Cutting Force during Grinding Determined by Regression Analysis and Genetic Algorithms

Pavel Kovač; Vladimir Pucovsky; Marin Gostimirović; Borislav Savković; Ľubomír Šooš; Dušan Ješić

doi:10.4028/www.scientific.net/KEM.686.13

Paper Titles

Preface, Committees

Assessment of Tool Life and Wear Intensity of CBN Tools in Hard Cutting
p.1

Molecular Dynamics Study of Abrasive Grain Morphology and Orientation in Nanometric Grinding
p.7

Cutting Force during Grinding Determined by Regression Analysis and Genetic Algorithms
p.13

Modelling and Analysis of Relationship between Cutting Parameters Surface Roughness and Cutting Forces Using Response Surface Methodology when Hard Turning with Coated Ceramic Inserts
p.19

Using Advanced CAM System in Modern Machining
p.27

Identification and Analysis of Residual Stresses in the Axisymmetric Workpiece Existing before and after Machining
p.33

Identification of the Minimal Thickness of Cutting Layer Based on the Acoustic Emission Signal
p.39

Morphology of the Chip Formation at Orthogonal High Speed Milling of AISI H13
p.45

HomeKey Engineering MaterialsKey Engineering Materials Vol. 686Cutting Force during Grinding Determined by...

Cutting Force during Grinding Determined by Regression Analysis and Genetic Algorithms

Abstract:

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.

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Periodical:

Key Engineering Materials (Volume 686)

Pages:

13-18

DOI:

https://doi.org/10.4028/www.scientific.net/KEM.686.13

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Online since:

February 2016

Authors:

Pavel Kovač*, Vladimir Pucovsky, Marin Gostimirović, Borislav Savković, Ľubomír Šooš, Dušan Ješić

Keywords:

Cutting Force, Cylindrical Grinding, Genetic Algorithms, Modeling, Strain Gauges

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* - Corresponding Author

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