Cardiff University | Prifysgol Caerdydd ORCA
Online Research @ Cardiff 
WelshClear Cookie - decide language by browser settings

Smart manufacturing systems for Industry 4.0: Conceptual framework, scenarios, and future perspectives

Zheng, Pai, wang, Honghui, Sang, Zhiqian, Zhong, Ray Y., Liu, Yongkui, Liu, Chao, Mubarok, Khamdi, Yu, Shiqiang and Xu, Xun 2018. Smart manufacturing systems for Industry 4.0: Conceptual framework, scenarios, and future perspectives. Frontiers of Mechanical Engineering 13 (2) , pp. 137-150. 10.1007/s11465-018-0499-5

Full text not available from this repository.

Abstract

Information and communication technology is undergoing rapid development, and many disruptive technologies, such as cloud computing, Internet of Things, big data, and artificial intelligence, have emerged. These technologies are permeating the manufacturing industry and enable the fusion of physical and virtual worlds through cyber-physical systems (CPS), which mark the advent of the fourth stage of industrial production (i.e., Industry 4.0). The widespread application of CPS in manufacturing environments renders manufacturing systems increasingly smart. To advance research on the implementation of Industry 4.0, this study examines smart manufacturing systems for Industry 4.0. First, a conceptual framework of smart manufacturing systems for Industry 4.0 is presented. Second, demonstrative scenarios that pertain to smart design, smart machining, smart control, smart monitoring, and smart scheduling, are presented. Key technologies and their possible applications to Industry 4.0 smart manufacturing systems are reviewed based on these demonstrative scenarios. Finally, challenges and future perspectives are identified and discussed.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Engineering
Publisher: Springer Verlag
ISSN: 2095-0233
Date of First Compliant Deposit: 21 May 2019
Date of Acceptance: 27 September 2017
Last Modified: 03 Jun 2019 10:18
URI: http://orca.cf.ac.uk/id/eprint/122766

Citation Data

Cited 25 times in Scopus. View in Scopus. Powered By Scopus® Data

Actions (repository staff only)

Edit Item Edit Item