An Automated Machine Learning Approach to Inkjet Printed Component Analysis: A Step Toward Smart Additive Manufacturing

arXiv:2404.04623v1 Announce Type: new
Abstract: In this paper, we present a machine learning based architecture for microwave characterization of inkjet printed components on flexible substrates. Our proposed architecture uses several machine learning algorithms and automatically selects the best algorithm to extract the material parameters (ink conductivity and dielectric properties) from on-wafer measurements. Initially, the mutual dependence between material parameters of the inkjet printed coplanar waveguides (CPWs) and EM-simulated propagation constants is utilized to train the machine learning models. Next, these …

abstract additive manufacturing algorithm algorithms analysis architecture arxiv automated automated machine learning components cs.et cs.lg extract machine machine learning machine learning algorithms manufacturing material paper parameters smart type