Organization of big metrology data within the Cyber-Physical Manufacturing Metrology Model (CPM3)
Samo za registrovane korisnike
2022
Autori
Sabbagh, R.Živković, Saša
Gawlik, B.
Sreenivasan, S.V.
Stothert, A.
Majstorović, Vidosav D.
Djurdjanović, Dragan
Članak u časopisu (Objavljena verzija)
Metapodaci
Prikaz svih podataka o dokumentuApstrakt
In this paper, we propose a novel data curation concept that enables data mining and analytics within the recently described Cyber-Physical Manufacturing Metrology Model (CPM3). The newly proposed methodology is based on organizing the metrology data into tree-based database structures using distance-based unsupervised clustering of the raw metrology data. Compared to traditionally utilized temporally organized lists, the new tree-based database organization of metrology data enables logarithmic acceleration of searches within the data and thus provides dramatic advantages for data mining. The newly proposed data curation methodology was evaluated in case studies involving hyper-spectral metrology of nanopatterned surfaces, coordinate measurement machine (CMM) inspection of aircraft engine turbines and imaging-based metrology of nano-volume droplets in the jet and fill stage of imprint lithography processes. Significant improvements in search speeds with minimal or no losses in search ...precision and recall were observed in all case-studies, with benefits of tree-based data organization growing with the size of the data.
Ključne reči:
Metrology / Industry 4.0 / Industrial internet of things / Cyber-Physical Manufacturing Systems / Big data management / Big data curationIzvor:
CIRP Journal of Manufacturing Science and Technology, 2022, 36, 90-99Izdavač:
- Elsevier Ltd
Finansiranje / projekti:
- This work was supported in part by the National Science Foundation (NSF) under Cooperative Agreement No. EEC-1160494
- This work is also supported in part by a donation from The MathWorks, Inc. to the University of Texas at Austin
Kolekcije
Institucija/grupa
Mašinski fakultetTY - JOUR AU - Sabbagh, R. AU - Živković, Saša AU - Gawlik, B. AU - Sreenivasan, S.V. AU - Stothert, A. AU - Majstorović, Vidosav D. AU - Djurdjanović, Dragan PY - 2022 UR - https://machinery.mas.bg.ac.rs/handle/123456789/3814 AB - In this paper, we propose a novel data curation concept that enables data mining and analytics within the recently described Cyber-Physical Manufacturing Metrology Model (CPM3). The newly proposed methodology is based on organizing the metrology data into tree-based database structures using distance-based unsupervised clustering of the raw metrology data. Compared to traditionally utilized temporally organized lists, the new tree-based database organization of metrology data enables logarithmic acceleration of searches within the data and thus provides dramatic advantages for data mining. The newly proposed data curation methodology was evaluated in case studies involving hyper-spectral metrology of nanopatterned surfaces, coordinate measurement machine (CMM) inspection of aircraft engine turbines and imaging-based metrology of nano-volume droplets in the jet and fill stage of imprint lithography processes. Significant improvements in search speeds with minimal or no losses in search precision and recall were observed in all case-studies, with benefits of tree-based data organization growing with the size of the data. PB - Elsevier Ltd T2 - CIRP Journal of Manufacturing Science and Technology T1 - Organization of big metrology data within the Cyber-Physical Manufacturing Metrology Model (CPM3) EP - 99 SP - 90 VL - 36 DO - 10.1016/j.cirpj.2021.10.009 ER -
@article{ author = "Sabbagh, R. and Živković, Saša and Gawlik, B. and Sreenivasan, S.V. and Stothert, A. and Majstorović, Vidosav D. and Djurdjanović, Dragan", year = "2022", abstract = "In this paper, we propose a novel data curation concept that enables data mining and analytics within the recently described Cyber-Physical Manufacturing Metrology Model (CPM3). The newly proposed methodology is based on organizing the metrology data into tree-based database structures using distance-based unsupervised clustering of the raw metrology data. Compared to traditionally utilized temporally organized lists, the new tree-based database organization of metrology data enables logarithmic acceleration of searches within the data and thus provides dramatic advantages for data mining. The newly proposed data curation methodology was evaluated in case studies involving hyper-spectral metrology of nanopatterned surfaces, coordinate measurement machine (CMM) inspection of aircraft engine turbines and imaging-based metrology of nano-volume droplets in the jet and fill stage of imprint lithography processes. Significant improvements in search speeds with minimal or no losses in search precision and recall were observed in all case-studies, with benefits of tree-based data organization growing with the size of the data.", publisher = "Elsevier Ltd", journal = "CIRP Journal of Manufacturing Science and Technology", title = "Organization of big metrology data within the Cyber-Physical Manufacturing Metrology Model (CPM3)", pages = "99-90", volume = "36", doi = "10.1016/j.cirpj.2021.10.009" }
Sabbagh, R., Živković, S., Gawlik, B., Sreenivasan, S.V., Stothert, A., Majstorović, V. D.,& Djurdjanović, D.. (2022). Organization of big metrology data within the Cyber-Physical Manufacturing Metrology Model (CPM3). in CIRP Journal of Manufacturing Science and Technology Elsevier Ltd., 36, 90-99. https://doi.org/10.1016/j.cirpj.2021.10.009
Sabbagh R, Živković S, Gawlik B, Sreenivasan S, Stothert A, Majstorović VD, Djurdjanović D. Organization of big metrology data within the Cyber-Physical Manufacturing Metrology Model (CPM3). in CIRP Journal of Manufacturing Science and Technology. 2022;36:90-99. doi:10.1016/j.cirpj.2021.10.009 .
Sabbagh, R., Živković, Saša, Gawlik, B., Sreenivasan, S.V., Stothert, A., Majstorović, Vidosav D., Djurdjanović, Dragan, "Organization of big metrology data within the Cyber-Physical Manufacturing Metrology Model (CPM3)" in CIRP Journal of Manufacturing Science and Technology, 36 (2022):90-99, https://doi.org/10.1016/j.cirpj.2021.10.009 . .