Next Article in Journal
Activity-Aware Physiological Response Prediction Using Wearable Sensors
Next Article in Special Issue
Influence of the Grinding Wheel Topography on the Thermo-Mechanical Stress Collective in Grinding
Previous Article in Journal
Energy Storage Scheduling with an Advanced Battery Model: A Game–Theoretic Approach
Previous Article in Special Issue
Experimental Analysis for the Use of Sodium Dodecyl Sulfate as a Soluble Metal Cutting Fluid for Micromachining with Electroless-Plated Micropencil Grinding Tools
Article Menu

Export Article

Open AccessArticle
Inventions 2017, 2(4), 31; doi:10.3390/inventions2040031

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.
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)
View Full-Text   |   Download PDF [5663 KB, uploaded 17 November 2017]   |  

Abstract

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
Figures

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

Scifeed alert for new publications

Never miss any articles matching your research from any publisher
  • Get alerts for new papers matching your research
  • Find out the new papers from selected authors
  • Updated daily for 49'000+ journals and 6000+ publishers
  • Define your Scifeed now

SciFeed Share & Cite This Article

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.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Inventions EISSN 2411-5134 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top