Accuracy Analysis of Incrementally Formed Tunnel Shaped Parts

Amar Kumar Behera, Daniel Afonso, Adrian Murphy, Yan Jin, Ricardo Alves de Sousa

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)
161 Downloads (Pure)

Abstract

Tunnel shaped parts with truncated pyramidal shapes were formed using Single Point Incremental Forming (SPIF) on a Stewart platform. The accuracy behavior of these parts was characterized by an error prediction response surface generated using Multivariate Adaptive Regression Splines (MARS). This response surface predicted over forming for low wall angle parts and under forming for higher wall angle parts. It is based on geometrical parameters associated with features on the part geometry and was used to compensate for inaccuracies in the part geometry. Feature detection was found to work well for tunnel shaped parts using similar thresholds as container shaped parts, while the maximum deviations were found to be lower at a wall angle of 60° compared to a part with wall angle 40°.
Original languageEnglish
Title of host publicationInternational Conference on Intelligent Computing for Sustainable Energy and Environment & International Conference on Intelligent Manufacturing and Internet of Things: Proceedings
Place of PublicationChongqing, China
PublisherSpringer
Pages40-49
Number of pages10
Publication statusEarly online date - 05 Sep 2018

Publication series

NameCommunications in Computer and Information Science
Volume923
ISSN (Print)1865-0929

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