Papers by Author: Ming Hai Wang

Abstract: According to the size effect theory established on the concept of geometrically necessary dislocations and results of nano-indentation experiments, a novel brittle-ductile mechanism of ultra-precision turning of single crystal silicon is proposed. The accurate critical chip thickness is firstly calculated on the basis of theoritical analysis. A macro-micro cutting model is created based on the brittle-ductile transition mechanism. Finally, the results of study are testified through experiments.

Abstract: The mechanism of brittle-ductile transition (BDT) in machined Si single crystal is investigated by simulating dislocations emission from crack tip along (111) and (111) slip plane under mixed-mode loading. One kind of compression-shear crack is taken into account and the law of strain-energy-density-factor is applied as fracture criteria. The total number of the emitted dislocations and the number of dislocations in each slip plane at the onset of cleavage are calculated. It is found that the ratio of stress intensity factor kII to kI that the crack tip is subjected has significant effect on the BDT in machined Si single crystal. Then the results are applied to study the action of negative rake angle and edge radius of diamond tool in the ultra-precision turning.

Abstract: In ultra-precision turning process, the predictive modeling of surface roughness and the optimization of cutting conditions are the key factors to improve the quality of products and raise the efficiency of equipments. In this paper, the application of genetic algorithm in identifying nonlinear surface roughness prediction model is discussed, and presents mixed genetic-simulated annealing algorithm approach to optimization of cutting conditions in ultra-precision turning. The experiment was carried out with diamond cutting tools, for machining single crystal aluminum optics covering a wide range of machining conditions. The results of fitting of prediction model and optimal cutting conditions using genetic algorithm (GA) are compared with least square method and traditional optimal method.