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Vol. 10 No. 1 (2020): JITA - APEIRON

Boris Pauković, Dražen Marinković

THE ROLE OF POSTPROCESSOR IN THE TRANSLATION OF VECTOR GRAPHICS UNDERSTANDABLE TO THE CNC MACHINE CONTROLLER

Original scientific paper

DOI:https://doi.org/ 10.7251/JIT2001058P

Abstract

The purpose of this paper is to show the post-processor role and importance in the creation of programming code which CNC machine controller can understand and proceed. Today, the use of CNC technology introduces the Industry 4.0 principles in the production, thus increasing the productivity and precision of the produced parts. It is very important to optimize all the production steps, from choosing the right CAD software for vectors drawing, defining tools and generating tool paths, creating and optimizing post-processor, to translating the tool paths in the programming code which controller of the CNC machine can understand, as well as educating the operators to be able to calibrate the machine and understand and run the CNC programming code properly. When all the abovementioned steps are correctly defined, the production can be optimized and best results are guaranteed.

Keywords: CNC technology, CAD/CAM software, postprocessor, CNC programming.

Vol. 26 No. 2 (2023): JITA - APEIRON

Igor Shubinsky, Alexey Ozerov

Application of Artificial Intelligence Methods for the Prediction of Hazardous Failures

Original scientific paper

Abstract

The availability of real-time data on the state of railway facilities and the state-of-the art technologies for data collection and analysis allow transition to the fourth generation maintenance. It is based on the prediction of the facility functional safety and dependability and the risk-oriented facility management. The article describes an approach to assessing the risks of hazardous facility failures using the latest digital data processing methods. The implementation of this approach will help set maintenance objectives and contribute to the efficient use of resources and the reduction of railway facility managers’ expenditures.

Keywords: predictive analysis, maintenance, functional safety, Big Data, Data Science, risk indicators.

Vol. 26 No. 2 (2023): JITA - APEIRON

Igor Shubinsky, Alexey Ozerov

Application of Artificial Intelligence Methods for the Prediction of Hazardous Failures

Original scientific paper

Abstract

The availability of real-time data on the state of railway facilities and the state-of-the art technologies for data collection and analysis allow transition to the fourth generation maintenance. It is based on the prediction of the facility functional safety and dependability and the risk-oriented facility management. The article describes an approach to assessing the risks of hazardous facility failures using the latest digital data processing methods. The implementation of this approach will help set maintenance objectives and contribute to the efficient use of resources and the reduction of railway facility managers’ expenditures.

Keywords: predictive analysis, maintenance, functional safety, Big Data, Data Science, risk indicators.