The measurement and analysis of micro bonding force for electroplated CBN grinding wheels based on response surface methodology. (November 2015) - Zhi, Geng; Li, Xuekun; Bi, Weiyao; Tang, Jiajun; Rong, Yiming
Highlights: An inclined micro-thread turning test is developed to measure the single grain micro bonding force. The FEM model is established and validated to simulate the grain dislodgement. The RSM is applied to build the comprehensive correlation of the bonding force with its dimensional size, spatial orientation, and bond layer thickness. The optimal bonding condition through regressed prediction model is identified. Abstract: The superabrasive (e.g. CBN or diamond) grain dislodgement occurrence on the wheel surface due to insufficient bonding force is the major failure phenomena in the grinding process with electroplated grinding tools. This failure leads to the abrupt increase of load on the immediate grains, accelerating more grain dislodgement on wheel surface. Ultimately, the aggregated grain dislodgement causes the workpiece profile accuracy degradation and catastrophic wheel sharpness loss. Therefore, the provision of sufficient and uniform micro bonding force all through the wheel surface is the critical task in electroplated superabrasive grinding wheel design. Considering the complexity in the micro bonding force enabling factors, e.g. the grain shape, dimensional size, spatial orientation, and bond layer thickness, it is vital to establish the quantitative and comprehensive relationship between these factors with the micro bonding force for optimal electroplated grinding wheel design. In this paper, an inclined micro-thread turning test is developed to measure the single grain micro bonding force. In addition, the finite element model of single CBN grain bonding force is established and validated to simulate the grain dislodgement. Finally, the response surface methodology (RSM) is applied to build the comprehensive correlation of the bonding force with its dimensional size, spatial orientation, and bond layer thickness. Therefore, the optimal bonding condition through regressed prediction model is identified to provide the quantitative basis for the electroplated CBN grinding wheels design, which indicates that the bonding force can be predicted for specific wheel manufacturing parameters and improved by related variable adjustment.