التفاصيل البيبلوغرافية
| العنوان: |
Industrial statistics and manifold data. |
| المؤلفون: |
del Castillo, Enrique1 (AUTHOR) exd13@psu.edu, Zhao, Xueqi1 (AUTHOR) |
| المصدر: |
Quality Engineering. 2020, Vol. 32 Issue 2, p155-167. 13p. |
| مصطلحات موضوعية: |
*INDUSTRIAL statistics, *DATABASES, *BIG data, *STATISTICAL process control, POINT processes, POINT cloud |
| مستخلص: |
Complex and not only big data exist everywhere in industry and how to control and optimize systems based on these data types is an important aspect of modern Quality Engineering. One fundamental type of complexity occurs when data lies on a lower dimensional, curved subspace or manifold. We review a new approach for statistical process monitoring of point cloud, mesh and voxel data based on intrinsic geometrical features of the 2-D manifold (surfaces) of scanned manufactured parts. Monitoring intrinsic properties avoids computationally expensive registration pre-processing of the data sets. We also present a review of recent approaches for analyzing and designing experiments where either the response or the covariates lie on manifolds. [ABSTRACT FROM AUTHOR] |
|
Copyright of Quality Engineering is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) |
| قاعدة البيانات: |
Business Source Index |