Variation Analysis and Visualization of Manufacturing Processes via Augmented Reality

In manufacturing processes and systems, many production and quality control decisions cannot be made in a timely manner due to the time delay for data collection, pre-processing and analysis. In this invention, we propose an online variation analysis and visualization method via augmented reality (AR) to operators. A regularized functional logistic regression model is constructed to predict a binary product quality indicator based on continuously measured process variables. This model is integrated with the AR platform, which provides not only the on-site visualization of raw data sets from manufacturing, but also useful information for decision support in variation reduction. The proposed method has been validated in a case study of quality prediction in an additive manufacturing process.

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For Information, Contact:
Li Chen
Licensing Associate
Virginia Tech Intellectual Properties, Inc.
(540) 443-9217
Ran Jin
Xiaoyu Chen