Abstract
This paper describes the use of a Learning Integrated Manufacturing System (LIMS) appliance for collecting operational data from manufacturing equipment and analyzing the data to monitor process performance. The aim is to optimize operations for the manufacturing facility. A Haas VF-4 CNC milling machine in the Machine Tool Research Center (MTRC) at the University of Tennessee, Knoxville serves as the machine and facility, respectively, for this case study.
| Original language | English |
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| Title of host publication | Proceedings - ASPE 2022 Annual Meeting |
| Publisher | American Society for Precision Engineering, ASPE |
| Pages | 339-342 |
| Number of pages | 4 |
| ISBN (Electronic) | 9781887706568 |
| State | Published - 2022 |
| Event | 37th Annual Meeting of the American Society for Precision Engineering, ASPE 2022 - Bellevue, United States Duration: Oct 10 2022 → Oct 14 2022 |
Publication series
| Name | Proceedings - ASPE 2022 Annual Meeting |
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Conference
| Conference | 37th Annual Meeting of the American Society for Precision Engineering, ASPE 2022 |
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| Country/Territory | United States |
| City | Bellevue |
| Period | 10/10/22 → 10/14/22 |
Funding
3 Notice: This manuscript has been authored by UT-Battelle, LLC, under contract DE-AC05-00OR22725 with the US Department of Energy (DOE). The US government retains and the publisher, by accepting the article for publication, acknowledges that the US government retains a nonexclusive, paid-up, irrevocable, worldwide license to publish or reproduce the published form of this manuscript, or allow others to do so, for US government purposes. DOE will provide public access to these results of federally sponsored research in accordance with the DOE Public Access Plan (http://energy.gov/downloads/doe-public-access-plan).