Optimization of industrial processes such as manufacturing or processing of specific materials constitutes a point of interest for many researchers, and its application can lead not only to speeding up the processes in question, but also to reducing the energy cost incurred during them. This article presents a novel approach to optimizing the spindle motion of a computer numeric control (CNC) machine. The proposed solution is to use deep learning with reinforcement to map the performance of the reference points realization optimization (RPRO) algorithm used in the industry. A detailed study was conducted to see how well the proposed method performs the targeted task. In addition, the influence of a number of different factors and hyperparameters of the learning process on the performance of the trained agent was investigated. The proposed solution achieved very good results, not only satisfactorily replicating the performance of the benchmark algorithm, but also speeding up the machining process and providing significantly higher accuracy.
Purpose: This article focuses on a comparative analysis of the technology of additive shaping and multi-axis CNC machining. The authors examine the impact of 3D printing assumptions and CNC machining conditions on the strength of the selected PET material used to produce machine elements on the example of a shaft-type element. The purpose of the study is to identify a better production method. Design/methodology/approach: The analysis was carried out by producing six samples of different diameters and lengths from the same thermoplastic material (ethylene terephthalate) by both 3D printing (FDM) and CNC machining. The resulting samples were subjected to a static compression test, for which a universal testing machine by Zwick & Roell 100 kN was used. The following factors during the production of elements were compared: the difficulty of preparing the project, the time of execution, the cost of execution, the accuracy of the execution and the properties of the elements made. Findings: Elements made by CNC machining have higher compressive strength and yield strength, as well as lower relative expansion and relative shortening. Those produced by CNC machining are created as a monolith (semi-finished product), and the printed elements are incrementally shaped layer by layer. During the strength test, the spaces between the layers decrease, which in turn causes an increase in relative shortening and a decrease in strength properties. Research limitations/implications: Further research is planned on the analysis of manufacturing technology using incremental shaping technology (e.g. change of filling density, change of filling type, change of material) compared to CNC machining. Practical implications: In the conducted tests, a universal method was used, which can be translated into a comparative study of elements made of other materials. Originality/value: The research carried out allowed for the initial assessment of the use of PET material for the production of machine elements through 3D printing and CNC machining.
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Porównywano zastosowania dostępnych technik programowania obróbki numerycznej przedmiotów o powtarzających się elementach konstrukcji. Analizowano możliwości stosowania programowania parametrycznego w trybie programowania zorientowanego warsztatowo oraz pracy w środowisku systemu klasy CAM. Zwrócono uwagę na przejrzystość tworzonego programu w aspekcie możliwości jego edycji i korekty składni, formy zapisu programu w pamięci obrabiarki oraz czasochłonność realizacji przykładowej operacji obróbki.
EN
The application of available methods to NC programming for parts with replicate geometrical elements is comparatively analysed. The possibility for the use of parametric programming both in workshop operation mode and in the environment of CAM system were presented. The capability of editing generated program and syntax correction, the form of its input into machine memory as well as exemplary part program execution time are studied.
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