Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
5015794 | International Journal of Machine Tools and Manufacture | 2017 | 32 Pages |
Abstract
This paper investigates the influences of minimum quantity lubrication (MQL) to material removal, surface integrity and temperature in the grinding of titanium alloys (Ti-6Al-4V) using coated abrasive discs. Titanium alloys are used for the slumping moulds when shaping soda-lime glass, due to their good corrosion resistance. However, during the grinding process the temperature can be over 300 °C in microseconds due to the inherent low thermal conductivity of titanium alloys, leading to a degradation of surface quality and integrity. In this work, the developed grinding model considers the effects of grit number, grinding speed, normal load pressure and MQL on the grinding force ratio. The developed model, which was composed of operating parameters, was calibrated by experimental results such as grit number, grinding speed, normal load pressure and the use of MQL to a precision level of 83.98%. The produced ultra-fine surface (~Ra 0.1 µm) demonstrates the progression of the adhesion, the plastic deformation following the fretting and sealing actions on the workpiece surface. The improvement of the surface integrity in its microhardness (~395HV0.025) prolonged the tool life and benefited the productivity. The observed objectives in the material removal rate and surface quality are influenced by the operating abrasives, grinding speed, normal loading pressure and blasting pressure in the grinding action. The control of the thresholds in the load and temperature could vary the surface conditions; whilst MQL provided instant effects to the work's hardening and thermal softening in grinding. The developed multiple criteria model in the response surface method (RSM), suggests the optimised parameter set and results when weightings of surface roughness and material removal rate are given.
Related Topics
Physical Sciences and Engineering
Engineering
Industrial and Manufacturing Engineering
Authors
Chunliang Kuo, Yichia Hsu, Chunhui Chung, Chao-Chang Arthur Chen,