A hybrid transfer learning framework for in-plane freeform shape accuracy control in additive manufacturing
Author:
Affiliation:
1. Department of Industrial Engineering and Decision Analytics, Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong
2. School of Management, Xi’an Jiaotong University, Xi’an, China
Funder
National Natural Science Foundation of China
Hong Kong RGC General Research Funds
Hong Kong Innovation and Technology Fund Postdoctoral Hub Programme
Hong Kong Innovation and Technology Fund Project
Publisher
Informa UK Limited
Subject
Industrial and Manufacturing Engineering
Link
https://www.tandfonline.com/doi/pdf/10.1080/24725854.2020.1741741
Reference30 articles.
1. A Statistical Transfer Learning Perspective for Modeling Shape Deviations in Additive Manufacturing
2. A prediction and compensation scheme for in-plane shape deviation of additive manufacturing with information on process parameters
3. Opportunities and challenges of quality engineering for additive manufacturing
4. Circle fitting by linear and nonlinear least squares
5. Two-step estimation of functional linear models with applications to longitudinal data
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