Next Article in Journal
High Voltage Graphene Nanowall Trench MOS Barrier Schottky Diode Characterization for High Temperature Applications
Next Article in Special Issue
Implementation of R&D Results and Industry 4.0 Influenced by Selected Macroeconomic Indicators
Previous Article in Journal
Application of Polymer Curing Agent in Ecological Protection Engineering of Weak Rock Slopes
Previous Article in Special Issue
A Low-Cost Add-On Sensor and Algorithm to Help Small- and Medium-Sized Enterprises Monitor Machinery and Schedule Processes
Open AccessArticle

Industrial Cyber-Physical System Evolution Detection and Alert Generation

1
Ikerlan Technology Research Centre, Big Data Architectures, 20500 Arrasate, Spain
2
Mondragon Unibertsitatea, Information Systems-HAZI-ISI, 20500 Arrasate, Spain
*
Author to whom correspondence should be addressed.
Appl. Sci. 2019, 9(8), 1586; https://doi.org/10.3390/app9081586
Received: 12 February 2019 / Revised: 1 April 2019 / Accepted: 11 April 2019 / Published: 17 April 2019
Industrial Cyber-Physical System (ICPS) monitoring is increasingly being used to make decisions that impact the operation of the industry. Industrial manufacturing environments such as production lines are dynamic and evolve over time due to new requirements (new customer needs, conformance to standards, maintenance, etc.) or due to the anomalies detected. When an evolution happens (e.g., new devices are introduced), monitoring systems must be aware of it in order to inform the user and to provide updated and reliable information. In this article, CALENDAR is presented, a software module for a monitoring system that addresses ICPS evolutions. The solution is based on a data metamodel that captures the structure of an ICPS in different timestamps. By comparing the data model in two subsequent timestamps, CALENDAR is able to detect and effectively classify the evolution of ICPSs at runtime to finally generate alerts about the detected evolution. In order to evaluate CALENDAR with different ICPS topologies (e.g., different ICPS sizes), a scalability test was performed considering the information captured from the production lines domain. View Full-Text
Keywords: Cyber-Physical Systems (CPS); scalability test; Internet of Things (IoT) Cyber-Physical Systems (CPS); scalability test; Internet of Things (IoT)
Show Figures

Figure 1

MDPI and ACS Style

Iglesias, A.; Sagardui, G.; Arellano, C. Industrial Cyber-Physical System Evolution Detection and Alert Generation. Appl. Sci. 2019, 9, 1586. https://doi.org/10.3390/app9081586

AMA Style

Iglesias A, Sagardui G, Arellano C. Industrial Cyber-Physical System Evolution Detection and Alert Generation. Applied Sciences. 2019; 9(8):1586. https://doi.org/10.3390/app9081586

Chicago/Turabian Style

Iglesias, Aitziber; Sagardui, Goiuria; Arellano, Cristobal. 2019. "Industrial Cyber-Physical System Evolution Detection and Alert Generation" Appl. Sci. 9, no. 8: 1586. https://doi.org/10.3390/app9081586

Find Other Styles
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Search more from Scilit
 
Search
Back to TopTop