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

Digitalization of production lines is the most important issue in the world in recent years. One of the most important issues of this digitalization for today’s manufacturing enterprises is the need to update maintenance practices and maintenance work processes in production lines with technological developments. The fact that sawing machines are in the first part of the production lines shows that it is of critical importance. In this study, it is aimed to determine the necessary principles for digitizing sawing machines and integrating the predictive maintenance system into the machine. As a result of the evaluation, the necessity of real-time data collection, data analysis and artificial intelligence algorithms for predictive maintenance requirements has been determined.

Production starts with supply of raw materials and cutting of this input to the desired dimensions in order to be taken to the production line. Sawing machines used to bring the raw material to the desired dimensions in the industrial manufacturing companies are of great importance and maintain the identity of being the indispensable machine tool of almost all the enterprises’ machine parks. Considering the transition to Industry 4.0 in next 10-15 years, Turkey, which has a significant market share in the production of sawing machines, still needs to be sustainable export to countries like EU Countries and the United States which have the highest level of preparation for Industry 4.0 is directly related to meeting the expectations of these countries. In this study, for both of to raise the level of preparedness and to increase the export potential of Turkey, it is aimed to determine which criteria should be taken as basis in the development of saw machines capable of meeting industry 4.0 requirements. As a result of the evaluation, to meet Industry 4.0 requirements it have been come fore to meet the needs such as adaptation of processing and cutting conditions with barcode data, optimization of cutting conditions by data analysis, remote monitoring and control by communication with desktop and mobile devices, real-time tracking for predictive maintenance and apply maintenance plan in concept of dark factories.