Bogdan Nedić

Selection Of Cutting Inserts For Aluminum Alloys Machining By Using MCDM Method

Abstract Machining of aluminum and its alloys requires the use of cutting tools with special geometry and material. Since there exists a number of cutting tools for aluminum machining, each with unique characteristics, selection of the most appropriate cutting tool for a given application is very complex task which can be viewed as a multi-criteria decision making (MCDM) problem. This paper is focused on multi-criteria analysis of VCGT cutting inserts for aluminum alloys turning by applying recently developed MCDM method, i.e. weighted aggregated sum product assessment (WASPAS) method. The MCDM model was defined using the available catalogue data from cutting tool manufacturers.

RSM and Neural Network Modeling of Surface Roughness During Turning Hard Steel

In the paper examined was the influence of the cutting regime parameters on surface roughness parameters during turning of hard steel with cubic boron nitrite cutting insert. In this study for modeling of surface finish parameters was used central compositional design of experiment and artificial neural network. The values of surface roughness parameters Ra and Rt were predicted by this two-modeling methodology and determined models were then compared. The results showed that the proposed systems can significantly increase the accuracy of the product profile when compared to the conventional approaches. The results indicate that the design of experiments with central composition plan modeling technique and artificial neural network can be effectively used for the prediction of the surface roughness for hard steel and determined significand cutting regime parameters.

Modeling of kerf width in plasma jet metal cutting process using ANN approach

In this paper Artificial Neural Network (ANN) model was developed for prediction of kerf width in plasma jet metal cutting process. Process parameters whose influence was analyzed are cutting height, cutting speed and arc current. An L18 (21x37) Taguchi orthogonal array experiment was conducted on aluminium sheet of 3 mm thickness. Using the experimental data a feed – forward backpropagation artificial neural network model was developed. After the prediction accuracy of the developed model was verified, the model was used to generate plots that show influence of process parameters and their interactions on analzyed kerf width and to get conlusions about process parameters values that lead to minimal kerf width.

Estimation of tool wear according to cutting forces during machining procedure

Purpose The main purpose of the study was to analyze the relationship between cutting forces and tool wear during turning of steel 30CrNiMo8. Design/methodology/approach It is very important to find the optimal machining conditions to increase the tool life and to improve product quality. Width of tool wear was measured by universal microscope. Findings During experimental procedure, one chip shape was obtained for the given machining parameters. Results showed negligible tool wear for the given experimental conditions. In other words, the tool wear is negligible for one chip shape. Originality/value To increase tool wear, there are different chip shapes.

MACHINING CONTACT AND NON-CONTACT INSPECTION TECHNOLOGIES IN INDUSTRIAL APPLICATION

Even though coordinate measuring machines (CMM) still achieve the most accurate measurement results, non-contact (optical) measuring systems are applied more and more in industry. The reasons of using optical scanners are in the higher speed of acquisition, higher density of data-points and better surface description, the ability to scan complex and non-rigid surfaces etc in comparison to contcact devices. This paper gives a review of state-of-the-art measuring contact and non-contact inspection technologies in industrial applications. Listed are the devices, principles and systems that are used at the data-acquisition (triangulation, time-of-flight and interferometry). The description of contact measuring machines (portable CMM and stationary CMM) and devices for non-contact scanning (laser scanner, structured light scanner and CT scanner) is given, and their advatages and disadvantages are mentioned with corresponding literature review.

TOOL WEAR, CUTTING TEMPERATURE AND CUTTING FORCE DURING TURNING HARD STEEL

In this study, cutting tool`s wear, temperature and forces during turning process were investigated. Used were two types of inserts HM and CBN were taken as cutting tools and round bar of EN 90MnCrV8 hardened steel was used as the workpiece. Since the life of the cutting tool material strongly depends upon cutting temperature, it is important to predict wear and heat generation in the tool. Determination of temperature field in tool was by thermal camera. Determined was dependence of temperature tool wear parameter for two cutting tool materials as well.

Multi-objective optimization of cut quality characteristic in CO2 laser cutting stainless steel

Original scientific paper In this paper, multi-objective optimization of the cut quality characteristics in CO2 laser cutting of AISI 304 stainless steel was discussed. Three mathematical models for the prediction of cut quality characteristics such as surface roughness, kerf width and heat affected zone were developed using the artificial neural networks (ANNs). The laser cutting experiment was planned and conducted according to the Taguchi’s L27 orthogonal array and the experimental data were used to train single hidden layer ANNs using the Levenberg-Marquardt algorithm. The ANN mathematical models were developed considering laser power, cutting speed, assist gas pressure, and focus position as the input parameters. Multi-objective optimization problem was formulated using the weighting sum method in which the weighting factors that are used to combine cut quality characteristics into the single objective function were determined using the analytic hierarchy process method.