機械学習を用いた生産ロボット減速機の故障予知手法の開発
概要
There are many production robots used at car manufacturing plants, and each of them uses several reducers. A breakdown of one of these reducers may cause a huge loss due to the stop of all production lines. Therefore, the condition based maintenance to predict failures by predetermined thresholds of average and standard deviation is being currently used. In this study, we propose a new failure prediction method using probability density function and noise removals to improve the accuracy of prediction. Evaluations of prototypes showed much better results and its performance was applicable to the actual production lines.
キーワード
production・manufacture, equipment/maintenance/maintenance, robot, failure prediction (D4)収録: 公益社団法人自動車技術会 2018 年秋季大会学術講演会講演予稿集
〔文献〕
田中 康裕，高木 徹，浦川 敏倫（日産自動車），太田 悠太, タン ドンジャオ（構造計画研究所）．
機械学習を用いた生産ロボット減速機の故障予知手法の開発．自動車技術会論文集．vol. 50, no. 2, pp. 585 - 590．2019．
Contact
まずはお気軽にお問い合せフォームからお問い合わせください。