SAMBA – an architecture for adaptive cognitive control of distributed Cyber-Physical Production Systems based on its self-awareness

Siafara, Lydia Chaido; Kholerdi, Hedyeh; Bratukhin, Aleksey; Taherinejad, Nima; Jantsch, Axel

doi:10.1007/s00502-018-0614-7

Record link:

https://resolver.obvsg.at/urn:nbn:at:at-ubtuw:3-5240
http://hdl.handle.net/20.500.12708/576

Title:

SAMBA – an architecture for adaptive cognitive control of distributed Cyber-Physical Production Systems based on its self-awareness

Citation:

Siafara, L. C., Kholerdi, H., Bratukhin, A., Taherinejad, N., & Jantsch, A. (2018). SAMBA – an architecture for adaptive cognitive control of distributed Cyber-Physical Production Systems based on its self-awareness. Elektrotechnik Und Informationstechnik : E & i, 135(3), 270–277. https://doi.org/10.1007/s00502-018-0614-7

Publisher DOI:

10.1007/s00502-018-0614-7

CatalogPlus:

AC15324302

Publication Type:

Article - Original Research Article

Language:

English

Authors:

Siafara, Lydia Chaido
Kholerdi, Hedyeh
Bratukhin, Aleksey
Taherinejad, Nima
Jantsch, Axel

Organisational Unit:

E384 - Institut für Computertechnik

Journal:

Elektrotechnik und Informationstechnik : e & i

ISSN:

0932-383X

Date (published):

Jun-2018

Number of Pages:

Publisher:

Springer Wien

Peer reviewed:

Yes

Keywords:

self-awareness; cognitive systems; dynamic clustering; autonomous collaborating objects; system health monitoring

Abstract:

Factories in Industry 4.0 are growing in complexity due to the incorporation of a large number of Cyber-Physical System (CPSs) which are logically and often physically distributed. Traditional monolithic control and monitoring structures are not able to address the increasing requirements regarding flexibility, operational time, and efficiency as well as resilience. Self-Aware health Monitoring and Bio-inspired coordination for distributed Automation systems (SAMBA) is a cognitive application architecture which processes information from the factory floor and interacts with the Manufacturing Execution System (MES) to enable automated control and supervision of decentralized CPSs. The proposed architecture increases the ability of the system to ensure the quality of the process by intelligently adapting to rapidly changing environments and conditions.

License:

CC BY 4.0