A prediction and compensation scheme for in-plane shape deviation of additive manufacturing with information on process parameters

Longwei Cheng, Andi Wang, Fugee Tsung

Research output: Contribution to journalArticlepeer-review

22 Scopus citations

Abstract

Shape fidelity is a critical issue that hinders the wider application of Additive Manufacturing (AM) technologies. In many AM processes, the shape of a product is usually different from its input design and the deviation usually depends on certain process parameters. In this article, we aim to improve the shape fidelity of AM products through compensation, with the information on these parameters. To achieve this, a two-step hierarchical scheme is proposed to predict the in-plane deviation of the product shape, which relates to the process parameters and the two-dimensional input shape. Based on this prediction procedure, a shape compensation strategy is developed that greatly improves the dimensional accuracy of products. Experimental studies of fused deposition modeling processes validate the effectiveness of our proposed scheme in terms of both predicting the shape deviation and improving the shape accuracy.

Original languageEnglish (US)
Pages (from-to)394-406
Number of pages13
JournalIISE Transactions
Volume50
Issue number5
DOIs
StatePublished - May 4 2018
Externally publishedYes

Keywords

  • Additive manufacturing
  • Gaussian process model
  • in-plane shape deviation
  • kernel smoothing

ASJC Scopus subject areas

  • Industrial and Manufacturing Engineering

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