Implementation of a Large-Scale Platform for Cyber-Physical System Real-Time Monitoring

被引:41
作者
Canizo, Mikel [1 ]
Conde, Angel [1 ]
Charramendieta, Santiago [1 ]
Minon, Raul [2 ]
Cid-Fuentes, Raul G. [3 ]
Onieva, Enrique [4 ]
机构
[1] Ikerlan Technol Res Ctr, Arrasate Mondragon 20500, Spain
[2] Tecnalia Res & Innovat, Vitoria 01510, Spain
[3] Global IoT & Eleven Paths & Telefon Invest & Desa, Madrid 28050, Spain
[4] Univ Deusto, DeustoTech, Deusto Inst Technol, Bilbao 48007, Spain
关键词
Anomaly detection; big data; cyber-physical system; industry; 4.0; real-time processing; BIG DATA ANALYTICS; ARCHITECTURE; CHALLENGES; INTERNET;
D O I
10.1109/ACCESS.2019.2911979
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The emergence of Industry 4.0 and the Internet of Things (IoT) has meant that the manufacturing industry has evolved from embedded systems to cyber-physical systems (CPSs). This transformation has provided manufacturers with the ability to measure the performance of industrial equipment by means of data gathered from on-board sensors. This allows the status of industrial systems to be monitored and can detect anomalies. However, the increased amount of measured data has prompted many companies to investigate innovative ways to manage these volumes of data. In recent years, cloud computing and big data technologies have emerged among the scientific communities as key enabling technologies to address the current needs of CPSs. This paper presents a large-scale platform for CPS real-time monitoring based on big data technologies, which aims to perform real-time analysis that targets the monitoring of industrial machines in a real work environment. This paper is validated by implementing the proposed solution on a real industrial use case that includes several industrial press machines. The formal experiments in a real scenario are conducted to demonstrate the effectiveness of this solution and also its adequacy and scalability for future demand requirements. As a result of the implantation of this solution, the overall equipment effectiveness has been improved.
引用
收藏
页码:52455 / 52466
页数:12
相关论文
共 55 条
[1]  
[Anonymous], 2015, P 19 INT C SOFTW PRO
[2]  
Antsaklis P. J., 2012, TECH REP
[3]   Big Data Meet Cyber-Physical Systems: A Panoramic Survey [J].
Atat, Rachad ;
Liu, Lingjia ;
Wu, Jinsong ;
Li, Guangyu ;
Ye, Chunxuan ;
Yi, Yang .
IEEE ACCESS, 2018, 6 :73603-73636
[4]   Big Data and virtualization for manufacturing cyber-physical systems: A survey of the current status and future outlook [J].
Babiceanu, Radu F. ;
Seker, Remzi .
COMPUTERS IN INDUSTRY, 2016, 81 :128-137
[5]  
Bahati R., 2011, The impact of control technology, V5, P161, DOI DOI 10.1145/1795194.1795205
[6]   Microservices Architecture Enables DevOps Migration to a Cloud-Native Architecture [J].
Balalaie, Armin ;
Heydarnoori, Abbas ;
Jamshidi, Pooyan .
IEEE SOFTWARE, 2016, 33 (03) :42-52
[7]   Future trends in management and operation of assembly systems: from customized assembly systems to cyber-physical systems [J].
Battaia, Olga ;
Otto, Alena ;
Sgarbossa, Fabio ;
Pesch, Erwin .
OMEGA-INTERNATIONAL JOURNAL OF MANAGEMENT SCIENCE, 2018, 78 :1-4
[8]  
Chavan Vibhavari., 2014, Int. J. Comput. Sci. Inf. Technol, V5, P7932
[9]   Real-Time or Near Real-Time Persisting Daily Healthcare Data Into HDFS and ElasticSearch Index Inside a Big Data Platform [J].
Chen, Dequan ;
Chen, Yi ;
Brownlow, Brian N. ;
Kanjamala, Pradip P. ;
Arredondo, Carlos A. Garcia ;
Radspinner, Bryan L. ;
Raveling, Matthew A. .
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, 2017, 13 (02) :595-606
[10]   Research on the technical architecture for building CPS and its application on a mobile phone factory [J].
Chen, Zhehan ;
Zhang, Xiaohua ;
He, Ketai .
2017 5TH INTERNATIONAL CONFERENCE ON ENTERPRISE SYSTEMS (ES), 2017, :76-84