İhsan Korkut

A DYNAMOMETER DESIGN AND ITS CONSTRUCTION FOR MILLING OPERATION

In this study, a strain gauge based dynamometer capable of measuring three-force components during metal cutting has been designed and constructed. In order to read and save the cutting force data automatically on a computer during metal cutting, a data acquisition system with the necessary hardware and software was also devised and connected to the developed dynamometer. Cutting force signals were captured and processed using a personal computer through operational amplifiers and analog-to-digital converter. Although the dynamometer was developed primarily for milling operations, it can be used to measure cutting forces during nearly all machining operations (turning, grinding, drilling, etc.). Machining tests were performed at different cutting parameters and the results showed that the dynamometer could be used reliably to measure cutting forces.

Application of regression and artificial neural network analysis in modelling of tool-chip interface temperature in machining

In this paper, the regression analysis (RA) and artificial neural network (ANN) are presented for the prediction of tool-chip interface temperature depends on cutting parameters in machining. The RA and ANN model for prediction tool-chip interface temperature are developed and mathematical equations derived for tool-chip interface temperature prediction are obtained. The tool-chip interface temperature results obtained from mathematical equations with RA and ANN model and the experimental results available in the literature obtained by using AISI 1117 steel work piece with embedded K type thermocouple into the uncoated cutting tool (Korkut, Boy, Karacan, & Seker, 2007) are compared. The coefficient of determination (R^2) both training and testing data for temperature prediction in the ANN model are determined as 0.999791289 and 0.997889303 whereas; R^2 for both training and testing data in the RA model are computed as 0.999063 and 0.999427, respectively. The correlation obtained by the training ANN model are better than the one obtained by training RA model. The training ANN model with the Levenberg-Marquardt (LM) algorithm provides more accurate prediction and is quite useful in the calculation of tool-chip interface temperature when compared with the trained RA method in machining. On the other hand, prediction values obtained the testing RA model is slightly better performance than the testing ANN model. The results show that the tool-chip interface temperature equation derived from RA and ANN model can be used for prediction.

Optimization of Cutting Parameters in Face Milling with Neural Networks and Taguchi based on Cutting Force, Surface Roughness and Temperatures

Prediction of cutting parameters as a function of cutting force, surface roughness and cutting temperature is very important in face milling operations. In the present study, the effect of cutting parameters on the mentioned responses were investigated by using artificial neural networks (ANN) which were trained by using experimental results obtained from Taguchi’s L8 orthogonal design. The experimental results are compared with the results predicted by ANN and the Taguchi method. By training the ANN with the results of experiments which are corresponding with the Taguchi L8 design, with only eight experiments an effective ANN model is trained. By using this network model the other combinations of experiments which did not perform previously, could be predicted with acceptable error.

The Experimental Investigation of the Effects of Different Chip Breaker Forms on the Cutting Forces

The objective of this paper is experimentally investigation of the effects of different chip breaker forms on the cutting forces according to various cutting parameters. AISI 1050 workpiece material, most used material in the manufacturing industry, and SNMG 120408R inserts and PSBNR 2525M12 tool holder have 75° approaching angle according to ISO 3685 are used in the experiments. Seven groups chip breaker form were used in the tests. The chip breaker forms are the coated inserts MA, SA, MS, GH and standard, and the uncoated inserts MS and standard. These inserts are Mitsubishi UC 6010 and UTI20T grade; correspond to ISO P30 and P15 grade, respectively. Machining tests were carried out by using five levels of cutting speeds (150, 200, 250, 300, 350 m/min), three levels of feed rate (0.15, 0.25, 0.35 mm/rev) and two levels of depth of cut (1.6, 2.5 mm). Cutting forces were measured using Kistler dynamometer. The test results show that the highest cutting force values were measured on SA, GH, MA forms, respectively. Complex chip breaker forms cause the increase of the cutting forces. Although the cutting forces on the uncoated inserts were partly small in light cutting conditions, it has increased on the uncoated inserts in heavy cutting conditions compared to coated inserts.

Delik Delme Operasyonlarında Matkap Geometrisinin, GGG 50 Malzemesi Üzerinde, Delik Kalitesi ve Kesme Performansına Olan Etkisi

Bu calismada, farkli matkap geometrileri ve kesme parametrelerinin delme performansi uzerine etkileri sistematik bir sekilde incelenmistir. Farkli geometrilere sahip dort tip matkap kullanilarak itme kuvveti, moment, yuzey puruzlulugu ve geometrik toleranstan sapma degerleri olculmustur. Deneysel calismalarda ticari olarak temin edilebilen yaygin iki takim geometrisi ile ozgun iki kanal geometrisinin performanslari test edilmistir. Delme operasyonu, 10 mm capinda, iki agizli, helisel, yekpare sementit karbur matkaplar kullanilarak GGG 50 malzemesi uzerinde gerceklestirilmistir. Deney deseni icin matkabin geometrik formu, kesme hizi ve ilerleme miktari olmak uzere dorder seviyeli uc farkli kontrol faktoru ile bir Taguchi Deney Tasarimi olusturulmustur. Deney sonuclarinin degerlendirilmesinde Taguchi S/N analizi ve elde edilen verilerin islendigi grafikler kullanilmistir. Anova analizi yardimiyla da deney parametrelerinin deney sonuclari uzerindeki onemi ve etki oranlari bulunmustur. Deneysel sonuclar degerlendirilerek optimum geometri ve optimum isleme sartlari belirlenmistir. Taguchi Sinyal-Gurultu analizinde “en kucuk en iyidir” yaklasimiyla degerlendirilen sonuclara gore; ilerleme kuvveti, giris-cikis yuzey puruzlulugu, dairesellikten sapma ve diklikten sapma acisindan ozgun olarak gelistirilen 4 numarali takim geometrisi diger geometrilere ustunluk saglarken, ilerlemenin en dusuk oldugu (0,15 mm/dev.) ve kesme hizinin en yuksek oldugu (110-120 m/dak.) kesme parametreleri ise kontrol faktorlerinin optimum seviyeleri olarak belirlenmistir.

The Effects of Austempering Temperature and Time on the Machinability of Vermicular Graphite Iron

Abstract In this study, the effect of austempering heat treatment on the cutting forces and surface roughness was investigated during the processing of vermicular graphite cast irons (VGCI) which are widely used in the automotive industry due to their high strength properties. The samples were austenitized at 900 °C for 90 minutes and then austempered at different temperatures (320 °C and 370 °C) for 60 min, 90 min, and 120 min. Machinability tests were carried out under dry conditions at the CNC machining center with the cutting parameters selected in accordance with ISO 3685. As a result of processing of austempered vermicular graphite cast irons with different characteristics the formed cutting forces, surface roughness, cylindricity, and circularity were measured and compared. At the end of the tests, it turned out that the ausferrite morphology (fine or coarse structure) can to be controlled with the austempering heat treatment as well as cutting forces and surface roughness were optimized, respectively. The best surface roughness value was obtained for the austempering parameters of 370 °C and 120 minutes.