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Your search keyword '"Zhao, Changxuan"' showing total 11 results
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11 results on '"Zhao, Changxuan"'

2. Deep learning and sequence mining for manufacturing process and sequence selection.

Author

Zhao, Changxuan, Dinar, Mahmoud, and Melkote, Shreyes N.

Subjects
CONVOLUTIONAL neural networks, GRAPH neural networks, DEEP learning, MANUFACTURING processes, ARTIFICIAL neural networks
Abstract

Automatic determination of manufacturing process sequences for the physical production of given part designs is key to facilitate on-demand cyber manufacturing. In this work, we propose an integrated framework that (i) identifies manufacturing features from 3D part designs using a Graph Neural Network (GNN), (ii) identifies the manufacturing processes necessary to produce all features in the part using a Convolutional Neural Network (CNN) that considers shape, material properties, and quality information, and (iii) outputs an ordered manufacturing sequence that can produce the designed part with the help of sequence mining. Using these methods, the knowledge required to enable automated manufacturing process selection is easily scalable and updatable without requiring manual population of ad-hoc or rule-based descriptions. We present exemplar implementations of the proposed framework by suggesting manufacturing sequences for discrete parts with multiple features. The suggested manufacturing sequences demonstrate the potential of the proposed framework for use in future on-demand cyber manufacturing applications. [ABSTRACT FROM AUTHOR]

Published
2024
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11. Real Time Monitoring Of Exposure Controlled Projection Lithography

Author

Zhao, Changxuan, Jariwala, Amit S., Rosen, David W., School of Mechanical and Aerospace Engineering, Proceedings of the 2nd International Conference on Progress in Additive Manufacturing (Pro-AM 2016), and Singapore Centre for 3D Printing

Abstract

Exposure Controlled Projection Lithography (ECPL) is a stereolithographic process in which lens shaped features are fabricated from Photopolymer resin. During the fabrication process, a dynamic mask is used to control and project radiation patterns through a transparent substrate onto the photopolymer resin to grow the features progressively from the substrate surface. We present a novel method to monitor the photopolymerization process in real-time with spatial resolution in a plane perpendicular to the growth of polymerization. A transparent Spatial Light Modulator (SLM) was incorporated into our Interferometric Cure Monitoring (ICM) system, an interferometric monitoring system which is used to measure the cured part height. The introduction of SLM enabled multiple point which could not be achieved by the traditional manually operated iris. This improved ICM system fulfilled the need of selectively scanning the curing area and estimating the height and width of the cured part at a specific region of interest. This multiple-point-selective monitoring approach is experimentally validated to measure the height at different locations of the cured part in real time, and also the lateral dimensions of the cured part at the substrate level by a scanning process controlled by the SLM. Published version

Published
2016

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