The project was funded by jinan science and technology bureau and undertaken by qilu university of technology, Machine vision-based online intelligent detection of foreign objects in liquids is implemented.2019GXRC067.

Silicon carbide (SiC) has been a promising the-third-generation semiconductor power device material for high-power, high-temperature, substrate applications. It aims to improve the material removal rate (MRR), on the premise of ensuring the surface roughness requirements of the double-faced mechanical polishing of 6-inch SiC substrate. To obtain the relationship between any point on SiC substrate and polishing pads, the model about double-faced mechanical polishing has been built and the kinematics equations were created. Best optimized material removal rate parameters were obtained. MRR reached the maximum when speed rate of the outside ring gear to the inside sun gear m=-1, speed rate of lower plate to the inside sun gear n=5, SiC substrate distribution radius RB=75. The primary and secondary order of MRR (n>m>RB) was obtained. An accurate mathematical model of orthogonal rotary regression test of Tri-factor quadratic of MRR was established and the regression model was significant. Surface quality of SiC substrate was observed and characterized with SEM and AFM. It greatly provides a key guarantee for the next process of CMP, confirmed the importance of MRR to ultra-smooth polishing, and provides a guarantee for its application in semiconductor equipment and technology.

No abstract