Chemical Engineering Applications
1. Reactor kinetics support (CSTR, PFR, catalytic reactors)
2. Thermodynamics (VLE, EOS, property methods)
3. Separation technologies: distillation, membrane, adsorption, and extraction
4. Process intensification concepts
Workshop: Drafting a process control scheme for a Distillation column case study
Programme
Day 1
Module 1: Introduction to generative AI in Process Engineering
1. Role of generative AI-powered tools in Chemical Engineering & Process Safety
2. Overview of generative AI capabilities, limitations, and reliability checks
3. Integrating generative AI with engineering workflows (simulation tools; HYSYS, UNISIM)
4. Importing Process Flow Scheme and P&ID in generative AI
Module 2: Process Design Fundamentals with generative AI
1. Material & Energy Balances (H&MB generation support)
2. Stream property predictions (enthalpy, phase, compositions)
3. Equipment design calculations:
- Heat exchangers (UA, LMTD, approach temperatures)
- Pumps & compressors (pump curves, surge line, NPSH)
- Distillation columns (McCabe-Thiele, shortcut distillation, tray efficiency)
Workshop: Using generative AI to draft a Heat & Material Balance for a Distillation column case study
Day 2
Module 3: Process Control & Automation
1. Control loop narratives (flow, pressure, temperature, level control)
2. P&ID development support and tag generation
3. Control valve sizing and pump minimum flow protection
4. Generative AI as Copilot for Dynamic Simulations in UNISIM/HYSYS
Module 4: Specialised Chemical Engineering Applications
1. Reactor kinetics support (CSTR, PFR, catalytic reactors)
2. Thermodynamics (VLE, EOS, property methods)
3. Separation technologies: distillation, membrane, adsorption, and extraction
4. Process intensification concepts
Workshop: Drafting a process control scheme for a Distillation column case study