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University of Illinois at Urbana-Champaign
Machine-learning-based measurement, modeling, and control of spatial variability in advanced manufacturing
Abstract
dc:descriptionSubmission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2024-05-01
Degree
thesis:*- Name thesis:degree_name
- Ph.D.
- Level thesis:degree_level
- Dissertation
- Discipline thesis:degree_discipline
- Mechanical Engineering
- Grantor
- University of Illinois at Urbana-Champaign
- Year dc:date
- 2022
Author and committee
dc:creator, dc:contributor.*- Author dc:creator
-
- Yang, Yuhang
- Contributors dc:contributor
-
- Shao, Chenhui
- Ferreira, Placid M
- King, William P
- Wang, Pingfeng
Subjects
dc:subject × 16- Machine learning
- Spatial process
- Spatiotemporal process
- Gaussian process
- Surface measurement
- Sampling design
- Measurement strategy
- Big data analytics
- Data fusion
- Smart manufacturing
- Advanced manufacturing
- Additive manufacturing
- Quality control
- Hierarchical modeling
- Data-efficient learning
- Intelligent metrology
Rights
dc:rights- Statement dc:rights
-
- Copyright 2021 Yuhang Yang
- Language dc:language
- en, eng
Identifiers
dc:identifier.*- Handle dc:identifier
- https://hdl.handle.net/2142/115503
- OAI identifier oai:identifier
- oai:www.ideals.illinois.edu:2142/115503