Enhancing Material Removal Rate Prediction on Wafer Surface: A PSO-DBN-OSELM Approach-Reference-Cited by-同舟云学术

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Enhancing Material Removal Rate Prediction on Wafer Surface: A PSO-DBN-OSELM Approach

Published:2023-12-22 Issue: Volume: Page:135-141
ISSN:
Container-title:2023 2nd International Conference on Advanced Sensing, Intelligent Manufacturing (ASIM)
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Author:

Zhan Tongjie¹,Liu Lisha¹,Liu Runlong²,Huang Erzhuo³,He Zixing¹,Chen Haowen⁴,Zhang Qian⁵

Affiliation:

1. Hunan University,School of Electrical and Information Engineering,Changsha,China

2. Shanghai Jiao Tong University,College of Smart Energy,Shanghai,China

3. Wuhan University,School of Urban Design,Wuhan,China

4. Hunan University,College of Computer Science and Electronic Engineering,Changsha,China

5. Hunan Zoomlion Intelligent Technology Co., Ltd,Changsha,China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10516323/10516326/10516508.pdf?arnumber=10516508

Reference14 articles.

1. Review on modeling and application of chemical mechanical polishing

2. Development of a capacity analysis and planning simulation model for semiconductor fabrication

3. Effects of Chemical-Electrical and Mechanical Parameters on Electrical-induced Chemical Mechanical Polishing of GaN

4. Analytical Modelling of Material Removal in Copper Chemical Mechanical Polishing Incorporating the Scratch Hardness of the Passivated Layer on Copper Thin Film Wafer

5. Prediction of the surface roughness and material removal rate in chemical mechanical polishing of single-crystal SiC via a back-propagation neural network

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