KPI-ML based integration of industrial information systems
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Yksityiskohdat
| Alkuperäiskieli | Englanti |
|---|---|
| Otsikko | 2019 IEEE 17th International Conference on Industrial Informatics, INDIN 2019 |
| Kustantaja | IEEE |
| Sivut | 93-99 |
| Sivumäärä | 7 |
| ISBN (elektroninen) | 9781728129273 |
| DOI - pysyväislinkit | |
| Tila | Julkaistu - 1 heinäkuuta 2019 |
| OKM-julkaisutyyppi | A4 Artikkeli konferenssijulkaisussa |
| Tapahtuma | IEEE International Conference on Industrial Informatics - Helsinki, Helsinki, Suomi Kesto: 22 heinäkuuta 2019 → 25 heinäkuuta 2019 https://www.indin2019.org/ |
Julkaisusarja
| Nimi | IEEE International Conference on Industrial Informatics (INDIN) |
|---|---|
| Vuosikerta | 2019-July |
| ISSN (painettu) | 1935-4576 |
Conference
| Conference | IEEE International Conference on Industrial Informatics |
|---|---|
| Lyhennettä | INDIN '19 |
| Maa | Suomi |
| Kaupunki | Helsinki |
| Ajanjakso | 22/07/19 → 25/07/19 |
| www-osoite |
Tiivistelmä
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.