IND-105
AI for Process Optimization & Control
A two-day program on applying AI to industrial process optimization, real-time control, and operational efficiency.
2 days
Process engineers, control engineers, operations engineers, plant managers
advanced
hybrid
On RequestOverview
Course Overview
Industrial processes generate enormous amounts of data that AI can use to optimize throughput, reduce energy consumption, and improve product quality. This program covers AI techniques for process optimization, model predictive control with ML, real-time advisory systems, and digital twin concepts. Participants learn how AI is enabling a new level of process performance.
Target Audience
Process engineers, control engineers, operations engineers, plant managers
Prerequisites
IND-101 or equivalent. Process engineering background.
Learning Objectives
- Apply AI to industrial process optimization
- Integrate ML with model predictive control
- Build real-time advisory systems
- Develop digital twin concepts for processes
- Measure and sustain optimization results
Key Modules
- AI for Process Optimization Overview
- ML-Based Process Modeling
- Model Predictive Control with ML
- Real-Time Advisory and Decision Support
- Digital Twin Concepts for Process Operations
- Energy and Quality Optimization with AI
- Case Studies in Process AI
Learning Outcomes
- A framework for AI-driven process optimization
- Understanding of ML-based model predictive control
- Practical approach to real-time advisory systems
- A digital twin development roadmap
Instructor
Your Instructor
Dr. Hussein Mustapha
AITECH Academy Faculty
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