Context Modeling with Situation Rules for Industrial Maintenance

Pekka Aarnio; Valeriy Vyatkin; David Hästbacka

doi:10.1109/ETFA.2016.7733539

Context Modeling with Situation Rules for Industrial Maintenance

Pekka Aarnio, Valeriy Vyatkin, David Hästbacka

Tampere University of Technology

Tutkimustuotos: Artikkeli kirjassa/konferenssijulkaisussa › Conference article in proceedings › Scientific › vertaisarvioitu

15 Sitaatiot (Scopus)

Abstrakti

Industrial maintenance requires not only experienced service personnel to carry out the tasks but also up-to-date information about the target equipment and its environment. Accessing information required to execute the tasks is a common challenge for maintenance personnel. This paper presents a knowledge modeling approach and a technical architecture of a gateway system developed to support maintenance personnel with information combined from legacy data sources as well as from context ontology augmented with situational knowledge. The novelty of the approach is its unified object oriented style of knowledge representation encapsulating predefined queries and rules into ontology classes. The approach utilizes standard Semantic Web technologies, especially SPARQL query language and SPARQL Inferencing Notation SPIN. Feasibility of the approach is demonstrated with a simple maintenance use case example executed in an experimental knowledge gateway system

Alkuperäiskieli	Englanti
Otsikko	Proceedings of the 21st IEEE Conference on Emerging Technologies and Factory Automation, ETFA'2016
Kustantaja	IEEE
Sivumäärä	9
ISBN (elektroninen)	978-1-5090-1314-2
DOI - pysyväislinkit	https://doi.org/10.1109/ETFA.2016.7733539
Tila	Julkaistu - 2016
OKM-julkaisutyyppi	A4 Artikkeli konferenssijulkaisussa
Tapahtuma	IEEE International Conference on Emerging Technologies and Factory Automation - Berlin, Saksa Kesto: 6 syysk. 2016 → 9 syysk. 2016 Konferenssinumero: 21 http://www.etfa2016.org/

Julkaisusarja

Nimi	Proceedings IEEE International Conference on Emerging Technologies and Factory Automation
Kustantaja	IEEE
ISSN (painettu)	1946-0740
ISSN (elektroninen)	2379-9560

Conference

Conference	IEEE International Conference on Emerging Technologies and Factory Automation
Lyhennettä	EFTA
Maa/Alue	Saksa
Kaupunki	Berlin
Ajanjakso	06/09/2016 → 09/09/2016
www-osoite	http://www.etfa2016.org/

Pääsy asiakirjaan

10.1109/ETFA.2016.7733539

Siteeraa tätä

@inproceedings{6565866bfc1f4882970c44a86473652f,

title = "Context Modeling with Situation Rules for Industrial Maintenance",

abstract = "Industrial maintenance requires not only experienced service personnel to carry out the tasks but also up-to-date information about the target equipment and its environment. Accessing information required to execute the tasks is a common challenge for maintenance personnel. This paper presents a knowledge modeling approach and a technical architecture of a gateway system developed to support maintenance personnel with information combined from legacy data sources as well as from context ontology augmented with situational knowledge. The novelty of the approach is its unified object oriented style of knowledge representation encapsulating predefined queries and rules into ontology classes. The approach utilizes standard Semantic Web technologies, especially SPARQL query language and SPARQL Inferencing Notation SPIN. Feasibility of the approach is demonstrated with a simple maintenance use case example executed in an experimental knowledge gateway system",

author = "Pekka Aarnio and Valeriy Vyatkin and David H{\"a}stbacka",

year = "2016",

doi = "10.1109/ETFA.2016.7733539",

language = "English",

series = " Proceedings IEEE International Conference on Emerging Technologies and Factory Automation",

publisher = "IEEE",

booktitle = "Proceedings of the 21st IEEE Conference on Emerging Technologies and Factory Automation, ETFA'2016",

address = "United States",

note = "IEEE International Conference on Emerging Technologies and Factory Automation, EFTA ; Conference date: 06-09-2016 Through 09-09-2016",

url = "http://www.etfa2016.org/",

}

Aarnio, P, Vyatkin, V & Hästbacka, D 2016, Context Modeling with Situation Rules for Industrial Maintenance. julkaisussa Proceedings of the 21st IEEE Conference on Emerging Technologies and Factory Automation, ETFA'2016 . Proceedings IEEE International Conference on Emerging Technologies and Factory Automation, IEEE, IEEE International Conference on Emerging Technologies and Factory Automation, Berlin, Saksa, 06/09/2016. https://doi.org/10.1109/ETFA.2016.7733539

Context Modeling with Situation Rules for Industrial Maintenance. / Aarnio, Pekka; Vyatkin, Valeriy; Hästbacka, David.
Proceedings of the 21st IEEE Conference on Emerging Technologies and Factory Automation, ETFA'2016 . IEEE, 2016. ( Proceedings IEEE International Conference on Emerging Technologies and Factory Automation).

Tutkimustuotos: Artikkeli kirjassa/konferenssijulkaisussa › Conference article in proceedings › Scientific › vertaisarvioitu

TY - GEN

T1 - Context Modeling with Situation Rules for Industrial Maintenance

AU - Aarnio, Pekka

AU - Vyatkin, Valeriy

AU - Hästbacka, David

N1 - Conference code: 21

PY - 2016

Y1 - 2016

N2 - Industrial maintenance requires not only experienced service personnel to carry out the tasks but also up-to-date information about the target equipment and its environment. Accessing information required to execute the tasks is a common challenge for maintenance personnel. This paper presents a knowledge modeling approach and a technical architecture of a gateway system developed to support maintenance personnel with information combined from legacy data sources as well as from context ontology augmented with situational knowledge. The novelty of the approach is its unified object oriented style of knowledge representation encapsulating predefined queries and rules into ontology classes. The approach utilizes standard Semantic Web technologies, especially SPARQL query language and SPARQL Inferencing Notation SPIN. Feasibility of the approach is demonstrated with a simple maintenance use case example executed in an experimental knowledge gateway system

AB - Industrial maintenance requires not only experienced service personnel to carry out the tasks but also up-to-date information about the target equipment and its environment. Accessing information required to execute the tasks is a common challenge for maintenance personnel. This paper presents a knowledge modeling approach and a technical architecture of a gateway system developed to support maintenance personnel with information combined from legacy data sources as well as from context ontology augmented with situational knowledge. The novelty of the approach is its unified object oriented style of knowledge representation encapsulating predefined queries and rules into ontology classes. The approach utilizes standard Semantic Web technologies, especially SPARQL query language and SPARQL Inferencing Notation SPIN. Feasibility of the approach is demonstrated with a simple maintenance use case example executed in an experimental knowledge gateway system

U2 - 10.1109/ETFA.2016.7733539

DO - 10.1109/ETFA.2016.7733539

M3 - Conference article in proceedings

T3 - Proceedings IEEE International Conference on Emerging Technologies and Factory Automation

BT - Proceedings of the 21st IEEE Conference on Emerging Technologies and Factory Automation, ETFA'2016

PB - IEEE

T2 - IEEE International Conference on Emerging Technologies and Factory Automation

Y2 - 6 September 2016 through 9 September 2016

ER -

Context Modeling with Situation Rules for Industrial Maintenance

Abstrakti

Julkaisusarja

Conference

Pääsy asiakirjaan

Sormenjälki

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