KPI-ML based integration of industrial information systems

Muhammad Ashhal Tahir; Mehdi Mahmoodpour; Andrei Lobov

doi:10.1109/INDIN41052.2019.8972139

KPI-ML based integration of industrial information systems

Muhammad Ashhal Tahir, Mehdi Mahmoodpour, Andrei Lobov

Automation Technology and Mechanical Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Scientific › peer-review

Abstract

In order to stay competitive in the global market, industrial manufacturers are implementing various methods to improve the production processes. This requires measuring important metrics and making use of performance measurement systems. Based on the data generated in manufacturing operations, various indicators can be defined and measured. These indicators serve as the basis for decision-making, control and health monitoring of a manufacturing process. In this paper an approach is presented that makes use of key performance indicators (KPIs). The KPIs used are defined in a standard known as, ISO 22400 Automation systems and integration-Key performance indicators (KPIs) that is usually applied for management of manufacturing operations. The approach uses the database of a production line to define KPIs and generates a tool for visualizing them. The KPIs are defined using a data model of Key Performance Indicator Markup Language (KPI-ML), which is an XML utilization of the ISO 22400 standard. The recommended approach paves a way for constructing generic KPI-ML visualization tools serving various industries to assess their performance with the same tool.

Original language	English
Title of host publication	2019 IEEE 17th International Conference on Industrial Informatics, INDIN 2019
Publisher	IEEE
Pages	93-99
Number of pages	7
ISBN (Electronic)	9781728129273
DOIs	https://doi.org/10.1109/INDIN41052.2019.8972139
Publication status	Published - 1 Jul 2019
Publication type	A4 Article in conference proceedings
Event	IEEE International Conference on Industrial Informatics - Helsinki, Helsinki, Finland Duration: 22 Jul 2019 → 25 Jul 2019 https://www.indin2019.org/

Publication series

Name	IEEE International Conference on Industrial Informatics (INDIN)
Volume	2019-July
ISSN (Print)	1935-4576

Conference

Conference	IEEE International Conference on Industrial Informatics
Abbreviated title	INDIN '19
Country/Territory	Finland
City	Helsinki
Period	22/07/19 → 25/07/19
Internet address	https://www.indin2019.org/

Keywords

Industrial information system
ISO 22400 standard
Key performance indicators
KPI-ML
Production line

Publication forum classification

Publication forum level 1

ASJC Scopus subject areas

Computer Science Applications
Information Systems

Access to Document

10.1109/INDIN41052.2019.8972139

Cite this

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title = "KPI-ML based integration of industrial information systems",

abstract = "In order to stay competitive in the global market, industrial manufacturers are implementing various methods to improve the production processes. This requires measuring important metrics and making use of performance measurement systems. Based on the data generated in manufacturing operations, various indicators can be defined and measured. These indicators serve as the basis for decision-making, control and health monitoring of a manufacturing process. In this paper an approach is presented that makes use of key performance indicators (KPIs). The KPIs used are defined in a standard known as, ISO 22400 Automation systems and integration-Key performance indicators (KPIs) that is usually applied for management of manufacturing operations. The approach uses the database of a production line to define KPIs and generates a tool for visualizing them. The KPIs are defined using a data model of Key Performance Indicator Markup Language (KPI-ML), which is an XML utilization of the ISO 22400 standard. The recommended approach paves a way for constructing generic KPI-ML visualization tools serving various industries to assess their performance with the same tool.",

keywords = "Industrial information system, ISO 22400 standard, Key performance indicators, KPI-ML, Production line",

author = "Tahir, {Muhammad Ashhal} and Mehdi Mahmoodpour and Andrei Lobov",

year = "2019",

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day = "1",

doi = "10.1109/INDIN41052.2019.8972139",

language = "English",

series = "IEEE International Conference on Industrial Informatics (INDIN)",

publisher = "IEEE",

pages = "93--99",

booktitle = "2019 IEEE 17th International Conference on Industrial Informatics, INDIN 2019",

note = "IEEE International Conference on Industrial Informatics, INDIN '19 ; Conference date: 22-07-2019 Through 25-07-2019",

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}

Tahir, MA, Mahmoodpour, M & Lobov, A 2019, KPI-ML based integration of industrial information systems. in 2019 IEEE 17th International Conference on Industrial Informatics, INDIN 2019. IEEE International Conference on Industrial Informatics (INDIN), vol. 2019-July, IEEE, pp. 93-99, IEEE International Conference on Industrial Informatics, Helsinki, Finland, 22/07/19. https://doi.org/10.1109/INDIN41052.2019.8972139

KPI-ML based integration of industrial information systems. / Tahir, Muhammad Ashhal; Mahmoodpour, Mehdi; Lobov, Andrei.
2019 IEEE 17th International Conference on Industrial Informatics, INDIN 2019. IEEE, 2019. p. 93-99 (IEEE International Conference on Industrial Informatics (INDIN); Vol. 2019-July).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Scientific › peer-review

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AU - Mahmoodpour, Mehdi

AU - Lobov, Andrei

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N2 - In order to stay competitive in the global market, industrial manufacturers are implementing various methods to improve the production processes. This requires measuring important metrics and making use of performance measurement systems. Based on the data generated in manufacturing operations, various indicators can be defined and measured. These indicators serve as the basis for decision-making, control and health monitoring of a manufacturing process. In this paper an approach is presented that makes use of key performance indicators (KPIs). The KPIs used are defined in a standard known as, ISO 22400 Automation systems and integration-Key performance indicators (KPIs) that is usually applied for management of manufacturing operations. The approach uses the database of a production line to define KPIs and generates a tool for visualizing them. The KPIs are defined using a data model of Key Performance Indicator Markup Language (KPI-ML), which is an XML utilization of the ISO 22400 standard. The recommended approach paves a way for constructing generic KPI-ML visualization tools serving various industries to assess their performance with the same tool.

AB - In order to stay competitive in the global market, industrial manufacturers are implementing various methods to improve the production processes. This requires measuring important metrics and making use of performance measurement systems. Based on the data generated in manufacturing operations, various indicators can be defined and measured. These indicators serve as the basis for decision-making, control and health monitoring of a manufacturing process. In this paper an approach is presented that makes use of key performance indicators (KPIs). The KPIs used are defined in a standard known as, ISO 22400 Automation systems and integration-Key performance indicators (KPIs) that is usually applied for management of manufacturing operations. The approach uses the database of a production line to define KPIs and generates a tool for visualizing them. The KPIs are defined using a data model of Key Performance Indicator Markup Language (KPI-ML), which is an XML utilization of the ISO 22400 standard. The recommended approach paves a way for constructing generic KPI-ML visualization tools serving various industries to assess their performance with the same tool.

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KW - Production line

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M3 - Conference contribution

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ER -

KPI-ML based integration of industrial information systems

Abstract

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Conference

Keywords

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ASJC Scopus subject areas

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