Validation of PERFoRM reference architecture demonstrating an application of data mining for predicting machine failure
| Autor: | Frederik Gosewehr, M. Mostafizur Rahman, M. Sidoumou, Jeffrey Wermann, Nandini Chakravorti, Nils Weinert |
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| Rok vydání: | 2018 |
| Předmět: |
Flexibility (engineering)
0209 industrial biotechnology Decision support system Computer science 02 engineering and technology 010501 environmental sciences Agile manufacturing 01 natural sciences 020901 industrial engineering & automation Control system Systems engineering Data analysis General Earth and Planetary Sciences Robot Reference architecture Root cause analysis 0105 earth and related environmental sciences General Environmental Science |
| Zdroj: | Procedia CIRP. 72:1339-1344 |
| ISSN: | 2212-8271 |
| DOI: | 10.1016/j.procir.2018.03.136 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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