h. khaloozadeh

$X$-bar control charts are widely used to monitor and control business and manufacturing processes. Design of control charts refers to the selection of parameters, including sample size, control-limit width, and sampling frequency. Many researchers have worked on this issue and have also proposed various solutions. However, despite the numerous advantages, the proposed methods also have their own set of problems. The biggest challenge is the complexity of solving these issues. Due to the fact that optimal design of control charts can be formulated as a multi objective optimization problem, in this paper to solve this problem, we used initial solution Spider's web data envelopment analysis method. In previous methods used multiple algorithms to resolve the issue. But in the proposed method once using Data Envelopment Analysis method and without any other algorithm can solve multi objective problem and this method can yield desirable efficient. Lastly, we compare our method with others and demonstrate its application in a real industrial context.

The SCADA system is a vital system that monitors and controls industrial processes. In these systems, a cyber attack occurs by infiltrating the communication channels between sensors, actuators and servers. In recent years, cyber-attacks have created problems for industrial control systems. A cyber attack has a function similar to a fault in terms of system malfunction. Having instantaneous network parameters such as latency, packet loss, and network traffic can probably make the difference between a fault and a cyber attack. The purpose of this initial research is to detect and then isolate the fault from the cyber attack of the SCADA system using different networks. To do this, a fluid passage system with a controller is modeled. A fault detection filter (BFDF) was designed, which detects various anomalies of the system, If at the time of detection of the anomaly by the filter, the network parameters also show abnormal conditions, a cyber attack is detected. The simulations were performed in Omnet ++ software. The research results showed the effectiveness of this method in distinguishing between fault and cyber attack.