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Event

Laboratory Production Metrology [SS202150550]

Type
internship (P)
Term
SS 2020
SWS
3
Language
Deutsch
Appointments
0
Links
ILIAS

Lecturers

Organisation

  • KIT-Fakultät für Maschinenbau

Part of

Literature

Skript zur Veranstaltung wird über (https://ilias.studium.kit.edu/) bereitgestellt. Ebenso wird auf gängie Fachliteratur verwiesen.

Lecture notes will be provided in Ilias (https://ilias.studium.kit.edu/). Additional reference to literature will be provided, as well. 

Note

During this course, students get to know measurement systems that are used in a production system. In the age of Industry 4.0, sensors are becoming more important. Therefore, the application of in-line measurement technology such as machine vision and non-destructive testing is focussed.  Additionally, laboratory based measurement technologies such as computed tomography are addressed. The students learn the theoretical background as well as practical applications for industrial examples. The students use sensors by themselves during the course. Additionally, they are trained on how to integrate sensors in production processes and how to analyze measurement data with suitable software.

The following topics are addressed:

  • Classification and examples for different measurement technologies in a production environment
  • Machine vision with optical sensors
  • Information fusion based on optical measurements
  • Robot-based optical measurements
  • Non-destructive testing by means of acoustic measurements
  • Coodinate measurement technology
  • Industrial computed tomography
  • Measurement uncertainty evaluation
  • Analysis of production data by means of data mining

 

Learning Outcomes:

The students …

  • are able to name, describe and mark out different measurement technologies that are relevant in a production environment.
  • are able to conduct measurements with the presented  in-line and laboratory based measurement systems.
  • are able to analyze measurement results and asses the measurement uncertainty of these.
  • are able to deduce whether a work piece fulfills quality relevant specifications by analysing measurement results.
  • are able to use the presented measurement technologies for a new task.

 

Workload:

regular attendance: 31,5 hours
self-study: 88,5 hours