CPS-enabled worry-free industrial applications

Autor: Jay Lee, Zhe Shi, Zongchang Liu, Chao Jin, Wenjing Jin
Rok vydání: 2017
Předmět:
Zdroj: 2017 Prognostics and System Health Management Conference (PHM-Harbin).
DOI: 10.1109/phm.2017.8079208
Popis: The increasing IoT technology provides large volume of data from various industrial applications, but the gap between the conventional automatic management system and the industry 4.0 system is how to convert the data to information, and then how to use the information to better assist the decision support and optimization in various aspects, including scheduling, planning, supply chain optimization, etc. Cyber physical systems connect the physical assets with the cyber computational capability, in which smart analytics are applied to make the invisible issues transparency and enable rapid and optimized decision-making. In this paper, a framework of CPS is presented to describe the CPS as a 5C architecture, including Connection level, Conversion level, Cyber level, Cognition level and Configuration level. The 5C architecture clearly states how to convert data to information; so the transparency and predictability enable to predict the degradation of the critical assets so as to use the information for smarter decision support. The transformation from traditional maintenance strategy to predictive maintenance strategy is the highlight to enable the worry-free entities. In order to fully understand the CPS architecture and how it can be applied to various industrial applications to realize a worry-free system, two successful case studies of CPS applications are introduced to present the application of CPS enabled cyber manufacturing with critical component health management as an example, and the worry-free wind turbine health management system.
Databáze: OpenAIRE