Využití umělé inteligence v rámci koncepce Průmyslu 4.0

Abstract

The submitted dissertation "USE OF ARTIFICIAL INTELLIGENCE IN THE CONCEPT OF INDUSTRY 4.0" is focused on the development and testing of a methodology for the possibility of using neural networks in the area of product quality testing in terms of their tightness when using the so-called air-air test method (tightness test where the test medium is air) at a different temperature of the environment and the tested product. The primary use of this methodology is industrial production in many areas, especially the automotive industry and other areas where the emphasis is placed on the tightness of the given products. The proposed methodology is tested on sample products, in which the state of the previous thermal operation is simulated with the subsequent step of tightness measurement. The measured data are then used as a training set of the proposed neural network. The results confirmed the assumption that neural networks can also be used in the field of leak testing in the automated environment of various types of industry. The work has the character of application-basic research, where the obtained results and procedures will be able to be applied in the operational environment of quality testing using leak tests. The results of the work also show that appropriately chosen artificial intelligence tools can be used in many areas where a sufficient amount of data can be collected.