Statistical Process Control in Big Data Environment

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27360%2F20%3A10247098" target="_blank" >RIV/61989100:27360/20:10247098 - isvavai.cz</a>
Result on the web
<a href="https://ieeexplore.ieee.org/document/9257251" target="_blank" >https://ieeexplore.ieee.org/document/9257251</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/ICCC49264.2020.9257251" target="_blank" >10.1109/ICCC49264.2020.9257251</a>

Result language
angličtina
Original language name
Statistical Process Control in Big Data Environment
Original language description
Big data analysis tools are an inevitable part of instruments and methods for monitoring and predicting the longitudinal performance of the processes in the production systems of the future, based on the deep automatization and overall digitalization. From this point of view statistical process control (SPC) will continue to be very effective method for meeting these goals. But there must be done some modifications. This paper deals with such possible modifications of SPC. In the first part of the paper the stress is put on various methods that can be integrated into SPC to meet new challenges in collecting, analysing and interpreting data (control charts for high yield processes, multivariable approaches, profile monitoring, data mining tools including machine learning methods, nonparametric control charts). SW for the selected discussed methods is also mentioned. The second part of the paper is devoted to the nonparametric methods of SPC and to the methodology of their practical application. (C) 2020 IEEE.
Czech name
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Czech description
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Project
<a href="/en/project/EF17_049%2F0008425" target="_blank" >EF17_049/0008425: A Research Platform focused on Industry 4.0 and Robotics in Ostrava Agglomeration</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach

Publication year
2020
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
Proceedings of the 2020 21st International Carpathian Control Conference, ICCC 2020
ISBN
978-1-72811-952-6
ISSN
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e-ISSN
—
Number of pages
6
Pages from-to
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Publisher name
IEEE
Place of publication
Piscataway
Event location
Košice
Event date
Oct 27, 2020
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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