An Approach for an Automated Adaption of KPI Ontologies by Reusing Systems Engineering Data

  • Hendrik Walzel
  • , Milan Vathoopan
  • , Alois Zoitl
  • , Alois Knoll

Research output: Chapter in Book/Report/Conference proceedingConference proceedingspeer-review

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 languageEnglish
Title of host publication2019 24th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA)
Pages1693-1696
Number of pages4
ISBN (Electronic)9781728103037
DOIs
Publication statusPublished - Sept 2019

Publication series

NameIEEE International Conference on Emerging Technologies and Factory Automation, ETFA
Volume2019-September
ISSN (Print)1946-0740
ISSN (Electronic)1946-0759

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 9 - Industry, Innovation, and Infrastructure
    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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