Model-Based Personalized Visualization System for Monitoring Evolving Industrial Cyber-Physical System

Industrial Cyber-Physical System Evolution Detection and Alert Generation

“…However, as Schütz et al remark [13], the reconfiguration is not available at a sensor level. However, the monitoring software [5] and the information visualization [10] do need to be adapted. This is crucial in Industry 4.0 [1,2,10], as the data captured from the ICPS are converted into information for decision-making.…”

“…The visualization subsystem, already developed and evaluated in Reference [10], is capable of visualizing both the information (information visualization) and the alerts (alert visualization) to communicate changes to the user. Moreover, the subsystem is also responsible for managing the invalid visualizations, i.e., if the ICPS evolves (e.g., a device is removed), the visualization fails due to the fact that the information to be displayed has disappeared.…”

“…Even if the example given is due to a business strategy, note that, as mentioned in Section 3, many reasons can trigger the evolution of an ICPS, e.g., devices' intelligence itself can cause changes in the Data Model. Additionally, it is important to notice that many people are supporting the monitoring system and that not all of them are interested in the same data or information [10]. In spite of that, all of them need to be informed about the occurred evolution.…”

“…Furthermore, ICPS devices are intelligent; they are able to change the data architecture depending on the status of the machine that is being monitored. Note that a concrete machine within a press line can be composed by more that 500 devices [10]. Therefore, being aware of what is happening in the industrial domain is important.…”

“…When an evolution happens, many people need to be alerted in order to detect anomalies to reduce system downtime, since a monitoring system is supported by different user roles that are interested in different information. Therefore, ICPSs evolve throughout their lifetimes [11], and managing the variability is crucial in Industry 4.0 [1, 2,10], as the data captured from the ICPS are converted into information for decision-making. Therefore, managing the variability requires capabilities, posing additional challenges for monitoring ICPSs [1, 11,12].…”