Abstract
Technological progress leads to an increased utilization of data analysis and Business Intelligence that support manufacturing management decisions. Many promising solutions utilize semantic technologies. However, the deployment and maintenance of semantic technologies especially in reconfigurable manufacturing environments require a lot of manual effort. Concepts to embed them in an automated environment, as required by Reconfigurable Manufacturing Systems, are limited. In this paper, we present an approach to reuse systems engineering data to guide an automated process that updates a production data knowledge base. Thereby, an ontology that integrates distributed operational data to compute Key Performance Indicators such as the Overall Equipment Effectiveness index can be updated during the manufacturing reconfiguration process. This reduces the effort to handle the required changes of semantic data integration systems and enables a cost-effective adaption of the Business Intelligence for Reconfigurable Manufacturing Systems.
| Original language | English |
|---|---|
| Title of host publication | 2019 24th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA) |
| Pages | 1693-1696 |
| Number of pages | 4 |
| ISBN (Electronic) | 9781728103037 |
| DOIs | |
| Publication status | Published - Sept 2019 |
Publication series
| Name | IEEE International Conference on Emerging Technologies and Factory Automation, ETFA |
|---|---|
| Volume | 2019-September |
| ISSN (Print) | 1946-0740 |
| ISSN (Electronic) | 1946-0759 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 9 Industry, Innovation, and Infrastructure
Fields of science
- 202017 Embedded systems
- 102022 Software development
- 102025 Distributed systems
- 102029 Practical computer science
- 202003 Automation
- 202041 Computer engineering
JKU Focus areas
- Digital Transformation
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