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Experimental Characterisation of Tool Hardness Evolution Under Consideration of Process Relevant Cyclic Thermal and Mechanical Loading During Industrial Forging Read chapter Read first chapter

2021 | OriginalPaper | Chapter

Automated Profiling of Energy Data in Manufacturing

Authors : C. Kaymakci, A. Sauer

Published in: Production at the leading edge of technology

Publisher: Springer Berlin Heidelberg

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Abstract

In order to offer energy flexibility in energy markets in short time slots a fast and efficient processing and analysis of data from shop floor to production planning and control is necessary. To this end and to gain more knowledge, different datasets and sources have to be integrated. This paper proposes a conceptual architecture and a method for profiling energy data of manufacturing systems. This includes datasets from information systems as well as physical sources such as sensors, actuators or machine data. Real-life data often come with quality problems like missing and invalid values, outliers or duplicates. The key concept is to automatically identify the necessary metadata for including the dataset in an environment where further analysis and integration of datasets can take place. Moreover, a web service for profiling and visualizing data is implemented.

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previous chapter Concept for Predicting Vibrations in Machine Tools Using Machine Learning
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Metadata
Title
Automated Profiling of Energy Data in Manufacturing
Authors
C. Kaymakci
A. Sauer
Copyright Year
2021
Publisher
Springer Berlin Heidelberg
Book
Production at the leading edge of technology

Print ISBN: 978-3-662-62137-0

Electronic ISBN: 978-3-662-62138-7

Copyright Year: 2021

DOI
https://doi.org/10.1007/978-3-662-62138-7_56

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