Optimizing Condition Monitoring of Big Data Systems

David Baglee, Unai Gorostegui, Erkki Jantunen, Jaime Campos, Pankaj Sharma

Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingsScientificpeer-review

Abstract

Industrial communication networks are common in a number of manufacturing organisations. The high availability of these networks is crucial for smooth plant operations. Therefore local and remote diagnostics of these networks is of primary importance in determining issues relating to plant reliability and availability. Condition Monitoring (CM) techniques when connected to a network provide a diagnostic system for remote monitoring of manufacturing equipment. The system monitors the health of the network and the equipment and is therefore able to predict performance. However, this leads to the collection, storage and analyses of large amounts of data, which must provide value. These large data sets are commonly referred to as Big Data. This paper presents a general concept of the use of condition monitoring and big data systems to show how they complement each other to provide valuable data to enhance manufacturing competiveness.
Original languageEnglish
Title of host publicationProceedings of the 2017 International Conference on Data Mining DMIN'17
EditorsRobert Stahlbock, Mahmoud Abou-Nasr, Gary M. Weiss
PublisherCSREA Press
Pages127-131
Number of pages5
ISBN (Electronic)1-60132-453-7
Publication statusPublished - 17 Jul 2017
MoE publication typeA4 Article in a conference publication
Event13th International Conference on Data Mining, DMIN'17 - Las Vegas, United States
Duration: 17 Jul 201720 Jul 2017
https://csce.ucmss.com/cr/books/2017/ConferenceReport?ConferenceKey=DMI (Full proceedings)

Conference

Conference13th International Conference on Data Mining, DMIN'17
Abbreviated titleDMIN 2017
CountryUnited States
CityLas Vegas
Period17/07/1720/07/17
OtherDMIN-17 is a part of the World Congress in Computer Science Computer Engineering & Applied Computing CSCE'17
Internet address

Fingerprint

Condition monitoring
Availability
Telecommunication networks
Health
Monitoring
Big data

Cite this

Baglee, D., Gorostegui, U., Jantunen, E., Campos, J., & Sharma, P. (2017). Optimizing Condition Monitoring of Big Data Systems. In R. Stahlbock, M. Abou-Nasr, & G. M. Weiss (Eds.), Proceedings of the 2017 International Conference on Data Mining DMIN'17 (pp. 127-131). CSREA Press.
Baglee, David ; Gorostegui, Unai ; Jantunen, Erkki ; Campos, Jaime ; Sharma, Pankaj. / Optimizing Condition Monitoring of Big Data Systems. Proceedings of the 2017 International Conference on Data Mining DMIN'17. editor / Robert Stahlbock ; Mahmoud Abou-Nasr ; Gary M. Weiss. CSREA Press, 2017. pp. 127-131
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Baglee, D, Gorostegui, U, Jantunen, E, Campos, J & Sharma, P 2017, Optimizing Condition Monitoring of Big Data Systems. in R Stahlbock, M Abou-Nasr & GM Weiss (eds), Proceedings of the 2017 International Conference on Data Mining DMIN'17. CSREA Press, pp. 127-131, 13th International Conference on Data Mining, DMIN'17, Las Vegas, United States, 17/07/17.

Optimizing Condition Monitoring of Big Data Systems. / Baglee, David; Gorostegui, Unai; Jantunen, Erkki; Campos, Jaime; Sharma, Pankaj.

Proceedings of the 2017 International Conference on Data Mining DMIN'17. ed. / Robert Stahlbock; Mahmoud Abou-Nasr; Gary M. Weiss. CSREA Press, 2017. p. 127-131.

Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingsScientificpeer-review

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N2 - Industrial communication networks are common in a number of manufacturing organisations. The high availability of these networks is crucial for smooth plant operations. Therefore local and remote diagnostics of these networks is of primary importance in determining issues relating to plant reliability and availability. Condition Monitoring (CM) techniques when connected to a network provide a diagnostic system for remote monitoring of manufacturing equipment. The system monitors the health of the network and the equipment and is therefore able to predict performance. However, this leads to the collection, storage and analyses of large amounts of data, which must provide value. These large data sets are commonly referred to as Big Data. This paper presents a general concept of the use of condition monitoring and big data systems to show how they complement each other to provide valuable data to enhance manufacturing competiveness.

AB - Industrial communication networks are common in a number of manufacturing organisations. The high availability of these networks is crucial for smooth plant operations. Therefore local and remote diagnostics of these networks is of primary importance in determining issues relating to plant reliability and availability. Condition Monitoring (CM) techniques when connected to a network provide a diagnostic system for remote monitoring of manufacturing equipment. The system monitors the health of the network and the equipment and is therefore able to predict performance. However, this leads to the collection, storage and analyses of large amounts of data, which must provide value. These large data sets are commonly referred to as Big Data. This paper presents a general concept of the use of condition monitoring and big data systems to show how they complement each other to provide valuable data to enhance manufacturing competiveness.

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Baglee D, Gorostegui U, Jantunen E, Campos J, Sharma P. Optimizing Condition Monitoring of Big Data Systems. In Stahlbock R, Abou-Nasr M, Weiss GM, editors, Proceedings of the 2017 International Conference on Data Mining DMIN'17. CSREA Press. 2017. p. 127-131