TY - GEN
T1 - Advantages of multiscale detection of defective pills during manufacturing
AU - Douglas, Craig C.
AU - Deng, Li
AU - Efendiev, Yalchin
AU - Haase, Gundolf
AU - Kucher, Andreas
AU - Lodder, Robert
AU - Qin, Guan
N1 - KAUST Repository Item: Exported on 2020-04-23
Acknowledged KAUST grant number(s): KUS-C1-016-04
Acknowledgements: This research was supported in part by NSF grants OISE-0405349, ACI-0305466, CNS-0719626, and ACI-0324876, DOE grant DE-FC26-08NT4, and Award No. KUS-C1-016-04, made by King Abdullah University of Science and Technology (KAUST).
This publication acknowledges KAUST support, but has no KAUST affiliated authors.
PY - 2010
Y1 - 2010
N2 - We explore methods to automatically detect the quality in individual or batches of pharmaceutical products as they are manufactured. The goal is to detect 100% of the defects, not just statistically sample a small percentage of the products and draw conclusions that may not be 100% accurate. Removing all of the defective products, or halting production in extreme cases, will reduce costs and eliminate embarrassing and expensive recalls. We use the knowledge that experts have accumulated over many years, dynamic data derived from networks of smart sensors using both audio and chemical spectral signatures, multiple scales to look at individual products and larger quantities of products, and finally adaptive models and algorithms.
AB - We explore methods to automatically detect the quality in individual or batches of pharmaceutical products as they are manufactured. The goal is to detect 100% of the defects, not just statistically sample a small percentage of the products and draw conclusions that may not be 100% accurate. Removing all of the defective products, or halting production in extreme cases, will reduce costs and eliminate embarrassing and expensive recalls. We use the knowledge that experts have accumulated over many years, dynamic data derived from networks of smart sensors using both audio and chemical spectral signatures, multiple scales to look at individual products and larger quantities of products, and finally adaptive models and algorithms.
KW - DDDAS
KW - Dynamic data-driven application systems
KW - High performance computing
KW - Integrated sensing and processing
KW - Manufacturing defect detection
KW - Parallel algorithms
UR - http://www.scopus.com/inward/record.url?scp=77951524689&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-11842-5_2
DO - 10.1007/978-3-642-11842-5_2
M3 - Conference contribution
AN - SCOPUS:77951524689
SN - 3642118410
SN - 9783642118418
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 8
EP - 16
BT - High Performance Computing and Applications - Second International Conference, HPCA 2009, Revised Selected Papers
T2 - 2nd International Conference on High-Performance Computing and Applications, HPCA 2009
Y2 - 10 August 2009 through 12 August 2009
ER -