SAMBA: A Self-Aware Health Monitoring Architecture for Distributed Industrial Systems

被引：0

作者：

Siafara, Lydia C. ^{[1
]}

Kholerdi, Hedyeh A. ^{[1
]}

Bratukhin, Aleksey ^{[2
]}

TaheriNejad, Nima ^{[1
]}

Wendt, Alexander ^{[1
]}

Jantsch, Axel ^{[1
]}

Treytl, Albert ^{[2
]}

Sauter, Thilo ^{[1
,2
]}

机构：

[1] TU Wien, Inst Comp Technol, Vienna, Austria

[2] Danube Univ Krems, Ctr Integrated Sensor Syst, Wr Neustadt, Austria

来源：

IECON 2017 - 43RD ANNUAL CONFERENCE OF THE IEEE INDUSTRIAL ELECTRONICS SOCIETY | 2017年

关键词：

Self-awareness; Monitoring; Health Monitoring; Distributed Cyber-Physical Systems; Bio-inspired; Cognitive System; Automation Systems; System Architecture;

D O I：

暂无

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

In the context of Industry 4.0, constantly evolving shop floors generate the need for a highly adaptive and autonomous automation system with lean maintenance, minimum downtime, maximum reliability, and resilience. Future Manufacturing Execution Systems (MESs) will be more complex and dynamic as well as distributed physically and logically. This makes it very difficult, if not impossible, for the conventional centralized architectures to effectively control these vibrant Cyber-Physical Production Systems (CPPSs). To address these issues, we propose Self-Aware health Monitoring and Bio-inspired coordination for distributed Automation systems (SAMBA), an architecture which tackles these challenges. SAMBA increases the ability of the system to intelligently adapt to rapidly changing environment and conditions of future CPPSs.

引用

页码：3512 / 3517

页数：6

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