MICRO-457 / 3 credits

Teacher(s): Hoffmann Patrik, Wasmer Kilian Thomas

Language: English


Summary

Repeatability in laser material processing is challenging due to high-speed dynamics. To address this issue, the course provides an overview of laser theory, laser-material interaction, various types of sensors (acoustic & optic), data acquisition, online monitoring, and control via machine learning

Content

Keywords

Laser processing, material processing, sensors, data acquistion, signal processing, machine learning, reinforcement learning.

Learning Prerequisites

Required courses

None, the lecture is self-contained.

Recommended courses

- MICRO-310a: Signals and systems I

- MICRO-311a: Signals and systems II

- MICRO-330: Sensors


Learning Outcomes

By the end of the course, the student must be able to:

  • Integrate the laser-materials interaction
  • Assess / Evaluate various type of sensors depending on the time scale of the process
  • Argue on the use of sensors depending on applications
  • Integrate Nyquist-Shannon sampling theorem
  • Integrate concepts of time, frequency, time-frequency domains
  • Recognize the various machine learning methods
  • Decide methods appropriate to practical problems

Transversal skills

  • Use a work methodology appropriate to the task.
  • Set objectives and design an action plan to reach those objectives.

Teaching methods

Oral presentation + discussions, guided exercises and rehearsal

Expected student activities

1) Participate actively in the lecture

2) Carry out all exercises

Assessment methods

Final written exam (85% grade), in-class assessment (15% grade).

Supervision

Office hours No
Assistants No
Forum No

In the programs

  • Semester: Fall
  • Exam form: Oral (winter session)
  • Subject examined: Materials processing with intelligent systems
  • Lecture: 2 Hour(s) per week x 14 weeks
  • Exercises: 1 Hour(s) per week x 14 weeks
  • Semester: Fall
  • Exam form: Oral (winter session)
  • Subject examined: Materials processing with intelligent systems
  • Lecture: 2 Hour(s) per week x 14 weeks
  • Exercises: 1 Hour(s) per week x 14 weeks

Reference week

 MoTuWeThFr
8-9     
9-10     
10-11   CM013 
11-12    
12-13   CM013 
13-14     
14-15     
15-16     
16-17     
17-18     
18-19     
19-20     
20-21     
21-22     

Thursday, 10h - 12h: Lecture CM013

Thursday, 12h - 13h: Exercise, TP CM013