A Study on the Visualization of Parts Manufacturing Prognoses Based on Machine-Learning Algorithms for Supporting Decision-Making in CAD Modelling

Research output: Contribution to book/Conference proceedings/Anthology/ReportConference contributionContributedpeer-review

Contributors

Abstract

Design for manufacturability is considered part of the general skill set of mechanical engineers. However, the requirements in practice are significantly more complex. An approach that uses learning algorithms to set parameters and requirements for specific manufacturing processes, materials, tools, and machines related to component geometries is presented. This approach is evaluated, and forecasts are created. A user interface is being developed to integrate the approach into the working environment of design engineers. This interface is designed to equip engineers with the pertinent information necessary for informed design decisions regarding component geometry. The efficacy of this assistance system, encompassing both the system itself and its user interface, was empirically evaluated in the present study. The results indicated that the system was perceived as helpful by the study participants, and the usability of the user interface was favorably assessed.

Details

Original languageEnglish
Title of host publicationDesign, User Experience, and Usability
EditorsMartin Schrepp
PublisherSpringer Science and Business Media B.V.
Pages131-142
Number of pages12
ISBN (electronic)978-3-031-93221-2
ISBN (print)978-3-031-93220-5
Publication statusPublished - 2025
Peer-reviewedYes

Publication series

SeriesLecture notes in computer science
Volume15794 LNCS
ISSN0302-9743

Conference

Title14th International Conference on Design, User Experience, and Usability
Abbreviated titleDUXU 2025
Conference number14
Descriptionheld as part of the 27th HCI International Conference, HCII 2025
Duration22 - 27 June 2025
Website
LocationGothia Towers Hotel and Swedish Exhibition and Congress Centre & Online
CityGothenburg
CountrySweden

External IDs

ORCID /0000-0003-0937-1927/work/191531383
ORCID /0000-0003-2862-9196/work/191533020

Keywords

Keywords

  • AI-based support, CAD modeling, information visualization