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データ駆動のタイムシリーズ分析のためのユニバリエート・クリンプ・フォース・カーブのデータセット
Bernd Hofmann1, Patrick Bründl2, Jörg Franke2
1Friedrich-Alexander-Universität Erlangen-Nürnberg, Institute for Factory Automation and Production Systems (FAPS), Nuremberg, Germany. bernd.hofmann@faps.fau.de.
Scientific data
|August 26, 2025
まとめ
この研究は,製造品質管理のための2,439のクリップ力曲線の新しいデータセットを導入します. このリソースは,産業プロセスを改善するための機械学習モデルとタイムシリーズ分析の開発に役立ちます.
科学分野:
- 製造エンジニアリング
- データサイエンス
- 品質管理
背景:
- データの可用性は,製造におけるデータ主導のツールの開発にとって大きな課題です.
- 工業的な環境では非常に重要であり,厳格な品質管理が必要です.
- クリップ・フォースのデータを分析する既存の方法は限られている.
研究 の 目的:
- 製造用途のクリップ・フォース・カーブに関する新しい,包括的なデータセットを導入する.
- クリミングプロセスの領域特有の機械学習モデルの開発を容易にする.
- 工業品質管理における単変数時間系列分析のためのベンチマークデータセットを提供する.
主な方法:
- 半自動クリッピングマシンから2,439のクリッピング力曲線を集めました.
- 最先端の異常検出システムを用いて曲線を注釈した.
- カーブの詳細なマニュアル分類を複数の品質カテゴリーに提供しました.
主要な成果:
- クリップ・フォース・カーブの2,439のユニークなデータセットが現在利用可能である.
- データセットには,自動化された異常検出と詳細な手動の品質分類が含まれています.
- これは機械学習と製造のためのタイムシリーズ分析の研究を容易にする.
結論:
- 提示されたデータセットは,製造におけるデータの可用性の必要性に対応しています.
- データ主導の品質管理を進めるための貴重なリソースです.
- インテリジェントな製造システムのさらなる研究と開発を可能にします.
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