REAL-TIME MULTISCALE DETECTION OF DEFECTIVE PILLS DURING MANUFACTURING Academic Article

abstract

• 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. 2012 Institute for Scientific Computing and Information.

authors

• Efendiev, Yalchin

published proceedings

• INTERNATIONAL JOURNAL OF NUMERICAL ANALYSIS AND MODELING

author list (cited authors)

• Douglas, C. C., Deng, L. i., Efendiev, Y., Haase, G., Kucher, A., & Lodder, R. A.

complete list of authors

• Douglas, Craig C||Deng, Li||Efendiev, Yalchin||Haase, Gunfolf||Kucher, Anfread||Lodder, Robert A

publication date

• June 2012

published in

• INTERNATIONAL JOURNAL OF NUMERICAL ANALYSIS AND MODELING  Journal

keywords

• And Parallel Algorithms
• Dddas And Integrated Sensing And Processing
• Dynamic Data-driven Application Systems
• High Performance Computing
• Manufacturing Defect Detection

start page

• 169

end page

• 180

volume

• 9

issue

• 2