Hofmann B, Bründl P, Franke J (2025)
Publication Type: Journal article
Publication year: 2025
Book Volume: 12
Article Number: 1484
Issue: 1
DOI: 10.1038/s41597-025-05858-0
Data availability represents a critical bottleneck in the development of data-driven analysis tools, particularly for domain-specific applications in manufacturing. This paper introduces a comprehensive dataset of crimp force curves, captured during the production of crimp connections and commonly used for in-line quality control in industrial settings. The dataset comprises 2,439 crimp force curves, obtained from a semi-automatic crimping machine. Each curve has been annotated by both a state-of-the-art crimp force monitoring system, capable of performing binary anomaly detection, and by the authors who provided a more detailed classification into multiple quality categories. The paper introduces this novel dataset with the objective to enhance data-driven quality control systems in manufacturing. Specifically, the dataset serves two specific purposes: it provides a robust foundation for developing domain-specific machine learning models in the context of crimping processes, and it offers a benchmark resource for univariate time series analysis in data-driven applications.
APA:
Hofmann, B., Bründl, P., & Franke, J. (2025). A Dataset of Univariate Crimp Force Curves for Data-Driven Time Series Analysis. Scientific Data, 12. https://doi.org/10.1038/s41597-025-05858-0
MLA:
Hofmann, Bernd, Patrick Bründl, and Jörg Franke. "A Dataset of Univariate Crimp Force Curves for Data-Driven Time Series Analysis." Scientific Data 12 (2025).
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