Validation of PERFoRM reference architecture demonstrating an application of data mining for predicting machine failure

被引：4

作者：

Chakravorti, Nandini ^{[1
]}

Rahman, M. Mostafizur ^{[1
]}

Sidoumou, Mohamed Redha ^{[1
]}

Weinert, Nils ^{[2
]}

Gosewehr, Frederik ^{[3
]}

Wermann, Jeffrey ^{[3
]}

机构：

[1] Mfg Technol Ctr Ltd, Pilot Way,Ansty Pk, Coventry CV7 9JU, W Midlands, England

[2] Siemens AG, Res Digitalizat & Automat, D-81739 Munich, Germany

[3] Hsch Emden Leer, Constantia Pl 4, D-26723 Emden, Germany

来源：

51ST CIRP CONFERENCE ON MANUFACTURING SYSTEMS | 2018年 / 72卷

关键词：

Industrie; 4.0; Predictive Maintenance; Data Mining; Machine Learning; Condition Monitoring; Equipment health;

D O I：

10.1016/j.procir.2018.03.136

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

The PERFoRM project aims to develop a reference architecture for Agile Manufacturing Control systems for plug-and-produce devices, robots and machines. The aim of the work is to improve the flexibility of the mechanical manufacturing of the housing parts involved in the production of industrial compressors and gas separators. An industrial demonstrator has been designed to implement a Data Analytics tool that provides rules beneficial for root cause analysis and a decision support system for early prediction of the failures. The tool also identifies key alarms for monitoring the machine condition. (C) 2018 The Authors. Published by Elsevier B.V. Peer-review under responsibility of the scientific committee of the 51st CIRP Conference on Manufacturing Systems.

引用

页码：1339 / 1344

页数：6

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