Advanced Data Analytics Platform for Manufacturing Companies

Data analytics is a key factor to make fully informed and data-driven decisions in modern manufacturing companies. With increasing international competition, classical approaches to data analytics have to be enhanced toward advanced data analytics to create smarter products, production processes and...

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Bibliographic Details
Published in2021 26th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA ) pp. 01 - 08
Main Authors Voigt, Tim, Migenda, Nico, Schone, Marvin, Pelkmann, David, Fricke, Matthias, Schenck, Wolfram, Kohlhase, Martin
Format Conference Proceeding
LanguageEnglish
Published IEEE 07.09.2021
Subjects
Companies
CPPS
Data analysis
Data analytics platform
Data models
Data structures
Industry 4.0
infrastructure
novelty detection
OWL
Production
Real-time systems
soft sensors
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Summary:Data analytics is a key factor to make fully informed and data-driven decisions in modern manufacturing companies. With increasing international competition, classical approaches to data analytics have to be enhanced toward advanced data analytics to create smarter products, production processes and customer services. This leverages the full potential of the data to quickly gain insights and make decisions. Application areas include predictive analytics, augmented analytics and real-time analytics. In this paper an advanced data analytics platform (ADAP) for manufacturing companies is presented and verified on a real-world production line. ADAP combines process data obtained in a physical environment with domain knowledge from experts to create data-driven models in a digital environment. In addition, ADAP is well scalable and provides a comprehensible data structure throughout the entire data workflow. ADAP is verified on two different advanced data analytics applications on an electrocoating plant. In order to relate the applications to real production requirements, the needs of local manufactures from the region Ostwestfalen-Lippe (OWL) are taken into account.
DOI:10.1109/ETFA45728.2021.9613499