The Faculty of Industrial Design Engineering of the Delft University of Technology offers a bachelor’s degree education programme and three master programs. Our students are lectured in ergonomics and learn to design and conduct research in ergonomics. In this paper we describe the development of methods to realize ergonomic fit mapping based on 3D anthropometrics and to educate students on this topic.

Due to the increasing availability of 3D scan data, we enter the complex field of 3D anthropometry and statistical shape models, which is an increasingly popular mathematical representation for 3D human shape variation. These facilities and knowledge are particularly useful when it comes to products that should fit close to the human body.

The use of 3D anthropometrics is explained and practiced throughout the different stages of complexity. It starts with the use of 1D and 2D anthropometric data, the application of percentiles and the DINED tool Ellipse to see the correlation between two different body dimensions and to determine the consequences for related product dimensions. It ends with the use of 3D anthropometric data for the design of a helmet for cyclists, by way of bi-variate based shape analysis of the head. We made efforts to lower the burden for students working with 3D scan data, for example by providing pre-processed 3D scan databases and casus specific measurement tables.
Original languageEnglish
Title of host publicationProceedings of the 21th International Conference on Engineering and Product Design Education (E&PDE 2019)
EditorsIan Whitfield
Publication statusAccepted/In press - 22 May 2019
Event21st International Conference on Engineering and Product Design Education - , United Kingdom
Duration: 12 Sep 201913 Sep 2019
https://epde.info/epde2019/

Conference

Conference21st International Conference on Engineering and Product Design Education
Abbreviated titleEPDE 2019
CountryUnited Kingdom
Period12/09/1913/09/19
Internet address

    Research areas

  • design education, 3D human shape variation, ergonomic fit mapping

ID: 53627622