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A DIN Spec 91345 RAMI 4.0 Compliant Data Pipelining Model: An Approach to Support Data Understanding and Data Acquisition in Smart Manufacturing Environments

  • Today, data scientists in the manufacturing domain are confronted with various communication standards, protocols and technologies to save and transfer various kinds of data. These circumstances makes it hard to understand, find, access and extract data needed for use case depended applications. One solution could be a data pipelining approach enforced by a semantic model which describes smart manufacturing assets itself and the access to their data along their life-cycle. Many research contributions in smart manufacturing already came out with with reference architectures like the RAMI 4.0 or standards for meta data description or asset classification. Our research builds upon these outcomes and introduces a semantic model based DIN Spec 91345 (RAMI 4.0) compliant data pipelining approach with the smart manufacturing domain as exemplary use case. This paper has a focus on the developed semantic model used to enable an easy data exploration, finding, access and extraction of data, compatible with various used communication standards, protocols and technologies used to save and transfer data.

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Metadaten
Author:Kevin Nagorny, Sebastian Scholze, Armando W. ColomboORCiD, José B. Oliveira
DOI:https://doi.org/10.1109/ACCESS.2020.3045111
ISSN:2169-3536
Parent Title (English):IEEE Access
Document Type:Article
Language:English
Year of Completion:2020
Date of first Publication:2020/12/16
Creating Corporation:IEEE
Release Date:2024/12/05
Tag:Data mining; Data models; Pipeline processing; Smart manufacturing
Volume:8
First Page:223114
Last Page:223129
Institute:Fachbereich Technik
Research Focus Area:Industrielle Informatik