LIMS DATA COLLECTION AND ANALYSIS FOR MACHINING MONITORING

Tobechukwu D. Nwabueze; Nat Frampton; Christopher Tyler; Jaydeep Karandikar; Tony Schmitz

LIMS DATA COLLECTION AND ANALYSIS FOR MACHINING MONITORING

Tobechukwu D. Nwabueze, Nat Frampton, Christopher Tyler, Jaydeep Karandikar, Tony Schmitz

Advanced Machining and Machine Tools Res

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

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
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

Conference

Conference	37th Annual Meeting of the American Society for Precision Engineering, ASPE 2022
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).

Funders	Funder number
U.S. Department of Energy

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Cite this

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title = "LIMS DATA COLLECTION AND ANALYSIS FOR MACHINING MONITORING",

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.",

author = "Nwabueze, {Tobechukwu D.} and Nat Frampton and Christopher Tyler and Jaydeep Karandikar and Tony Schmitz",

note = "Publisher Copyright: {\textcopyright} 2022 Proceedings - ASPE 2022 Annual Meeting. All right reserved.; 37th Annual Meeting of the American Society for Precision Engineering, ASPE 2022 ; Conference date: 10-10-2022 Through 14-10-2022",

year = "2022",

language = "English",

series = "Proceedings - ASPE 2022 Annual Meeting",

publisher = "American Society for Precision Engineering, ASPE",

pages = "339--342",

booktitle = "Proceedings - ASPE 2022 Annual Meeting",

}

Nwabueze, TD, Frampton, N, Tyler, C, Karandikar, J & Schmitz, T 2022, LIMS DATA COLLECTION AND ANALYSIS FOR MACHINING MONITORING. in Proceedings - ASPE 2022 Annual Meeting. Proceedings - ASPE 2022 Annual Meeting, American Society for Precision Engineering, ASPE, pp. 339-342, 37th Annual Meeting of the American Society for Precision Engineering, ASPE 2022, Bellevue, United States, 10/10/22.

LIMS DATA COLLECTION AND ANALYSIS FOR MACHINING MONITORING. / Nwabueze, Tobechukwu D.; Frampton, Nat; Tyler, Christopher et al.
Proceedings - ASPE 2022 Annual Meeting. American Society for Precision Engineering, ASPE, 2022. p. 339-342 (Proceedings - ASPE 2022 Annual Meeting).

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

TY - GEN

T1 - LIMS DATA COLLECTION AND ANALYSIS FOR MACHINING MONITORING

AU - Nwabueze, Tobechukwu D.

AU - Frampton, Nat

AU - Tyler, Christopher

AU - Karandikar, Jaydeep

AU - Schmitz, Tony

PY - 2022

Y1 - 2022

N2 - 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.

AB - 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.

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M3 - Conference contribution

AN - SCOPUS:85146217119

T3 - Proceedings - ASPE 2022 Annual Meeting

SP - 339

EP - 342

BT - Proceedings - ASPE 2022 Annual Meeting

PB - American Society for Precision Engineering, ASPE

T2 - 37th Annual Meeting of the American Society for Precision Engineering, ASPE 2022

Y2 - 10 October 2022 through 14 October 2022

ER -

LIMS DATA COLLECTION AND ANALYSIS FOR MACHINING MONITORING

Abstract

Publication series

Conference

Funding

UN SDGs

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