TY - JOUR
T1 - Real-Time Multiscale Detection of Defective Pills During Manufacturing
AU - Douglas , C. C.
AU - Deng , L.
AU - Efendiev , Y.
AU - Haase , G.
AU - Kucher , A.
AU - Lodder , R. A.
JO - International Journal of Numerical Analysis and Modeling
VL - 2
SP - 169
EP - 180
PY - 2012
DA - 2012/09
SN - 9
DO - http://doi.org/
UR - https://global-sci.org/intro/article_detail/ijnam/618.html
KW - Manufacturing defect detection, dynamic data-driven application systems, DDDAS and integrated sensing and processing, high performance computing, and parallel algorithms.
AB - <p style="text-align: justify;">We explore methods to automatically detect the quality in individual or batches of
pharmaceutical products as they are manufactures. 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.</p>