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Open AccessArticle

Stochastic Kinematic Process Model with an Implemented Wear Model for High Feed Dry Grinding

Institute of Machine Tools and Manufacturing, ETH Zürich, Leonhardstrasse 21, 8092 Zürich, Switzerland
Author to whom correspondence should be addressed.
Inventions 2017, 2(4), 31;
Received: 12 October 2017 / Revised: 8 November 2017 / Accepted: 14 November 2017 / Published: 16 November 2017
(This article belongs to the Special Issue Modern Grinding Technology and Systems)
This paper considers heavy duty grinding with resin bonded corundum grinding wheels and without lubrication and cooling. A vertical turning machine redesigned to a grinding machine test bench with a power controlled grinding spindle is used in all of the experiments, allowing high tangential table feed rates up to 480 m/min. This special test-rig emulates the railway grinding usually done by a railway grinding train. The main test-rig components are presented and the resulting kinematics of the experimental set-up is described. A stochastic kinematic grinding model is presented. A wear model that is based on the kinematic description of the grinding process is set up. Grain breakage is identified as the main wear phenomenon, initiated by grain flattening and micro-splintering. The wear model is implemented into the stochastic kinematic modelling. The workpiece material side flow and spring back are considered. The simulation results are validated experimentally. The workpiece surface roughness is compared and a good agreement between simulation and experiment can be found, where the deviation between the experiment and the simulation is less than 15% for single-sided contact between the grinding wheel and the workpiece. Higher deviations between simulation and experiment, up to 24%, for double-sided contact is observed. View Full-Text
Keywords: wear modelling; self-sharpening; high-performance dry grinding; surface roughness wear modelling; self-sharpening; high-performance dry grinding; surface roughness
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MDPI and ACS Style

Kuffa, M.; Kuster, F.; Wegener, K. Stochastic Kinematic Process Model with an Implemented Wear Model for High Feed Dry Grinding. Inventions 2017, 2, 31.

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