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ML2306 Industrial Analytics for Advanced Manufacturing 6.0 credits

The course is about advanced manufacturing and in particular smart machinery and metrology as integrated parts of manufacturing system for discrete component manufacturing.

Information per course offering

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Termin

Course syllabus as PDF

Please note: all information from the Course syllabus is available on this page in an accessible format.

Course syllabus ML2306 (Autumn 2019–)
Headings with content from the Course syllabus ML2306 (Autumn 2019–) are denoted with an asterisk ( )

Content and learning outcomes

Course contents

Development towards intelligent factories is based on products and production resources such as machines, robots and tools have embedded ability to communicate, perform self diagnosis, become autodidactic and have the possibility to perform automatic adjustments, adaptations and optimisations. In other words, products and processes are intended to become more intelligent and autonomous.

The course deals with advanced production, with a focus on intelligent production equipment and metrology as integrated parts of production systems for manufacturing of components. The course contains a review of industrial robots and machine tools, their configurations, sub-systems, design and operational ability. The course also includes characterisation, simulation, supervision, methods for diagnostics and prognostics of machines, as well as tools for identification of improvement possibilities.

The course aim to teach students about how to acquire and apply new knowledge through three primary learning activities: design, carry out and document individual research. The aim will be achieved through several teaching and introductory activities to reach the intended learning outcomes.

Intended learning outcomes

On completion of the course, the students should be able to:

  • Describe the basic concepts in operational safety, condition based maintenance and capability of machines.
  • Describe the basic design and work principles for advanced production equipment such as machine tools and industrial robots.
  • Explain the relation between capability of advanced production equipment and system performance.
  • Explain the importance of testing and categorisation of advanced production equipment.
  • Explain the basic work principles for sensors and systems: e g accelerometer, inclinometer and velocity gyroscope; and data collection systems.
  • Use a combination of sensors, measuring instruments, statistical data analysis and signal processing to assess the condition and capability of the equipment.
  • Use information from scientific articles and international standards for problem solving.

Literature and preparations

Specific prerequisites

Completed course ML1503 Industrial systems II, 6 credits or the equivalent.

Completed course Bachelor thesis, 15 credits or the equivalent.

Equipment

No information inserted

Literature

Uppgift om kurslitteratur meddelas i kurs-PM.

Examination and completion

If the course is discontinued, students may request to be examined during the following two academic years.

Grading scale

A, B, C, D, E, FX, F

Examination

  • INL1 - Assignment, 1.0 credits, grading scale: P, F
  • LAB1 - Laboratory work, 1.0 credits, grading scale: P, F
  • TEN1 - Written exam, 4.0 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.

The examiner decides, in consultation with KTH's coordinator for disabilities (Funka), about possible adapted examination for students with documented, permanent disabilities. The examiner may permit other examination format for re-examination of individual students.

Opportunity to complete the requirements via supplementary examination

No information inserted

Opportunity to raise an approved grade via renewed examination

No information inserted

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

Add-on studies

No information inserted