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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Libes, D. Seungjun Shin Jungyub Woo |
| Copyright Year | 2015 |
| Description | Author affiliation: Eng. Lab., Nat. Inst. of Stand. & Technol., Gaithersburg, MD, USA (Libes, D.; 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. |
| Starting Page | 68 |
| Ending Page | 75 |
| File Size | 535105 |
| Page Count | 8 |
| File Format | |
| e-ISBN | 9781479999262 |
| DOI | 10.1109/BigData.2015.7363743 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2015-10-29 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Data analysis Challenge problems NIST Big data Data analytics Data quality Manufacturing Sensors Encryption Synchronization Requirements Smart manufacturing |
| Content Type | Text |
| Resource Type | Article |
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