Application of function-oriented roughness parameters using confocal microscopy

Klauer, Katja; Eifler, Matthias; Seewig, Jörg; Kirsch, Benjamin; Aurich, Jan C.

doi:10.1016/j.jestch.2018.04.004

Cited by 19 publications

(12 citation statements)

References 12 publications

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“…In other to analyze the possibility of using Sp/Sz and Sq/Sa parameters for description of the ordinate distribution of diversified textures, the correlation and regression analysis of forty surfaces was carried out. The linear coefficient of correlation was also used in previous studies [42][43][44][45]. Table 1 lists the values of the linear coefficient of correlation among the analyzed parameters.…”

Section: Of 20mentioning

confidence: 99%

Prediction of Parameters of Equivalent Sum Rough Surfaces

2020

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In statistical models, the contact of two surfaces is typically replaced by the contact of a smooth, flat, and an equivalent rough sum surface. For the sum surface, the zeroth, second, and fourth moments of the power spectral density m0, m2, and m4 respectively, are the sum of spectral moments of two contacted surfaces. In this work, the selected parameters of the sum surfaces were predicted when the parameters of individual surfaces are known. During parameters selection, it was found that the pair of parameters: Sp/Sz (the emptiness coefficient) and Sq/Sa, better described the shape of the probability ordinate distribution of the analyzed textures than the frequently applied pair: the skewness Ssk and the kurtosis Sku. It was found that the RMS height Sq and the RMS slope Sdq were predicted with very high accuracy. The accuracy of prediction of the average summit curvature Ssc, the areal density of summits Sds, and parameters characterizing the shape of the ordinate distribution Sp/Sz and Sq/Sa was also good (the maximum relative errors were typically smaller than 10%).

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Section: Of 20mentioning

confidence: 99%

Prediction of Parameters of Equivalent Sum Rough Surfaces

2020

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“…It should be also noted here, that Rz may be better to be used to describe ground or similar surfaces. For deterministic processes, like turning and burnishing, the Ra arithmetical average height roughness parameter seems to be much more satisfying [41]. Starting from a feed value of f = 0.0597 mm, the values of Ra are essentially the same for all three data sets, the points on the graph overlap in several cases.…”

Section: Resultsmentioning

confidence: 92%

CAD and FEM Modelling of Theoretical Roughness in Diamond Burnishing

Felhő

Varga

2022

Int. J. Precis. Eng. Manuf.

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Diamond burnishing is a widely used finishing machining that can have a positive effect on both the roughness of cut surfaces and its stress state. This paper is focused on the examination of the theoretical and real roughness of surfaces machined by sliding burnishing. In determining the theoretical roughness, the surface structure created by the pre-burnishing cutting (turning) was also considered. Two different modelling methods were used to obtain theoretical surface roughness data: CAD-modelling and finite element simulation. A method using CAD-based modelling of the machined surface was used to determine the theoretical roughness for both the turning and burnishing processes. However, this previously developed model is not directly applicable to plastic deformation processes such as diamond burnishing, so the principle of the Hertz theory for normal contact of elastic solids was used to calculate the penetration depth of the tool into the workpiece. The 2D FEM simulations were performed in the DEFORM software. To validate the applied modelling methods, real cutting experiments were performed, where the surface roughness values were measured during diamond burnishing experiments with different feed per revolution values. Based on the comparison of both applied modelling methods with real roughness data it can be stated that the theoretical roughness values are well approximated the real data.

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“…Before and after cutting experiments and collected data, all unused and used tools are taken to measure the occurred wear by using the 3D Measuring Laser Microscope. The Material Ratio Curve has been used to evaluate the occurred wear on the cutting edge by measuring and analyzing the SMr2 [29][30][31]. The comparison between SMr2 values before and after cutting experiments is explored that how much wear is exactly occurred.…”

Section: Experimental Measurement Of Cutting Tool Wear For Validationmentioning

confidence: 99%

A model approach for in-process tool condition monitoring in CNC turning using machine vision

Sawangsri

Wattanasinbumrung

2022

Int J Interact Des Manuf

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Tool wear monitoring and real-time predicting tool life during the machining process is becoming a crucial element in modern manufacturing to properly determine the ideal point to replace tool, remains a challenge currently. In this paper, the model approach for in-process monitoring and predicting progressive tool wear by using machine vision is proposed. The developed method adopts machine vision to acquire tool wear images from a CCD camera. The emerged wear analysis is conducted based on the in-progress of signal processing on captured tool wear images, received throughout the cutting process. This automated analysis is carried out with programming to assess and compare a number of pixels of cutting edge images between cutting tools before machining and during the machining process.The developed system is evaluated through experiments of actual cutting conducted on the CNC turning machine with the proposed system installed to evaluate progressive wear during the machining process.Experimental results are capable of indicating the emerged wear at the current state by comparing the number of pixels between the new and used tools. Average ank wear (VB) is also evaluated linked to tool rejection criteria.The developed system is validated by the 3D microscope measuring actual wear on the used tool after cutting experiments. Comparative wear analysis is then performed by nding the correlation equation of pixels examined by a developed system and SMr2 value measured by the microscope. The results showed that the relationship between the number of pixels and SMr2 is a strong correlation.

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Application of function-oriented roughness parameters using confocal microscopy

Cited by 19 publications

References 12 publications

Prediction of Parameters of Equivalent Sum Rough Surfaces

Prediction of Parameters of Equivalent Sum Rough Surfaces

CAD and FEM Modelling of Theoretical Roughness in Diamond Burnishing

A model approach for in-process tool condition monitoring in CNC turning using machine vision

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