The course is about decision support systems in advanced manufacturing technology, based on industrial metrology tools and procedures. The course includes an extensive review of advanced manufacturing processes and industrial metrology tools, methods, algorithms and their applicability, configurations, subsystems, structure, design and operational capability. During the course, extensive training is given in handling and evaluation of production and measurement data through use of applicable statistical tools and algorithms for machine learning to receive and account result with traceability. The course intends to teach the students how measuring techniques assist decision support in advanced production. On completion of the course, the students will be able to apply new knowledge through three main activities : design, carry out and document personal research.
MG2045 Decision-making for Advanced Manufacturing 6.0 credits
Information per course offering
Information for Autumn 2025 Start 27 Oct 2025 programme students
- Course location
KTH Campus
- Duration
- 27 Oct 2025 - 12 Jan 2026
- Periods
Autumn 2025: P2 (6 hp)
- Pace of study
33%
- Application code
50861
- Form of study
Normal Daytime
- Language of instruction
English
- Course memo
- Course memo is not published
- Number of places
Min: 5
- Target group
- Compulsory for TIEMM MOPR1 Conditionally elective for TPRMM Elective for all other Master programmes as long as it can be included in your programme.
- Planned modular schedule
- [object Object]
- Schedule
Contact
Course syllabus as PDF
Please note: all information from the Course syllabus is available on this page in an accessible format.
Course syllabus MG2045 (Autumn 2021–)Headings with content from the Course syllabus MG2045 (Autumn 2021–) are denoted with an asterisk ( )
Content and learning outcomes
Course contents
Intended learning outcomes
After passing the course, the students should be able to:
- Describe advanced manufacturing processes
- Explain the importance of metrology (measurement technology) in advanced manufacturing processes
- Describe methods and instruments that are used industry for metrology purposes
- Evaluate measurement and manufacturing data by use of suitable statistical tools and algorithms for machine learning
- Apply decision support systems for advanced manufacturing
Literature and preparations
Specific prerequisites
Admitted to a Master's programme (two-year).
Literature
You can find information about course literature either in the course memo for the course offering or in the course room in Canvas.
Examination and completion
Grading scale
A, B, C, D, E, FX, F
Examination
- INLA - Individual home assignment, 1.5 credits, grading scale: A, B, C, D, E, FX, F
- LABA - Laboratory work, 1.5 credits, grading scale: P, F
- PROA - Project work, 3.0 credits, grading scale: A, B, C, D, E, FX, F
Based on recommendation from KTH’s coordinator for disabilities, the examiner will decide how to adapt an examination for students with documented disability.
The examiner may apply another examination format when re-examining individual students.
If the course is discontinued, students may request to be examined during the following two academic years.
Examiner
Ethical approach
- All members of a group are responsible for the group's work.
- In any assessment, every student shall honestly disclose any help received and sources used.
- In an oral assessment, every student shall be able to present and answer questions about the entire assignment and solution.
Further information
Course room in Canvas
Registered students find further information about the implementation of the course in the course room in Canvas. A link to the course room can be found under the tab Studies in the Personal menu at the start of the course.
Offered by
Main field of study
Mechanical Engineering
Education cycle
Second cycle