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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Acknowledgements
The research is supported by the National Key Research and Development Program of China No. 2018YFB1004001, the National Science Foundation of China No. 61572057, 61672538 and 61872388, the Natural Science Foundation of Hunan Province No. 2017JJ3414, Anhui Province Key Laboratory of Industry Safety and Emergency Technology No. ISET201810 and the Fundamental Research Funds for the Central Universities of Central South University No. 2018zzts575.
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Zhou, F., Lin, X., Liu, C. et al. A survey of visualization for smart manufacturing. J Vis 22, 419–435 (2019). https://doi.org/10.1007/s12650-018-0530-2
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DOI: https://doi.org/10.1007/s12650-018-0530-2