# Industrial Cyber-Physical System Evolution Detection and Alert Generation
## 1 Introduction  
Nowadays, Industrial Cyber-Physical Systems (ICPSs) play an important role in the current trend of automation in manufacturing as Industry 4.0 is increasingly gaining strength [1; 2; 3]. ICPSs are \"physical, biological, and engineered systems whose operations are monitored, coordinated, controlled, and integrated by a computing and communication core\" [4]. An ICPS is composed of different types of devices, i.e., actuators, displays, and sensors. Data from the devices is monitored in order to transform information that is visualized by the user to monitor the industrial domain [2; 5; 6]. In the automotive domain, manufacturing production lines are based on press machines (press lines). A press line is composed of different machines (e.g., press machine and furnace) and every machine within the press line is composed of different devices. Additionally, each device is able to send different attributes where the information about that device is reflected. Thus, the press line composition in addition to the devices within each machine depends on a customer's real needs, i.e., depending on the production line, one machine or another is introduced in the press line. Note that the characteristics of each machine are variable, e.g., different types of furnace exist or different press machine sizes exist. Additionally, devices within each machine are variable, and they also depend on the customer needs [5]. These makes each press line different from each other, i.e., different ICPS topologies exist. Thus, a monitoring solution in Industry 4.0 receives large amounts of data coming from heterogeneous and distributed devices, which implies that the monitoring system must be scalable enough to respond to different ICPS topologies. These data are being used to identify anomalies during operation [7; 8]. Additionally, after analyzing the industrial domain, we realized that they required a continuous renovation, known as retrofitting, i.e., new devices can be introduced, removed, or modified depending on the customer needs (e.g., new elements of an industrial domain need to be monitored due to customer requirements, so new devices must be inserted). Users can make decisions that impact the business [9]. 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]. As a part of the monitoring logic, it is necessary to communicate the occurred evolution to all users who are supervising the ICPS that is being monitored. Thus, having updated and reliable information at any time allows users to make decisions. Therefore, monitoring solutions in a dynamic context, such as Industry 4.0, need to be flexible to identify and integrate ICPS evolutions rapidly to meet the requirements. Although the identified issues are motivated by a press line domain, we notice that the ICPS evolution is something known in the literature [13,14], and considering the domain analysis performed in our previous work [5], we realized that ICPS evolution besides the different ICPS topologies are not specific problems for press lines.