Advantages of multiscale detection of defective pills during manufacturing

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

doi:10.1007/978-3-642-11842-5_2

Advantages of multiscale detection of defective pills during manufacturing

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

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

5 Scopus citations

Abstract

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.

Original language	English (US)
Title of host publication	High Performance Computing and Applications - Second International Conference, HPCA 2009, Revised Selected Papers
Pages	8-16
Number of pages	9
DOIs	https://doi.org/10.1007/978-3-642-11842-5_2
State	Published - 2010
Externally published	Yes
Event	2nd International Conference on High-Performance Computing and Applications, HPCA 2009 - Shanghai, China Duration: Aug 10 2009 → Aug 12 2009

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	5938 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	2nd International Conference on High-Performance Computing and Applications, HPCA 2009
Country/Territory	China
City	Shanghai
Period	08/10/09 → 08/12/09

Bibliographical note

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.

Keywords

DDDAS
Dynamic data-driven application systems
High performance computing
Integrated sensing and processing
Manufacturing defect detection
Parallel algorithms

ASJC Scopus subject areas

Theoretical Computer Science
General Computer Science

Access to Document

10.1007/978-3-642-11842-5_2

Cite this

Douglas, C. C., Deng, L., Efendiev, Y., Haase, G., Kucher, A., Lodder, R., & Qin, G. (2010). Advantages of multiscale detection of defective pills during manufacturing. In High Performance Computing and Applications - Second International Conference, HPCA 2009, Revised Selected Papers (pp. 8-16). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5938 LNCS). https://doi.org/10.1007/978-3-642-11842-5_2

Douglas, Craig C. ; Deng, Li ; Efendiev, Yalchin et al. / Advantages of multiscale detection of defective pills during manufacturing. High Performance Computing and Applications - Second International Conference, HPCA 2009, Revised Selected Papers. 2010. pp. 8-16 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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title = "Advantages of multiscale detection of defective pills during manufacturing",

abstract = "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.",

keywords = "DDDAS, Dynamic data-driven application systems, High performance computing, Integrated sensing and processing, Manufacturing defect detection, Parallel algorithms",

author = "Douglas, {Craig C.} and Li Deng and Yalchin Efendiev and Gundolf Haase and Andreas Kucher and Robert Lodder and Guan Qin",

note = "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.; 2nd International Conference on High-Performance Computing and Applications, HPCA 2009 ; Conference date: 10-08-2009 Through 12-08-2009",

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Douglas, CC, Deng, L, Efendiev, Y, Haase, G, Kucher, A, Lodder, R & Qin, G 2010, Advantages of multiscale detection of defective pills during manufacturing. in High Performance Computing and Applications - Second International Conference, HPCA 2009, Revised Selected Papers. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 5938 LNCS, pp. 8-16, 2nd International Conference on High-Performance Computing and Applications, HPCA 2009, Shanghai, China, 08/10/09. https://doi.org/10.1007/978-3-642-11842-5_2

Advantages of multiscale detection of defective pills during manufacturing. / Douglas, Craig C.; Deng, Li; Efendiev, Yalchin et al.
High Performance Computing and Applications - Second International Conference, HPCA 2009, Revised Selected Papers. 2010. p. 8-16 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5938 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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Douglas CC, Deng L, Efendiev Y, Haase G, Kucher A, Lodder R et al. Advantages of multiscale detection of defective pills during manufacturing. In High Performance Computing and Applications - Second International Conference, HPCA 2009, Revised Selected Papers. 2010. p. 8-16. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-642-11842-5_2

Advantages of multiscale detection of defective pills during manufacturing

Abstract

Publication series

Conference

Bibliographical note

Keywords

ASJC Scopus subject areas

Access to Document

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