Automation of technological processes can significantly reduce production costs, time and labor costs. However, automated measuring control systems always have the risk of errors and failures, which in turn can lead to unnecessarily long downtime, marriage, distortion or loss of necessary information. To avoid such negative consequences, redundancy is used as a way to ensure the reliability of process control.
The essence of the decision
Redundancy is a widespread and almost the only way to drastically increase the level of reliability of technological processes in production. An integral part of backup systems are subsystems of diagnostics, control of faults and defects. If any component fails, it is promptly replaced with a working one that is in reserve. On the other hand, process control systems use, save and calculate a large number of various data and parameters that affect the entire process. The implementation of the method can be implemented using the following solutions:
- one of them is the installation of additional measuring devices (instrumentation), which will duplicate the removal, processing and transmission of data from existing measuring devices;
- second, this is a solution to the problem with the help of artificial intelligence. Information backup is used to ensure the correct operation of artificial intelligence. This solution provides for the calculation of the required parameter based on the accumulated information on previous cycles of the technological process.
Redundant failures of measuring devices by installing additional devices is very expensive, so the best solution for this task is to use calculations using artificial intelligence.
If the data is distorted and any measuring device is defective, they are replaced by the calculated values in automatic mode, as is done by the CING artificial intelligence system.
Redundancy of measuring devices in the process
Management of technological processes in modern production involves working with a large amount of data presented in different forms. Developing an effective solution to ensure an optimal response time to changes in the course of the technological process is beyond the power of one or several full-time specialists. This affects the quality, as well as the speed of eliminating failures and faults. This problem is easily solved by the artificial intelligence of the CING system, which is able to process the entire data array in a fraction of seconds and find objectively effective solutions.
For unification, the basis of the CING artificial intelligence system is a neural network. By analyzing the available and obtained data, AI CING calculates a technological parameter that cannot be monitored or measured due to the absence of a sensor or a failure of the measuring device. Thus, there is a redundancy of devices that ensure the quality control of technological processes. The automatic backup system works online, which ensures the fast provision of missing parameters, which means high reliability of quality control.