Multi-sensor and MTConnect dataset of metal cutting anomaly in milling from laboratory and industry settings.
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| Title: | Multi-sensor and MTConnect dataset of metal cutting anomaly in milling from laboratory and industry settings. |
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| Authors: | Kim E; Elmore Family School of Electrical and Computer Engineering, Purdue University, West Lafayette, USA. kim3235@purdue.edu., Sim Y; School of Mechanical Engineering, Purdue University, West Lafayette, USA., Li AS; Department of Computer Science, Purdue University, West Lafayette, USA., Mostafiz MI; Department of Computer Science, Purdue University, West Lafayette, USA., Van Meter Z; TMF Center, Williamsport, USA., Jun MB; School of Mechanical Engineering, Purdue University, West Lafayette, USA., Bertino E; Department of Computer Science, Purdue University, West Lafayette, USA., Shakouri A; Elmore Family School of Electrical and Computer Engineering, Purdue University, West Lafayette, USA. |
| Source: | Scientific data [Sci Data] 2026 Apr 24; Vol. 13 (1). Date of Electronic Publication: 2026 Apr 24. |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: Nature Publishing Group Country of Publication: England NLM ID: 101640192 Publication Model: Electronic Cited Medium: Internet ISSN: 2052-4463 (Electronic) Linking ISSN: 20524463 NLM ISO Abbreviation: Sci Data Subsets: MEDLINE; PubMed not MEDLINE |
| Database: | MEDLINE Ultimate |
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