A new benchmark dataset for machine learning applications in discrete manufacturing: CiP-DMD

The development of machine learning applications in manufacturing depends primarily on the availability of meaningful and reliable data. In this paper, we present the Center for industrial Productivity - Discrete Manufacturing Dataset (CiP-DMD), the first open-source discrete manufacturing dataset o...

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Bibliographic Details
Published in:Procedia CIRP 2024, Vol.126, p.423-428
Main Authors: Jourdan, Nicolas, Biegel, Tobias, Cassoli, Beatriz Bretones, Metternich, Joachim
Format: Article
Language:English
Subjects:
Benchmark
Dataset
Machine Learning
Manufacturing
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Summary:The development of machine learning applications in manufacturing depends primarily on the availability of meaningful and reliable data. In this paper, we present the Center for industrial Productivity - Discrete Manufacturing Dataset (CiP-DMD), the first open-source discrete manufacturing dataset of a multi-step machining process for which detailed documentation is available. The dataset encompasses a comprehensive description of the individual machining processes, the quality controls and the traceability concept used to match the process and quality data corresponding to the production of 847 pneumatic cylinders. With this new benchmark dataset, we aim to contribute to the development of new approaches and foment the permeation of machine learning in manufacturing.
ISSN:2212-8271
2212-8271
DOI:10.1016/j.procir.2024.08.390