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KPI-ML based integration of industrial information systems

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Standard

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 proceedingConference contributionScientificpeer-review

Harvard

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

APA

Tahir, M. A., Mahmoodpour, M., & Lobov, A. (2019). KPI-ML based integration of industrial information systems. In 2019 IEEE 17th International Conference on Industrial Informatics, INDIN 2019 (pp. 93-99). (IEEE International Conference on Industrial Informatics (INDIN); Vol. 2019-July). IEEE. https://doi.org/10.1109/INDIN41052.2019.8972139

Vancouver

Tahir MA, Mahmoodpour M, Lobov A. KPI-ML based integration of industrial information systems. In 2019 IEEE 17th International Conference on Industrial Informatics, INDIN 2019. IEEE. 2019. p. 93-99. (IEEE International Conference on Industrial Informatics (INDIN)). https://doi.org/10.1109/INDIN41052.2019.8972139

Author

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

Bibtex - Download

@inproceedings{8bc220a022a544899b947681a506af4a,
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",
month = "7",
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",

}

RIS (suitable for import to EndNote) - Download

TY - GEN

T1 - KPI-ML based integration of industrial information systems

AU - Tahir, Muhammad Ashhal

AU - Mahmoodpour, Mehdi

AU - Lobov, Andrei

PY - 2019/7/1

Y1 - 2019/7/1

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.

KW - Industrial information system

KW - ISO 22400 standard

KW - Key performance indicators

KW - KPI-ML

KW - Production line

U2 - 10.1109/INDIN41052.2019.8972139

DO - 10.1109/INDIN41052.2019.8972139

M3 - Conference contribution

T3 - IEEE International Conference on Industrial Informatics (INDIN)

SP - 93

EP - 99

BT - 2019 IEEE 17th International Conference on Industrial Informatics, INDIN 2019

PB - IEEE

ER -