Multivariate adaptive regression splines as a tool to improve the accuracy of parts produced by FSPIF

Johan Verbert*, Amar Kumar Behera, Bert Lauwers, Joost R. Duflou

*Corresponding author for this work

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

17 Citations (Scopus)

Abstract

Feature Assisted Single Point Incremental Forming (FSPIF) is a technique to increase the accuracy of the SPIF process. FSPIF generates an optimized toolpath based on the features detected in the workpiece geometry and using knowledge of the behavior of these features during incremental forming. Using this optimized toolpath, parts can be formed with higher accuracy. The prediction of the dimensional deviations occurring in different features during forming as a function of their type (e.g. planar, ruled, freeform or ribs) and various process parameters, such as sheet thickness, wall angle, tool diameter, rolling direction, etc., is an important step in the FSPIF method. Due to the great number of parameters and combinations that are possible, a mathematical tool should be used in order to automate the prediction process. One such tool is MARS or Multivariate Adaptive Regression Splines, a fast, non-parametric multivariate regression technique with automatic variable selection, which generates continuous surfaces as a response function. In this paper, the authors describe and validate the use of MARS as a tool to predict deviations in uncompensated tests by training the MARS model using only a limited number of experiments. Using this validated model, compensation strategies are developed and implemented, which have shown significant improvements in accuracy in new test cases.

Original languageEnglish
Title of host publicationSheet Metal 2011, SheMet 2011
Pages841-846
Number of pages6
Volume473
DOIs
Publication statusPublished - 2011
Externally publishedYes
Event14th International Conference on Sheet Metal, SheMet 2011 - Leuven, Belgium
Duration: 18 Apr 201120 Apr 2011

Publication series

NameKey Engineering Materials
Volume473
ISSN (Print)1013-9826

Conference

Conference14th International Conference on Sheet Metal, SheMet 2011
CountryBelgium
CityLeuven
Period18/04/201120/04/2011

Keywords

  • Accuracy
  • Features
  • Incremental forming
  • Regression splines
  • SPIF

ASJC Scopus subject areas

  • Materials Science(all)
  • Mechanics of Materials
  • Mechanical Engineering

Fingerprint Dive into the research topics of 'Multivariate adaptive regression splines as a tool to improve the accuracy of parts produced by FSPIF'. Together they form a unique fingerprint.

  • Cite this

    Verbert, J., Behera, A. K., Lauwers, B., & Duflou, J. R. (2011). Multivariate adaptive regression splines as a tool to improve the accuracy of parts produced by FSPIF. In Sheet Metal 2011, SheMet 2011 (Vol. 473, pp. 841-846). (Key Engineering Materials; Vol. 473). https://doi.org/10.4028/www.scientific.net/KEM.473.841