Advantages of Multiscale Detection of Defective Pills during Manufacturing
Type
Book ChapterAuthors
Douglas, Craig C.Deng, Li
Efendiev, Yalchin R.

Haase, Gundolf
Kucher, Andreas
Lodder, Robert
Qin, Guan
KAUST Grant Number
KUS-C1-016-04Date
2010Permanent link to this record
http://hdl.handle.net/10754/597475
Metadata
Show full item recordAbstract
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. © 2010 Springer-Verlag.Citation
Douglas CC, Deng L, Efendiev Y, Haase G, Kucher A, et al. (2010) Advantages of Multiscale Detection of Defective Pills during Manufacturing. High Performance Computing and Applications: 8–16. Available: http://dx.doi.org/10.1007/978-3-642-11842-5_2.Sponsors
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).Publisher
Springer Natureae974a485f413a2113503eed53cd6c53
10.1007/978-3-642-11842-5_2