TY - JOUR
T1 - On assessing spatial uniformity of particle distributions in quality control of manufacturing processes
AU - Kam, Kin Ming
AU - Zeng, Li
AU - Zhou, Qiang
AU - Tran, Richard
AU - Yang, Jian
N1 - Funding Information:
Jian Yang is an Associate Professor of Bioengineering at the University of Texas at Arlington. He received his Ph.D. from the Institute of Chemistry at the Chinese Academy of Sciences in Beijing, and has been a postdoctoral research fellow in the Biomedical Engineering Department at Northwestern University. His research interests are polymer synthesis and characterization, cell scaffold fabrication and tissue engineering. His research is sponsored by National Science Foundation, National Institutes of Health, American heart Association, etc. He is a recipient of the CAREER Award from NSF in 2010.
PY - 2013/1
Y1 - 2013/1
N2 - There are many situations in quality control of manufacturing processes in which the quality of a process is characterized by the spatial distribution of certain particles in the product, and the more uniform the particle distribution is, the better the quality is. To realize quality control and guide process improvement efforts, the degree of spatial uniformity of particle distributions needs to be assessed. On the other hand, many quantitative metrics have been developed in areas outside manufacturing for measuring uniformity of point patterns, which can be applied for this purpose. However, critical issues exist in applying existing metrics for quality control relating to which metrics to choose and how to use them in specific situations. To provide general guidelines on these issues, this research identifies popular uniformity metrics scattered in different areas and compares their performance in detecting nonuniform particle distributions under various practical scenarios through a comprehensive numerical study. Effects of different factors on the performance of the metrics are revealed and the best metric is found. The use and effectiveness of the selected metric is also demonstrated in a case study where it is applied to data from emerging material fabrication processes in nanomanufacturing and biomanufacturing.
AB - There are many situations in quality control of manufacturing processes in which the quality of a process is characterized by the spatial distribution of certain particles in the product, and the more uniform the particle distribution is, the better the quality is. To realize quality control and guide process improvement efforts, the degree of spatial uniformity of particle distributions needs to be assessed. On the other hand, many quantitative metrics have been developed in areas outside manufacturing for measuring uniformity of point patterns, which can be applied for this purpose. However, critical issues exist in applying existing metrics for quality control relating to which metrics to choose and how to use them in specific situations. To provide general guidelines on these issues, this research identifies popular uniformity metrics scattered in different areas and compares their performance in detecting nonuniform particle distributions under various practical scenarios through a comprehensive numerical study. Effects of different factors on the performance of the metrics are revealed and the best metric is found. The use and effectiveness of the selected metric is also demonstrated in a case study where it is applied to data from emerging material fabrication processes in nanomanufacturing and biomanufacturing.
KW - Complete spatial randomness (CSR)
KW - Metal matrix nanocomposite (MMNC)
KW - Particle distribution
KW - Point patterns
KW - Spatial uniformity
KW - Tissue-engineered scaffolds
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U2 - 10.1016/j.jmsy.2012.07.018
DO - 10.1016/j.jmsy.2012.07.018
M3 - Article
AN - SCOPUS:84903552950
SN - 0278-6125
VL - 32
SP - 154
JO - Journal of Manufacturing Systems
JF - Journal of Manufacturing Systems
IS - 1
ER -