Course content

This course offers an in-depth exploration of the concepts, methods, and tools used in the creation and application of digital twins for sustainable manufacturing. A digital twin is a virtual representation of a physical object or system, updated from real-time data and using simulation, machine learning, and reasoning to help decision-making. This paradigm is increasingly pivotal in various industries for optimizing operations, predicting outcomes, and enhancing sustainability.

Course Content:

• Introduction to modeling and virtual representations of physical worlds
• Overview of the Digital Twin paradigm
• In-depth study of modeling and simulation methods/tools, including Discrete Event Simulation, System Dynamics, and Agent-Based Modeling
• Practical application to Finite Element Method (FEM) simulation
• Data collection and harmonization techniques
• Tools and methods for data exploration, analysis, and visualization
• Making sense of data to derive meaningful insights
• Quantitative analysis methodologies and report writing

Learning outcome

Upon completing this course, students will acquire:

1. Knowledge:

• A comprehensive understanding of the digital twin paradigm and its various applications.
• Advanced knowledge of analytical tools within the context of sustainable manufacturing.
• Familiarity with different simulation tools for decision-making in sustainable manufacturing, including FEM simulation.

1. Skills:

• Proficiency in selected software tools such as discrete event simulation, system dynamics, Monte Carlo methods, agent-based modeling, and FEM simulation.
• Capability to measure and develop sustainable development indicators.
• Critical thinking skills for interpreting sustainable development indicators.
• Competence in writing detailed reports using quantitative analytical tools.

1. General Competence:

• Ability to convert data into actionable information for decision-making in manufacturing processes and management.
• Holistic understanding of the supply chain of data: production, processing, and analysis.
• A critical and analytical approach to sustainability assessment and decision-making for sustainable development solutions within manufacturing.
• Understanding the strengths and differences between various modeling and simulation software/methods.

Learning methods and activities

Teaching Methods:

• Interactive seminars utilizing the flipped classroom approach
• E-learning modules for flexible learning
• Project-based work to apply theoretical knowledge
• Collaborative group work to enhance teamwork skills
• Guest lectures from industry experts to provide real-world insights
• Hands-on practical exercises using modeling and simulation tools

The course is designed to be accessible to both on-campus and remote students. Each student can choose the pedagogical arrangement that best fits their needs. Seminars will be conducted on campus and are also available via streaming through Blackboard Collaborate/MS Teams, with recordings accessible through NTNU's learning management system. Tutoring will be available both on-campus and online at scheduled times. The course assessment is based on a pass/fail system. The medium of instruction is Norwegian/English, and all assignments, reports, and documentation must be submitted in Norwegian/English.

Compulsory assignments

• Exercises

Specific conditions

Recommended previous knowledge

Basic concepts of probability and statistics

Basic concepts of mathematics

Course materials

Relevant articles and reports will be given at course start.