Welcome to the InfoSci Platform
Online Detection and Prediction of Fused Deposition Modelled Parts Using Artificial Intelligence

Online Detection and Prediction of Fused Deposition Modelled Parts Using Artificial Intelligence

Sachin Salunkhe, G. Kanagachidambaresan, C. Rajkumar, K. Jayanthi
Copyright: © 2022 |Pages: 16
ISBN13: 9781799885160|ISBN10: 179988516X|ISBN13 Softcover: 9781799885177|EISBN13: 9781799885184
DOI: 10.4018/978-1-7998-8516-0.ch009
Cite Chapter Cite Chapter

MLA

Salunkhe, Sachin, et al. "Online Detection and Prediction of Fused Deposition Modelled Parts Using Artificial Intelligence." Applications of Artificial Intelligence in Additive Manufacturing, edited by Sachin Salunkhe, et al., IGI Global, 2022, pp. 194-209. https://doi.org/10.4018/978-1-7998-8516-0.ch009

APA

Salunkhe, S., Kanagachidambaresan, G., Rajkumar, C., & Jayanthi, K. (2022). Online Detection and Prediction of Fused Deposition Modelled Parts Using Artificial Intelligence. In S. Salunkhe, H. Hussein, & J. Davim (Eds.), Applications of Artificial Intelligence in Additive Manufacturing (pp. 194-209). IGI Global. https://doi.org/10.4018/978-1-7998-8516-0.ch009

Chicago

Salunkhe, Sachin, et al. "Online Detection and Prediction of Fused Deposition Modelled Parts Using Artificial Intelligence." In Applications of Artificial Intelligence in Additive Manufacturing, edited by Sachin Salunkhe, Hussein Mohammed Abdel Moneam Hussein, and J. Paulo Davim, 194-209. Hershey, PA: IGI Global, 2022. https://doi.org/10.4018/978-1-7998-8516-0.ch009

Export Reference

Mendeley
Favorite

Abstract

Fused deposition modelling (FDM) is a technology used for filament deposition of heated plastic filaments by a given pattern by the melted extrusion process. Delamination is a critical issue of FDM's incredibly complex parts. In this chapter, the artificial intelligence (machine learning) model is used for online detections and prediction of FDM parts. The proposed machine learning and convolutional neural network model is capable of online detect delamination of FDM parts. The proposed model can also be applied for different types of additive manufacturing materials with less human interaction.

Request Access

You do not own this content. Please login to recommend this title to your institution's librarian or purchase it from the IGI Global bookstore.