• Evaluate the essence of process intensification, energy analysis, and artificial intelligence.
• Apply these concepts to realize a sustainable process industry.

The Sustainable Process Engineering course has a scope of study materials in the form of three main pillars of the elements that make up Sustainable Process Engineering, namely process intensification, energy analysis, and artificial intelligence for industry. The language of instruction used in learning is Indonesian. Learning is implemented using interactive lecture methods and case studies. The learning mode in this course is offline, with the use of EMAS UI and Microsoft Teams for distributing lecture materials as well as collecting assignments and exercises.

1. Demirel, R., & Rosen, M. A. (2023). Sustainable Process Engineering: Process Intensification, Energy Analysis, Artificial Intelligence. CRC Press: Boca Raton.
2. Szekely, G. (2021). Sustainable Process Engineering. De Gruyter: Berlin.
3. Brennan, D. (2012). Sustainable Process Engineering: Concepts, Strategies, Evaluation, and Implementation. CRC Press: Boca Raton.
4. Koltuniewicz, A. B. (2014). Sustainable Process Engineering: Prospects and Opportunities. De Gruyter: Berlin.
5. Boodhoo, K., & Harvey, A. (2013). Process Intensification for Green Chemistry: Engineering Solutions for Sustainable Chemical Processing. Wiley: United Kingdom.

• Sustainability Concept in the Process Industry

  • Introduction to sustainability in industrial processes
  • Principles of sustainable development and their application to the process industry
  • Balancing economic, environmental, and social aspects in industrial practices

• Process Routes and Green Industry Matrix

  • Identifying sustainable process routes in the chemical and process industries
  • Using the green industry matrix to evaluate and optimize process sustainability
  • Case studies demonstrating the application of sustainable process routes

• Process Intensification Techniques

  • Overview of process intensification principles and methods
  • Techniques for improving process efficiency, reducing energy consumption, and minimizing waste
  • Examples: compact heat exchangers, reactive distillation, and microreactors

• Artificial Intelligence in the Process Industry

  • Role of artificial intelligence (AI) in optimizing industrial processes
  • AI applications: predictive maintenance, process monitoring, and decision-making
  • Integration of AI tools such as machine learning and neural networks in process design

• Process Industry Life Cycle

  • Understanding the life cycle of industrial processes: raw material extraction, production, usage, and disposal
  • Life cycle assessment (LCA) for evaluating environmental impacts
  • Strategies for improving the life cycle sustainability of industrial processes

• Energy Analysis

  • Principles of energy analysis in the process industry
  • Techniques for evaluating energy efficiency and identifying energy-saving opportunities
  • Tools and methodologies for conducting energy audits and analysis