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Considerations and Recommendations for Data Availability for Data Analytics for Manufacturing

Published

Author(s)

Donald E. Libes, Seungjun Shin, Jungyub Woo

Abstract

Data analytics is increasingly becoming recognized as a valuable set of tools and techniques for improving performance in the manufacturing enterprise. However, data analytics requires data and a lack of useful and usable data has become an impediment to research in data analytics. In this paper, we describe issues that would help aid data availability including data quality, reliability, efficiency, and formats specific to data analytics in manufacturing. To encourage data availability, we present recommendations and requirements to guide future data contributions. We also describe the need for data for challenge problems in data analytics. A better understanding of these needs, recommendations, and requirements may improve the ability of researchers and other practitioners to improve research and more rapidly deploy data analytics in manufacturing.
Proceedings Title
2015 IEEE International Conference on Big Data (IEEE Big Data 2015) Proceedings
Conference Dates
October 29-November 1, 2015
Conference Location
Santa Clara, CA
Conference Title
2015 IEEE International Conference on Big Data (IEEE Big Data 2015)

Keywords

Keywords: big data, challenge problems, data analytics, data quality, requirements, smart manufacturing

Citation

Libes, D. , Shin, S. and Woo, J. (2015), Considerations and Recommendations for Data Availability for Data Analytics for Manufacturing, 2015 IEEE International Conference on Big Data (IEEE Big Data 2015) Proceedings, Santa Clara, CA, [online], https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=918991 (Accessed July 19, 2024)

Issues

If you have any questions about this publication or are having problems accessing it, please contact reflib@nist.gov.

Created October 29, 2015, Updated April 25, 2018