Marin Gostimirović

Application of fuzzy logic and regression analysis for modeling surface roughness in face milliing

The objective of this study is to examine the influence of machining parameters on surface finish in face milling. A new approach in modeling surface roughness which uses artificial intelligence tools is described in this paper. This paper focuses on developing empirical models using fuzzy logic and regression analysis. The values of surface roughness predicted by these models are then compared. The results showed that the proposed system can significantly increase the accuracy of the product profile when compared to the conventional approaches, like regression analysis. The results indicate that the fuzzy logic modeling technique can be effectively used for the prediction of surface roughness in dry machining.

Application of Neuro-Fuzzy Systems for Modeling Surface Roughness Parameters for Difficult-to-Cut-Steel

The objective of this study is to examine the influence of machining parameters on surface finish in turning difficult-to-cut-steel. A new approach in modeling surface roughness which uses design of experiments is described in this paper. The values of surface roughness predicted by different models are then compared. Adaptive-neuro-fuzzy-inference system (ANFIS) was used. The results showed that the proposed system 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 can be effectively used for the prediction of the surface roughness for difficult-to-cut-steel.

An Analytical Study of Energy Partition in Grinding

This paper indicates the occurrence of high thermal energy in the surface layer of workpiece material during the process of grinding. To help identify the share of heat which affects the workpiece, firstly the analysis of past research in the field of heat transfer during grinding was conducted. Further there is a proposition of analytical expression for heat distribution factor to the workpiece in the grinding process. Goal of this analytical dependence is to achieve more efficient production of mechanical parts without thermal defects in the surface layer of the part. Presented equation for energy partition has a characteristic of widespread practical use.

MONITORING OF THE DISCHARGE CURRENT BY HALL-EFFECT SENSOR

The paper describes the use of Hall-effect sensor to monitor the discharge current in electrical discharge machining (EDM). The discharge current across the gap between tool and workpiece is fed into developed acquisition system for the recording of impulses during processing. The data acquisition system consists of a sensor that works on the Hall element principle and microcontroller which collects and sends data on the PC that performs data acquisition. Experimental results have shown that discharge current and discharge duration can be clearly classified even with different machining conditions. The integration of the acquisition system can substantially improve the performance of the EDM process trought the analysis of discharge current.

ADAPTIVE NEURO-FUZZY MODELING OF THERMAL VOLTAGE PARAMETERS FOR TOOL LIFE ASSESSMENT IN FACE MILLING

The focus of this paper is to develop a reliable procedure to predict tool life during face milling process. This procedure involves a combination of Method of Least Squares and Neuro Fuzzy system. The factorial designs combined with the ANFIS techniques were applied to perform the prediction of thermal voltage. A least-squares linear regression is applied to perform the prediction of tool life from thermal-voltage signals. In this contribution we also discussed the construction of an ANFIS system that tends to provide a linguistic model for the estimation of thermal voltage obtained with different membership functions. This research focuses on developing ANFIS models using triangular and Gaussian membership functions. The work shows that the membership functions have the dominant effect among the on the accuracy model. The results indicate that the training of ANFIS with the Gaussian membership function obtains a higher accuracy rate in the prediction of thermal voltage, respectively tool life.

MODELING OF CUTTING FORCES IN BALL-END MILLING PROCESS OF HARD (HARDENED) STEEL BY USING RESPONSE SURFACE METHODOLOGY

Received: 06 September 2017 / Accepted: 02 November 2017 Abstract: The possibility of modeling the cutting forces provides an analytical basis for the planning of the machining process, for the construction of machine tool, the optimization of cutting tool geometry as well as on-line monitoring and process management. The planning and execution of the experiment was carried out on the basis of the rotatable central composite design-RCCD here for the input independent parameters the cutting speed was selected, i.e. the spindle speed (n), the feed per tooth (fz), the axial (ap) and radial (ae) depth of cut. Cutting forces (Fx,Fy,Fz) and the resultant cutting force (FR) for the responsive variables are selected. Using the RSM methodology, reliable mathematical models for cutting forces in the form of quadratic polynomials were obtained.

Cutting Force during Grinding Determined by Regression Analysis and Genetic Algorithms

This paper presents an investigation of possibilities of using regression analysis and genetic algorithms in modelling the cutting force values in cylindrical grinding. The process included measurement of cutting forces during cylindrical grinding and later calculating their values using abovementioned techniques. It was concluded that both techniques can be used for cutting forces modelling with genetic algorithms having a slight advantage.

Using Advanced CAM System in Modern Machining

Goal of this paper highlight characteristics and spectrum of machining cutting sequences that programming system SolidCAM support. The practical goal of this paper is defining post-processor and machine simulation for 3-axis CNC machine like a tool for verification modern tool-path and generation G-code that will be used for cutting real part.