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Szymon Wojciechowski

Machined Surface Roughness Including Cutter Displacements in Milling of Hardened Teel

The work presented here, concentrates on experimental surface roughness analysis in the milling of hardened steel using a monolithic torus mill. Machined surface roughness with respect to milling process dynamics has been investigated. The surface roughness model including cutter displacements has been developed. Cutting forces and cutter displacements (vibrations) were measured in order to estimate their quantitative influence on Ra and Rz parameters. The cutter displacements were measured online using a scanning 3D laser vibrometer. The influence of cutting speed vc on surface roughness parameters (Ra, Rz) was also studied. The research revealed that real surface roughness parameters are significantly higher than those calculated on the basis of a kinematic-geometric basic model, and their values are strongly dependent on dynamic cutter displacements.

Open access

Szymon Wojciechowski and Szymon Wilk

Abstract

In this paper we describe results of an experimental study where we checked the impact of various difficulty factors in imbalanced data sets on the performance of selected classifiers applied alone or combined with several preprocessing methods. In the study we used artificial data sets in order to systematically check factors such as dimensionality, class imbalance ratio or distribution of specific types of examples (safe, borderline, rare and outliers) in the minority class. The results revealed that the latter factor was the most critical one and it exacerbated other factors (in particular class imbalance). The best classification performance was demonstrated by non-symbolic classifiers, particular by k-NN classifiers (with 1 or 3 neighbors - 1NN and 3NN, respectively) and by SVM. Moreover, they benefited from different preprocessing methods - SVM and 1NN worked best with undersampling, while oversampling was more beneficial for 3NN.

Open access

Szymon Wojciechowski, Paweł Twardowski and Michał Wieczorowski

Abstract

In this paper, an analysis of various factors affecting machined surface texture is presented. The investigation was focused on ball end mill inclination against the work piece (defined by surface inclination angle a. Surface roughness was investigated in a 3D array, and measurements were conducted parallel to the feed motion direction. The analysis of machined surface irregularities as a function of frequency (wavelength A), on the basis of the Power Density Spectrum - PDS was also carried out. This kind of analysis is aimed at valuation of primary factors influencing surface roughness generation as well as its randomness. Subsequently, a surface roughness model including cutter displacements was developed. It was found that plain cutting with ball end mill (surface inclination angle a= 0°) is unfavorable from the point of view of surface roughness, because in cutter’s axis the cutting speed vc ~ 0 m/min. This means that a cutting process does not occur, whereas on the machined surface some characteristics marks can be found. These marks do not appear in case of a* 0°, because the cutting speed vc * 0 on the fill I length of the active cutting edge and as a result, the machined surface texture is more homogenous. Surface roughness parameters determined on the basis of the model including cutter displacements are closer to experimental data for cases with inclination angles a* 0°, in comparison with those determined for plain cutting (a= 0°). It is probably caused by higher contribution in surface irregularities generation of plastic and elastic deformations cumulated near the cutter’s free end than kinematic and geometric parameters, as well as cutter displacements.

Open access

Martyna Wiciak, Paweł Twardowski and Szymon Wojciechowski

Abstract

In this paper, the problem of tool wear prediction during milling of hard-to-cut metal matrix composite Duralcan™ was presented. The conducted research involved the measurements of acceleration of vibrations during milling with constant cutting conditions, and evaluation of the flank wear. Subsequently, the analysis of vibrations in time and frequency domain, as well as the correlation of the obtained measures with the tool wear values were conducted. The validation of tool wear diagnosis in relation to selected diagnostic measures was carried out with the use of one variable and two variables regression models, as well as with the application of artificial neural networks (ANN). The comparative analysis of the obtained results enable.

Open access

Szymon Bzoma, Włodzimierz Meissner, Tomasz Janiszewski, Magdalena Wybraniec, Magdalena Remisiewicz, Robert Krupa, Radosław Kozik, Krzysztof Kaczmarek, Anna Kleszcz, Piotr Minias, Radosław Włodarczyk, Krzysztof Lukoszek and Adam Wojciechowski

Fieldwork Results of Wader Research Stations Working in Poland in 2006-2008