Advantages of Multiscale Detection of Defective Pills during Manufacturing

摘要：

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.

关键词： manufacturing defect detection dynamic data-driven application systems DDDAS integrated sensing and processing high performance computing and parallel algorithms

作者: Craig C. Douglas Li Deng Yalchin Efendiev Gundolf Haase Andreas Kucher Robert Lodder Guan Qin

作者单位: University of Wyoming Department of Mathematics, 1000 University Avenue, Dept. 3036,Laramie, WY 8207 JSOL Corporation, Chuo-ku, Tokyo 104-0053, Japan Texas A&M University, Mathematics Department, College Station, TX, USA Karl-Franzens University of Graz, Mathematics and Computational Sciences Department,A-8010 Graz, Aus Karl-Franzens University of Graz, Mathematics and Computational Sciences Department,A-8010 Graz,Aust University of Kentucky Chemistry Department,Lexington, KY 40506, USA University of Wyoming Department of Chemical and Petroleum Engineering, 1000 University Avenue, Dept

会议类型: 国际会议

会议名称: The Second International Conference on High Performance Computing and Applications(第二届高性能计算及应用国际会议)

会议地点: 上海

会议语种:英文

页码: 8-16

在线出版日期: 2009-08-10（万方平台首次上网日期，不代表论文的发表时间）