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Journal of Visualization

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26.11.2018 | Regular Paper

A survey of visualization for smart manufacturing

verfasst von: Fangfang Zhou, Xiaoru Lin, Chang Liu, Ying Zhao, Panpan Xu, Liu Ren, Tingmin Xue, Lei Ren

Erschienen in: Journal of Visualization | Ausgabe 2/2019

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Abstract

In smart manufacturing, people are facing an increasing amount of industrial data derived from various digitalized and connected sources in all kinds of formats. Analyzing and utilizing the data can support informed decision-making at different stages of the entire manufacturing life cycle. In recent years, visualization, as an important technology for understanding large and complex data, has been frequently introduced for industrial data analysis, empowering people with insights for process innovation and efficiency improvement. In this paper, we present a literature review of the visualization technologies specifically tailored for smart manufacturing applications. We propose a taxonomy to categorize the existing research based on application scenarios and industry sectors. We also introduce some concrete examples of applied research projects from different phases of the manufacturing life cycle and discuss the application features of several representative industries. Finally, we identify existing technical challenges and point out directions for future research.

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Vorheriger Artikel Recent research advances on interactive machine learning

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Titel: A survey of visualization for smart manufacturing
verfasst von: Fangfang Zhou
Xiaoru Lin
Chang Liu
Ying Zhao
Panpan Xu
Liu Ren
Tingmin Xue
Lei Ren
Publikationsdatum: 26.11.2018
Verlag: Springer Berlin Heidelberg
Erschienen in: Journal of Visualization / Ausgabe 2/2019
Print ISSN: 1343-8875
Elektronische ISSN: 1875-8975
DOI: https://doi.org/10.1007/s12650-018-0530-2

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