Humanity has been interested in magnetism for over 300 years. Many authors have studied the use of applied magnetism to change the properties of products and expand the use of magnetic processing in ship repair production [1, 2]. Experience shows that magnetic pulse processing (MPP) is a simple and economical way to increase the durability of metal-cutting tools, increase the resource of the most worn parts of machines and mechanisms, and increase the durability of friction units, assembly units, and structures during their repair and manufacture. MPP has a number of advantages: simplicity of electromagnetic energy concentration on the product, its rapid accumulation by the material of the working elements of the part, and the efficiency of improving the operational characteristics (processing time is 0.3 ... 2.0 s with insignificant energy consumption). The indicated advantages of magnetic processing of products in comparison with other methods of hardening have been repeatedly confirmed by industrial experience in ship repair production [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12].
However, the complexity of the practical application of MPP lies in the need to adjust the parameters of processing modes, taking into account a specific product. One of the most rational ways to solve this problem is to use adaptive control systems (CS). In the development and construction of such a system, it is advisable to use artificial intelligence methods in particular Adaptive Network-based Fuzzy Inference System networks (ANFIS), for solving optimization processing and forecasting MPP results. The use of these methods will allow for a modern approach to solving this problem. Therefore, the creation of an MPP installation with an intelligent control module is an urgent task today.