Course - Digital twin for sustainable manufacturing - VB8005
VB8005 - Digital twin for sustainable manufacturing
New from the academic year 2020/2021
Examination arrangement: Report
|Evaluation form||Weighting||Duration||Examination aids||Grade deviation|
|Approved report||100/100||1 semesters|
- The concept of modelling and virtual representations of physical worlds
- Understanding of the concept of Digital Twin for manufacturing
- Measurement and data generation
- Predictive maintenance with Digital Twin
- Tools for data exploration, analysis and visualisation
- Characteristics of the physical system to implement digital twin
- Enablers for implementation of Cyber-Physical systems in manufacturing
- Use of digital twin for implementation of sustainable manufacturing principles
- Digital communication - Internet of Things
- Tutorials on Learning Factory Cyber-Physical System
After completing the course, the student is supposed to
- General understanding of digital twin concept and its applications.
- Advanced knowledge of analytical tools in the context of sustainable manufacturing.
- Knowledge of the implementation processes for Digital twin system
- Understanding of the structure of Cyber-Physical systems in sustainable Manufacturing
- Training on digital twin software CIRUS.
- Using of digital twin for predictive maintenance
- Ability to measure and create sustainable development indicators in the context of Cyber-Physical systems
- Ability to think critically when interpreting simulation data from the digital twin
- Be able to convert data into information that gives value in the process of decision-making in the manufacturing process and management
- Have holistic understanding of the supply chain of data: producing, processing and consuming.
- Have a critical and analytical approach to sustainability assessment and decision making for sustainable development solutions in Cyber-Physical systems.
Learning methods and activities
Laboratory exercises - Learning Factory
The lectures in the course will be given on campus. Lectures that sum up the main issues in the lecture will also be available on internet through the learning management system.
Tutoring is given at campus in accordance to announced times.
Further on evaluation
- The course will be graded based on a term paper written by each individual student.
- Re-sit: Whole course must be re-taken.
Recommended previous knowledge
Basic Knowledge on probability and statistics
Basic knowledge on mathematics
Required previous knowledge
Basic Knowledge on manufacturing processes
- Scientific articles, hand-outs and online resources/materials provided by lecturers.
- Industry cases
- Some material must be read before attending the course
Credits: 7.5 SP
Study level: Doctoral degree level
Term no.: 1
Teaching semester: SPRING 2021
Language of instruction: English
- Manufacturing Systems
- Safety, Reliability and Maintenance
- Production and Quality Engineering
- Production and Quality Engineering - Information Technology
Examination arrangement: Report
- Term Status code Evaluation form Weighting Examination aids Date Time Digital exam Room *
Room Building Number of candidates
- * The location (room) for a written examination is published 3 days before examination date. If more than one room is listed, you will find your room at Studentweb.
For more information regarding registration for examination and examination procedures, see "Innsida - Exams"