https://scholars.lib.ntu.edu.tw/handle/123456789/598313
標題: | Cloud-based analytics module for predictive maintenance of the textile manufacturing process | 作者: | Chang R.-I Lee C.-Y Hung Y.-H. RAY-I CHANG |
關鍵字: | Internet of things;Knowledge discovery in a database;Machine learning;Predictive maintenance | 公開日期: | 2021 | 卷: | 11 | 期: | 21 | 來源出版物: | Applied Sciences (Switzerland) | 摘要: | Industry 4.0 has remarkably transformed many industries. Supervisory control and data acquisition (SCADA) architecture is important to enable an intelligent and connected manufacturing factory. SCADA is extensively used in many Internet of Things (IoT) applications, including data analytics and data visualization. Product quality management is important across most manufacturing industries. In this study, we extensively used SCADA to develop a cloud-based analytics module for production quality predictive maintenance (PdM) in Industry 4.0, thus targeting textile manufacturing processes. The proposed module incorporates a complete knowledge discovery in database process. Machine learning algorithms were employed to analyze preprocessed data and provide predictive suggestions for production quality management. Equipment data were analyzed using the proposed system with an average mean-squared error of ~0.0005. The trained module was implemented as an application programming interface for use in IoT applications and third-party systems. This study provides a basis for improving production quality by predicting optimized equipment settings in manufacturing processes in the textile industry. ? 2021 by the authors. Licensee MDPI, Basel, Switzerland. |
URI: | https://www.scopus.com/inward/record.uri?eid=2-s2.0-85118212630&doi=10.3390%2fapp11219945&partnerID=40&md5=d9daa57cd575201adb6846e1f52c7bdb https://scholars.lib.ntu.edu.tw/handle/123456789/598313 |
ISSN: | 20763417 | DOI: | 10.3390/app11219945 |
顯示於: | 工程科學及海洋工程學系 |
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