An Approach for Implementing ISA 95-Compliant Big Data Observation, Analysis and Diagnosis Features in Industry 4.0 Vision Following Manufacturing Systems

Kevin Nagorny; Sebastian Scholze; José Barata; Armando Walter Colombo

doi:10.1007/978-3-319-31165-4_12

An Approach for Implementing ISA 95-Compliant Big Data Observation, Analysis and Diagnosis Features in Industry 4.0 Vision Following Manufacturing Systems

Kevin Nagorny, Sebastian Scholze, José Barata, Armando Walter Colombo

Research output: Chapter in Book/Report/Conference proceeding › Chapter

3 Citations (Scopus)

Abstract

Current trends are showing a technological evolution to an unified Industrial Internet of Things network where smart manufacturing devices are loosely coupled over a cloud to realize comprehensive collaboration and analysis possibilities, and to increase the dynamic and volatile of manufacturing environments. This rising complexity generates also higher ranges of error possibilities and analog a growing demand of new diagnostic approaches to handle also those highly complex systems as manufacturing systems which are following the Industry 4.0 vision. This is an ISA’95 compliant approach of a Big Data analytics methodology for analysis and observation in Industry 4.0 vision following manufacturing systems.

Original language	English
Title of host publication	IFIP Advances in Information and Communication Technology
Editors	M. Luis Camarinha-Matos, António J. Falcão, Nazanin Vafaei, Shirin Najdi
Place of Publication	Cham
Publisher	SPRINGER INTERNATIONAL PUBLISHING AG
Pages	116-123
Number of pages	8
Volume	470
ISBN (Print)	978-3-319-31165-4
DOIs	https://doi.org/10.1007/978-3-319-31165-4_12
Publication status	Published - 2016
Event	7th IFIP WG 5.5/SOCOLNET Advanced Doctoral Conference on Computing, Electrical and Industrial Systems, DoCEIS 2016 - Costa de Caparica, Portugal Duration: 11 Apr 2016 → 13 Apr 2016

Conference

Conference	7th IFIP WG 5.5/SOCOLNET Advanced Doctoral Conference on Computing, Electrical and Industrial Systems, DoCEIS 2016
Country	Portugal
City	Costa de Caparica
Period	11/04/16 → 13/04/16

Keywords

Big data
Context sensitivity
Cyber-physical systems
Data mining
Diagnostics
Engineering
ISA-95

Access to Document

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Nagorny, K., Scholze, S., Barata, J., & Colombo, A. W. (2016). An Approach for Implementing ISA 95-Compliant Big Data Observation, Analysis and Diagnosis Features in Industry 4.0 Vision Following Manufacturing Systems. In M. L. Camarinha-Matos, A. J. Falcão, N. Vafaei, & S. Najdi (Eds.), IFIP Advances in Information and Communication Technology (Vol. 470, pp. 116-123). SPRINGER INTERNATIONAL PUBLISHING AG. https://doi.org/10.1007/978-3-319-31165-4_12

Nagorny, Kevin ; Scholze, Sebastian ; Barata, José ; Colombo, Armando Walter. / An Approach for Implementing ISA 95-Compliant Big Data Observation, Analysis and Diagnosis Features in Industry 4.0 Vision Following Manufacturing Systems. IFIP Advances in Information and Communication Technology. editor / M. Luis Camarinha-Matos ; António J. Falcão ; Nazanin Vafaei ; Shirin Najdi. Vol. 470 Cham : SPRINGER INTERNATIONAL PUBLISHING AG, 2016. pp. 116-123

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abstract = "Current trends are showing a technological evolution to an unified Industrial Internet of Things network where smart manufacturing devices are loosely coupled over a cloud to realize comprehensive collaboration and analysis possibilities, and to increase the dynamic and volatile of manufacturing environments. This rising complexity generates also higher ranges of error possibilities and analog a growing demand of new diagnostic approaches to handle also those highly complex systems as manufacturing systems which are following the Industry 4.0 vision. This is an ISA{\textquoteright}95 compliant approach of a Big Data analytics methodology for analysis and observation in Industry 4.0 vision following manufacturing systems.",

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author = "Kevin Nagorny and Sebastian Scholze and Jos{\'e} Barata and Colombo, {Armando Walter}",

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Nagorny, K, Scholze, S, Barata, J & Colombo, AW 2016, An Approach for Implementing ISA 95-Compliant Big Data Observation, Analysis and Diagnosis Features in Industry 4.0 Vision Following Manufacturing Systems. in ML Camarinha-Matos, A J. Falcão, N Vafaei & S Najdi (eds), IFIP Advances in Information and Communication Technology. vol. 470, SPRINGER INTERNATIONAL PUBLISHING AG, Cham, pp. 116-123, 7th IFIP WG 5.5/SOCOLNET Advanced Doctoral Conference on Computing, Electrical and Industrial Systems, DoCEIS 2016, Costa de Caparica, Portugal, 11/04/16. https://doi.org/10.1007/978-3-319-31165-4_12

An Approach for Implementing ISA 95-Compliant Big Data Observation, Analysis and Diagnosis Features in Industry 4.0 Vision Following Manufacturing Systems. / Nagorny, Kevin; Scholze, Sebastian; Barata, José; Colombo, Armando Walter.

IFIP Advances in Information and Communication Technology. ed. / M. Luis Camarinha-Matos; António J. Falcão; Nazanin Vafaei; Shirin Najdi. Vol. 470 Cham : SPRINGER INTERNATIONAL PUBLISHING AG, 2016. p. 116-123.

Research output: Chapter in Book/Report/Conference proceeding › Chapter

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AB - Current trends are showing a technological evolution to an unified Industrial Internet of Things network where smart manufacturing devices are loosely coupled over a cloud to realize comprehensive collaboration and analysis possibilities, and to increase the dynamic and volatile of manufacturing environments. This rising complexity generates also higher ranges of error possibilities and analog a growing demand of new diagnostic approaches to handle also those highly complex systems as manufacturing systems which are following the Industry 4.0 vision. This is an ISA’95 compliant approach of a Big Data analytics methodology for analysis and observation in Industry 4.0 vision following manufacturing systems.

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KW - Context sensitivity

KW - Cyber-physical systems

KW - Data mining

KW - Diagnostics

KW - Engineering

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Nagorny K, Scholze S, Barata J, Colombo AW. An Approach for Implementing ISA 95-Compliant Big Data Observation, Analysis and Diagnosis Features in Industry 4.0 Vision Following Manufacturing Systems. In Camarinha-Matos ML, J. Falcão A, Vafaei N, Najdi S, editors, IFIP Advances in Information and Communication Technology. Vol. 470. Cham: SPRINGER INTERNATIONAL PUBLISHING AG. 2016. p. 116-123 https://doi.org/10.1007/978-3-319-31165-4_12