|
This course provides a comprehensive examination of AI applications within chemical engineering, focusing on practical implementation across industrial operations. Participants explore foundational AI concepts, industrial data infrastructure requirements, and integration strategies with control systems, digital twins, and Industrial Internet of Things (IIoT) architectures. The course examines how AI supports process optimization in reactors, separation systems, utilities, and production scheduling while maintaining operational safety and regulatory compliance. Emphasis is placed on the role of AI as a decision-support enhancement that complements engineering judgment rather than replacing professional expertise.
|
|
|
Learning Objectives:
Upon completion of this course, participants will be able to:
- Explain fundamental Artificial Intelligence technologies and their relevance to chemical engineering systems, including machine learning, neural networks, and anomaly detection methods.
- Describe the data infrastructure, industrial integration requirements, and system architectures necessary to support AI deployment within chemical engineering environments.
- Identify opportunities for AI-driven process optimization across reactors, separation systems, utilities, and production operations while maintaining safe operating constraints.
- Evaluate how Artificial Intelligence supports predictive maintenance, equipment reliability analysis, and remaining useful life estimation for critical chemical processing equipment.
- Analyze the role of AI in improving process safety, hazard detection, abnormal situation management, and risk assessment within high-hazard industrial facilities.
- Explain how AI technologies enhance product quality, consistency, and regulatory compliance through real-time monitoring, soft sensors, and Process Analytical Technology integration.
- Recognize cybersecurity risks, ethical responsibilities, regulatory considerations, and professional accountability associated with implementing AI systems in chemical engineering operations.
- Assess emerging AI technologies and future trends influencing chemical engineering practice, including autonomous systems, digital twins, sustainability optimization, and intelligent manufacturing environments.
|
|
