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The Big Data expansion is emerging alongside the development of information technology. Increasing the number of processes drastically increases the number of data. Data are in various forms from paper, audio, geological, digital and other forms. At the same time, computers are becoming increasingly accessible in all spheres of life. Computers take over the role of Big Data management, manipulating them, switching from one location to another and processing them. New technologies are being developed with the aim of managing data in order to improve business reporting, analysis and identifying opportunities to improve business. Therefore, digitization becomes an imperative in the data management strategy.

The paper presents the methods for prediction of the cutting parameters. In order to test the workability of the material by process of scraping, from the aspect of the cutting temperature, an natural thermopar was placed just below the cutting edge of the plate. In this way, a simple, reliable, accurate and economical method for determining the workability of material by cutting is obtained. The feasibility study of several semi-finished products by applying the realized experiments was carried out. Different materials in processing with cutting discs with different coatings give different results, which are used to form neural network and linear regression models.

In a modern era of information technologies, everyday changes are more numerous and various. One of those changes is related to the greater use of mobile devices in a decision making processes. They may be used in the field of automation and improvement of production processes. Their main purpose may be seen as the achievement of optimal production quality, lower production costs, timely deliveries, rational management of material and information flows. Having this in mind, it may be said that interactive data processing from different data sources and the application of artificial intelligence methods is possible within the field of metal coating data processing and prediction. In this paper, novel developed model and expert system, which consists of mobile databases and neural network for the prediction of quality of coating has been presented. Input data obtained from the databases are related to the starting conditions of deposition and the quality of the given coating material, while the target data are related to the thickness and roughness of the material surfaces. Application of the presented solution may confirm the possibility of integration of mobile databases and neural networks within a mobile expert system in the field of modern production systems.