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Reflections on Visualization Research Projects in the Manufacturing Industry.

Lena Cibulski, Johanna Schmidt, Wolfgang Aigner

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    Industry 4.0 generates vast manufacturing data. Visualization and visual analytics are key, but challenges exist. This study offers guidance for engineers and researchers to improve interdisciplinary success.

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    Area of Science:

    • Manufacturing Engineering
    • Computer Science
    • Data Visualization
    • Visual Analytics

    Background:

    • Industry 4.0 and cyber-physical systems generate massive datasets, especially in manufacturing.
    • Visualization and visual analytics are critical for leveraging this data and are key technologies in the fourth industrial revolution.

    Purpose of the Study:

    • To analyze experiences from applied research projects on visualization in manufacturing.
    • To identify challenges and research gaps from both industry and research perspectives.
    • To provide guidance for successful interdisciplinary collaboration between manufacturing engineers and visualization researchers.

    Main Methods:

    • Qualitative analysis of experiences from applied research projects.
    • Characterization and distillation of lessons learned.
    • Identification of research gaps in visualization for manufacturing.

    Main Results:

    • Identified significant challenges in applying visualization within the manufacturing industry.
    • Distilled key lessons learned from practical interdisciplinary projects.
    • Highlighted specific research gaps requiring further investigation.

    Conclusions:

    • Successful application of visualization in manufacturing requires addressing interdisciplinary challenges.
    • Further research is needed to bridge the gap between visualization techniques and manufacturing needs.
    • Guidance provided aims to improve the success rate of future collaborative projects.