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

S. Salunkhe, G. Kanagachidambaresan, C. Rajkumar, K. Jayanthi
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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.
基于人工智能的熔融沉积模型零件在线检测与预测
熔融沉积建模(FDM)是一种通过熔融挤压工艺将加热的塑料长丝按给定的图案进行长丝沉积的技术。分层是FDM极其复杂的零件的一个关键问题。在本章中,人工智能(机器学习)模型被用于FDM零件的在线检测和预测。提出的机器学习和卷积神经网络模型能够在线检测FDM零件的分层。所提出的模型也可以应用于不同类型的增材制造材料,而人工交互较少。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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