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Abstract
n order to allocate resources effectively according to the production plan and to reduce disturbances, a framework for smart production performance analysis is proposed in this article. Decisional DNA based knowledge models of engineering objects, processes and factory are developed within the proposed framework. These models are the virtual representation of manufacturing resources, and with help of Internet of Things, are capable of capturing the past experience and formal decisions. A case study for the smart tool performance analysis is presented in which information of key tool parameters like tool life, surface integrity, tool forces and chip formation can be sensed in real-time, and predictions can be made according to specific requirements. This framework is capable of creating a cyber-physical conjoining of the bottom-level manufacturing resources and thus can work as a technological basis for smart factories and Industry 4.0.
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Authors (3)
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Syed Imran
- Aligarh University, India Faculty of Engineering and Technology
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Cesar Sanin
- University of Newcastle, Australia School of Engineering
Cite as
Full text
- Publication version
- Accepted or Published Version
- DOI:
- Digital Object Identifier (open in new tab) 10.1080/01969722.2019.1565122
- License
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Details
- Category:
- Articles
- Type:
- artykuł w czasopiśmie wyróżnionym w JCR
- Published in:
-
CYBERNETICS AND SYSTEMS
no. 50,
pages 154 - 164,
ISSN: 0196-9722 - Language:
- English
- Publication year:
- 2019
- Bibliographic description:
- Imran S., Szczerbicki E., Sanin C.: Decisional-DNA Based Smart Production Performance Analysis Model// CYBERNETICS AND SYSTEMS. -Vol. 50, nr. 2 (2019), s.154-164
- DOI:
- Digital Object Identifier (open in new tab) 10.1080/01969722.2019.1565122
- Verified by:
- Gdańsk University of Technology
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