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Article

Extracting Value from Industrial Alarms and Events: A Data-Driven Approach Based on Exploratory Data Analysis

1
Postgraduate Program in Electrical and Computer Engineering, Federal University of Rio Grande do Norte, Natal 59078-970, Rio Grande do Norte, Brazil
2
Digital Metropolis Institute, Federal University of Rio Grande do Norte, Natal 59078-970, Rio Grande do Norte, Brazil
3
School of Sciences and Technology, Federal University of Rio Grande do Norte, Natal 59078-970, Rio Grande do Norte, Brazil
4
Petróleo Brasileiro S.A., Rio de Janeiro 21941-915, Brazil
*
Author to whom correspondence should be addressed.
Sensors 2019, 19(12), 2772; https://doi.org/10.3390/s19122772
Received: 15 March 2019 / Revised: 25 April 2019 / Accepted: 1 May 2019 / Published: 20 June 2019
(This article belongs to the Special Issue Data Science and Internet of Everything (IoE))
Alarm and event logs are an immense but latent source of knowledge commonly undervalued in industry. Though, the current massive data-exchange, high efficiency and strong competitiveness landscape, boosted by Industry 4.0 and IIoT (Industrial Internet of Things) paradigms, does not accommodate such a data misuse and demands more incisive approaches when analyzing industrial data. Advances in Data Science and Big Data (or more precisely, Industrial Big Data) have been enabling novel approaches in data analysis which can be great allies in extracting hitherto hidden information from plant operation data. Coping with that, this work proposes the use of Exploratory Data Analysis (EDA) as a promising data-driven approach to pave industrial alarm and event analysis. This approach proved to be fully able to increase industrial perception by extracting insights and valuable information from real-world industrial data without making prior assumptions. View Full-Text
Keywords: alarm and event management; data science; exploratory data analysis; industry 4.0; monitoring alarm and event management; data science; exploratory data analysis; industry 4.0; monitoring
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MDPI and ACS Style

Bezerra, A.; Silva, I.; Guedes, L.A.; Silva, D.; Leitão, G.; Saito, K. Extracting Value from Industrial Alarms and Events: A Data-Driven Approach Based on Exploratory Data Analysis. Sensors 2019, 19, 2772. https://doi.org/10.3390/s19122772

AMA Style

Bezerra A, Silva I, Guedes LA, Silva D, Leitão G, Saito K. Extracting Value from Industrial Alarms and Events: A Data-Driven Approach Based on Exploratory Data Analysis. Sensors. 2019; 19(12):2772. https://doi.org/10.3390/s19122772

Chicago/Turabian Style

Bezerra, Aguinaldo, Ivanovitch Silva, Luiz A. Guedes, Diego Silva, Gustavo Leitão, and Kaku Saito. 2019. "Extracting Value from Industrial Alarms and Events: A Data-Driven Approach Based on Exploratory Data Analysis" Sensors 19, no. 12: 2772. https://doi.org/10.3390/s19122772

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