ENBIS: European Network for Business and Industrial Statistics

Bayesian Hierarchical Model for Integrating Multi-resolution Metrology Data

23 September 2008, 12:20 – 12:40

Abstract

Submitted by

Yu Ding

Authors

Heidi Xia, Yu Ding, and Bani Mallick

Affiliation

Texas A&M

Abstract

This article presents a Bayesian hierarchical model to integrate multi-resolution metrology data for inspecting geometry quality of manufactured parts. Our treatment includes using a Gaussian process for modeling metrology data at a single resolution level and establishing a linkage model to connect datasets at different resolutions. A unique problem in this metrology application is the misalignment between the low- and high-resolution datasets.
To address this issue, an optimization procedure is first employed to roughly align datasets of different resolutions and then a neighborhood linkage model is introduced to link a high-resolution data point with a group of low-resolution data points. Improvements are demonstrated using the datasets from a milled sine-wave part, measured by two coordinate measuring machines of different resolutions, respectively.

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