International Scientific Journals
of Scientific Technical Union of Mechanical Engineering "Industry 4.0"

The paper deals with implementation of artificial intelligence method for diagnostics of technological machines. The deep learning as a method of AI seems to be a very good candidate for solving complex problem of technical diagnostics. The method is now implemented for diagnostics for concrete production enterprise.

Diagnostic system is very important part of a system for fault prediction and it is very helpful tool to improve efficiency of industry production. If we want to attain an optimalisation of production, have shortest lead times, low costs of production we need accurate information from maximal number of criteria collected from production machines, to setup best process parameters focused on reaching acceptable life time of machine parts. For this reason, we need improve the power of diagnostic systems with implementation of new methods with new possibilities.

Business Intelligence is set of techniques and tools for acquisition and transformation of raw data into meaningful and useful informations. Multicriterial diagnostic is approach to obtain real status of machining proces just in time and produce a big group of raw data. We want to prepare application business intelligence tools in multicriterial diagnostic process to obtain results of diagnostic process and find "hiddenly" influence the result.