Haddeleme işleminin silindirik parçalarda uygulaması, deney sonuçlarının yapay sinir ağları ile modellenmesi

Abstract

Haddeleme işlemi talaşlı imalatta son işlem operasyonu olarak kullanılmakta ve uygulandığı iş parçası yüzeylerinde bazı iyileşmeler (yüzey sertliğinin artması, yüzey pürüzlülüğünün iyileştirilmesi, yorulma ve aşınma ile ilgili iyileşmeler, yüzeydeki çatlak oluşturabilecek derinliklerin azaltılması vb.) meydana getirmektedir. Bu çalışmada haddeleme yapabilen bir aparat yardımıyla silindirik Al 6061–T6 malzemesi üzerinde farklı parametreler (Kuvvet (N), İlerleme (mm/dev), Bilye Çapı (mm), Paso sayısı) kullanılarak haddeleme işlemi gerçekleştirilmiştir. Haddelemede kullanılan parametrelerin yüzey pürüzlülüğü ve yüzey sertliğine etkileri incelenmiştir. Son olarak deney sonuçları Yapay sinir ağları ile modellenerek elde edilen sonuçlarla deney sonuçları karşılaştırılmıştır.

Keywords

• Haddeleme, yüzey pürüzlülüğü, yüzey sertliği, yapay sinir ağları (YSA)

Application Of The Burnishing Process On Cylindrical Parts, Modelling Experimental Data With Artificial Neural Network

Abstract

Burnishing process a sensitive processing technique being applied in super final of functional surfaces of machine elements without machining is being used as the finishing operation in machining, and brings along reward (increase of surface hardness, improved surface roughness improvement on fatigue and wear, and so reducing the depth of the surface cracks can be created.) work piece on which it is applied. In his final operation technique, it can also be used in geometrical improvement processes such as removing the ovalness as well as mechanical improvement processes. While performing burnishing operation, the use of lubrication assists the improvement of mechanical features. As many processing methods (milling, stoning, polishing, honing, adapting) are being used frequency improving the surface roughness value, burnishing operation is also a processing method being used for this operation. The purpose of this final operation can be explained as not obtaining a dimensional correctness but as composing a appropriate surface roughness value on the piece, increasing the abrasion and corrosion resistances of the work piece, enabling improvements in the fatigue and tensile strengths of the piece and reaching enhanced micro hardness values on the surface layers of the piece. In this study, application of burnishing operation on cylindrical pieces and the affects of parameters used in burnishing operation (pressure force, radius of ball and rotation speed) on the surface roughness and surface hardness was discussed. For the tests, Al 6061 –T6 alloy was used as work piece material. Finally, experimental results was modelled with artificial neural network and The experimental results were compared with the results achieved from ANN. The tests were realized by using CNC Taksan lathe machine. Coolant was not used in the tests. Average surface roughness of the work pieces prepared for the tests was measured as 2,6μm, and normal surface hardness was measured as 65 RB. So as to apply burnishing operation, an apparatus was used which can be used for the burnishing of cylindrical pieces on the lathe and which has ballon its end as roller set. The hardness value of balls, which are taken as ready and which are used as crusher, was 58-65RC, and surface roughness was 0.10-0.15μm. Spring system was used in order to adjust the pressure force during burnishing. Three different head design was made to hold the ends of apparatus (balls) procured as ready and used as roller. These heads are being used as per the diameter value of the balls used. The force required for the performance of burnishing operation had been obtained by spring pressure. Consequently, different forces had been obtained at different spring tightenin grates. 108 tests were realized in order to examine the affects of parameters used in burnishing operation. As the result of tests, the measurements were realized with Mitutoyo Surftest Sj-201 device for surface roughness and with Digirock-RBOV device for surface hardness. As the result of the tests made, it was determined that the burnishing operation positively affects the surface hardness and surface roughness of the material. The highest surface hardness was measured as 81.49, and hardness increased by 25% compared to raw piece. The lowest surface hardness was measured as 77.6 RB, and hardness increased by 19% compared to raw piece. In the same manner, the best surface roughness value was measured as 0,12μm, and roughness improved by about 20 times compared to raw piece. The highest surface roughness value was measured as 1,23 μm, and about 2 times improvement realized in respect of roughness value compared to raw piece. Under the conditions of current test;  The negative effect of increase of feed rate on the surface roughness and surface hardness was observed.  The positive effect of increase of pressure force on the surface roughness and surface hardness was observed.  The positive effect of increase of pas number on the surface roughness and surface hardness was observed.  The positive effect of increase of ball diameter on the surface roughness and surface hardness was observed.  The optimum model is obtained within the 4×24×2 configuration that consists of a single hidden layer with 24 neurons in addition to the 4 input sand 2 output with the hyperbolic tangent activation function for the ANN intelligent model.