Digital Fabrication and Makerspace Skills for Science (FAB)

Course content

This course focuses on digital fabrication machines (like 3D printers and laser cutters) and electronic sensing technologies (like Arduinos and infrared cameras), and their ability to support research and laboratory tasks in various fields of science. We will get hands-on in the makerspace to build skills in creating new physical objects from digital designs, and new sensing devices that can understand the world. Then, we will break into groups and work on real problems in laboratories by building a novel solution to a scientist’s problem. The instructors will provide a series of sample cases that students can explore with their projects, or they can bring their own ideas for scientific problems to solve. We will also discuss the future of digital fabrication technologies for science, for example, in organ printing, construction, and other fields. Throughout the course, we will explore papers and projects that develop novel applications of makerspace technologies or use them in innovative ways, as well as get a basic grounding in iterative development. 

 

The skill-building component will include core makerspace skills like: 

  • 2D and 3D modeling 

  • Laser cutting and 3D printing objects which fit with existing objects or offer interactive capabilities 

  • Soldering 

  • Basic and advanced circuit prototyping and microcontroller programming 

  • Signal processing and machine learning for analyzing sensor signals 

 

The project component will focus on: 

  • Application of skills gained 

  • Documentation of the project in the format of, e.g., an Instructable 

  • Iterative development in connection with scientific, technical, and user feedback 

 

The course is highly hands-on, with lots of building and experimentation. Students will be taught and expected to apply safety practices around the machines. 

 

NB: Students are not expected to have any previous experience in programming, design, or working with digital fabrication machines. Bring your curiosity and excitement, and we will teach you everything you need to know! 

Learning outcome

At course completion, the successful student will have

Knowledge of

  • digital fabrication technologies; their basic underlying principles, advantages and disadvantages; and possible application to various scientific and engineering disciplines 

  • existing and up-and-coming applications of digital fabrication technologies in scientific fields like medicine and construction 
     

Skills in

  • designing and manufacturing 2D and 3D objects with various digital fabrication technologies 

  • translating between real-world and virtual-world dimensions and data for precision fabrication at various physical scales 

  • exploring current research on new ways to use digital fabrication technologies in the sciences 

  • assembling and programming basic electronic circuits for sensing 

  • analyzing basic sensing signals using signal processing or machine learning techniques 
     

Competences to

  • analyzing real-world needs of scientists and creating solutions with digital fabrication technologies 

  • practical digital fabrication technology usage 
     

This course is a mix of short lectures and demos, hands-on time in the lab, and field- and project-work in groups.

Selected papers and book chapters. See Absalon when the course is set up.

 

No particular pre-requisites. Basic programming knowledge is a bonus.

Oral
Continuous feedback during the course of the semester
Peer feedback (Students give each other feedback)
ECTS
7,5 ECTS
Type of assessment
Oral exam on basis of previous submission, 20 min.
Type of assessment details
The exam consists of two parts:

A) A group report in the form of a portfolio based on the group project executed during the course.

B) An individual oral exam (without preparation) based on the group project and group report as well as other material from the course

The written and oral examination are not weighted, only one overall assessment is provided for the two parts of the exam.
Aid
All aids allowed

The student can use all aids for the project and preparation for the oral exam, but during the oral exam they are not allowed to use internet or AI.

Marking scale
7-point grading scale
Censorship form
No external censorship
Exam period

Several Internal examiners.

Re-exam

Same as the ordinary exam.  

For the re-exam the student must submit a new individual report or resubmit an edited version of the group report no later than 3 weeks before the re-exam. 

Criteria for exam assessment

See Learning Outcomes.

Single subject courses (day)

  • Category
  • Hours
  • Lectures
  • 24
  • Preparation
  • 32
  • Practical exercises
  • 24
  • Project work
  • 110
  • Exam
  • 16
  • English
  • 206

Kursusinformation

Language
English
Course number
NDAB25000U
ECTS
7,5 ECTS
Programme level
Bachelor
Duration

1 block

Placement
Block 1
Schedulegroup
C
Capacity
16
The number of places might be reduced if you register in the late-registration period (BSc and MSc) or as a credit or single subject student.
Studyboard
Study Board of Mathematics and Computer Science
Contracting department
  • Department of Computer Science
Contracting faculty
  • Faculty of Science
Course Coordinator
  • Valkyrie Savage   (4-857082704f73783d7a843d737a)
Saved on the 13-03-2025

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