Reference Architectures for Industry 4.0: Literature Review

被引:6
作者
Helmann, Alexandre [1 ]
Deschamps, Fernando [1 ]
Rocha Loures, Eduardo de Freitas [1 ]
机构
[1] Pontificia Univ Catolica Parana, Curitiba, Parana, Brazil
来源
TRANSDISCIPLINARY ENGINEERING FOR COMPLEX SOCIO-TECHNICAL SYSTEMS - REAL-LIFE APPLICATIONS | 2020年 / 12卷
关键词
Architecture model; Industry; 4.0; reference model; smart manufacturing;
D O I
10.3233/ATDE200074
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Currently, production systems are receiving the application of more advanced, integrated and connected technologies to optimize the performance of their manufacturing processes. The new technological solutions demand architectures that support intelligent solutions for a new digitalized industry. However, production systems already in operation have difficulty in implementing these technologies. The existing barriers limit the availability of the direct integration of different systems contemplated in an automation system architecture. This article systematically reviews the existing literature to portray the characteristics of each architecture and that can guide the adoption of new technologies. Through this review, emerging reference architectures were identified, such as RAMI4.0, IIRA, IBM Industry 4.0 and NIST Smart Manufacturing. In conclusion, the article presents a framework for considering which model best fits with the new technological solutions.
引用
收藏
页码:171 / 180
页数:10
相关论文
共 16 条
[1]  
[Anonymous], 2000, 15704 ISOTC184SC5WG1
[2]  
[Anonymous], 2015, Tech. Rep
[3]  
Dyer A., 2010, INFORM RESOURCES MAN, P1167
[4]  
Ensslin L., 2010, PROKNOW C KNOWLEDGE, V10
[5]  
Henning K., 2013, RECOMMENDATIONS IMPL
[6]  
Industrial Value Chain Initiative, 2016, IND VALUE CHAIN REFE
[7]  
Jen L., 2000, IEEE RECOMMENDED PRA
[8]  
LEVIS A.H., 2009, Handbook of Systems Engineering and Management
[9]   Smart manufacturing standardization: Architectures, reference models and standards framework [J].
Li, Qing ;
Tang, Qianlin ;
Chan, Iotong ;
Wei, Hailong ;
Pu, Yudi ;
Jiang, Hongzhen ;
Li, Jun ;
Zhou, Jian .
COMPUTERS IN INDUSTRY, 2018, 101 :91-106
[10]  
Lu Y, 2015, IEEE INT CON AUTO SC, P998, DOI 10.1109/CoASE.2015.7294229