Course syllabus

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TRA260 TRA260 Unlocking the potential of additive manufacturing lp2 HT24 (7.5 hp)

Course is offered by the department of Tracks

 

Contact details

The tutors involved are as follows.

Examiner: Prof. Lars Nyborg, phone 7721257, e-mail: lars.nyborg@chalmers.se

Supervisor:

Erika Tuneskog                                                      e-mail: erika.tuneskog@chalmers.se

 

Course purpose

This course consists of project assignments (Work-Packages) of 7.5 credit units. The aim is to make sure that the participants have acquired relevant in-depth knowledge in using topology optimization as a design tool for additive manufacturing.

  • General knowledge in setting up simple topology optimal criteria.
  • STL generation/ model transfer.
  • Adaptations for manufacturing with additive manufacturing.

 

Schedule

Booked times slots by e-mail. Mondays and Thursdays. 

 

Course literature

The lecture hand-outs (pdf-format) will be provided only for course participants.

Via Canvas you will find downloadable documents.  Only students being registered for the course will have access to these documents.

The e-sources behind the course are:

 

MAIN SOURCE

  • Bendsoe, M. P., & Sigmund, O. (2003). Topology optimization: theory, methods, and applications. Springer Science & Business Media.

OTHER SOURCES

  • Liu, S., Li, Q., Liu, J., Chen, W., & Zhang, Y. (2018). A realization method for transforming a topology optimization design into additive manufacturing structures. Engineering, 4(2), 277-285.
  • Siva, G. (2022). STL files to CAD format for topology optimized structures.
  • Mirzendehdel, A. M., & Suresh, K. (2016). Support structure constrained topology optimization for additive manufacturing. Computer-Aided Design, 81, 1-13.
  • Liu, J., Huang, J., Zheng, Y., Hou, S., Xu, S., Ma, Y., ... & Li, L. (2023). Challenges in topology optimization for hybrid additive-subtractive manufacturing: A review. Computer-Aided Design, 103531.

 

Learning objectives and syllabus

Valid for all Tracks courses:

  • critically and creatively identify and/or formulate advanced architectural or engineering problems
  • master problems with open solutions spaces which includes to be able to handle uncertainties and limited information.
  • lead and participate in the development of new products, processes and systems using a holistic approach by following a design process and/or a systematic development process.
  • work in multidisciplinary teams and collaborate in teams with different compositions
  • show insights about cultural differences and to be able to work sensitively with them.
  • show insights about and deal with the impact of architecture and/or engineering solutions in a global, economic, environment and societal context.
  • identify ethical aspects and discuss and judge their consequences in relation to the specific problem
  • orally and in writing explain and discuss information, problems, methods, design/development processes and solutions
  • fulfill project specific learning outcomes
Course specific:
  • Present an application specific approach to DfAM
  • Adapt design concepts for the respective metal AM technology (LB-PBF or EB-PBF)
  • Screen and choose an adequate metal AM technology (LB-PBF or EB-PBF) for manufacturing the developed part, including design limitations/opportunities and cost evaluation
  • Work collaboratively within a multi-disciplinary group
  • Describe and understand the basic principles for topology optimization.
  • Choosing and implementing optimal criteria methods for various situations of potential importance in practical engineering.
  • Learn to use different software for topology optimization.
  • Describe and understand the basic principles for implementation of topology optimization in additive manufacturing designs.
  • Set up and model simple problems with topology optimization and prepare models for manufacturing with additive manufacturing.

 

 

Course design

Description of the course's learning activities; how they are implemented and how they are connected. This is the student's guide to navigating the course. Do not forget to give the student advice on how to learn as much as possible based on the pedagogy you have chosen. Often, you may need to emphasize concrete things like how often they should enter the learning space on the learning platform, how different issues are shared between supervisors, etc.

Provide a plan for

  • lectures
  • exervises
  • laboratory work
  • projects
  • supervision
  • feedback
  • seminars

Should contain a description of how the digital tools (Canvas and others) should be used and how they are organized, as well as how communication between teachers and students takes place (Canvas, e-mail, other).

Do not forget to describe any resources that students need to use, such as lab equipment, studios, workshops, physical or digital materials.

You should be clear how missed deadlines and revisions are handled.

 

Link to the syllabus on Studieportalen.

Study plan

 

Examination form

The course consists of three separate Work Packages (WP), each of which is completed in groups. At the end of each WP, every group is required to give a 15-minute presentation and submit a 1,500-word report.

At the end of the course, each student must submit an individual reflection document, with a maximum of 1,000 words.

 

Course summary:

Date Details Due