Gauge capability studies for high-density data: SPC Phase 0
Author(s) -
Romina Dastoorian,
Lee J. Wells
Publication year - 2020
Publication title -
procedia manufacturing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.504
H-Index - 43
ISSN - 2351-9789
DOI - 10.1016/j.promfg.2020.05.026
Subject(s) - point cloud , statistical process control , repeatability , computer science , laser scanning , system of measurement , data mining , laser , reliability engineering , process (computing) , engineering , statistics , mathematics , artificial intelligence , physics , optics , astronomy , operating system
In manufacturing, advanced measurement systems (e.g., 3D laser scanners) are continually being incorporated into modern quality control (QC) systems to provide high-density (HD) data. A significant amount of research efforts has been placed in the development of QC tools, such as Phase I and II statistical process control (SPC) approaches using HD data. However, the effectiveness of SPC tools highly depends on measurement system adequacy. The study of the quality and adequacy of a measurement system, known as measurement capability or Phase 0 in SPC applications, is a prerequisite to implementing any SPC tool; which has mostly been neglected for HD data. This paper proposes a holistic Gauge study approach for HD data obtained from 3D laser scanners (e.g. point clouds) by using spatial statistics data models. The main objectives of this work are two-fold: 1) Study how to analyse the repeatability and reproducibility of a point cloud and 2) Quantify the uncertainty associated with a point cloud under different factors involved in acquiring point clouds from 3D laser scanners.
Accelerating Research
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom
Address
John Eccles HouseRobert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom