Abstract
Micro-grinding using micro-tools has become very prevalent due to the miniaturization of products with increased process requirements. Moreover, this process provides an edge over other competitive processes, especially as a final process step. The quality of the part produced by the micro-scale grinding process can be influenced by various factors, particularly by the induced mechanical forces. Therefore, predictive model of cutting force can provide guidance for further development and optimization of the process. Although there has been a lot of a research conducted on conventional grinding, little knowledge has been accumulated on micro-scale grinding due to the fact that it is an emerging field of research. The early grinding models developed are mostly based on parameters such as wheel and workpiece velocity, depth of cut and grit size of the grinding wheel. Those early models narrated that the grits penetrate and cut the material from the workpiece surface with the generated grinding forces proportional to the removed material. However, those models may not be appropriate for micro-scale grinding due to the mode of material removal and the method of contact between surfaces which is different from the macro-scale method. In addition to that, due to the small feed rate used in brittle material machining, ploughing force needs to be considered intensively in addition to the chip formation force. Therefore, a new analytical model has been proposed to evaluate cutting forces of micro-grinding process based on the process configuration, workpiece material properties and micro-grinding tool topography. The size effect of micro-machining has been carefully considered in this proposed model. Therefore, this approach allows the derivation of cutting force comprising of both the chip formation force and ploughing force. Experimental investigation in a micro-grinding configuration has been pursued to validate the proposed predictive model. The estimated cutting force showed a good correlation with the experimental values except for higher depth of cut and lower feed rate. Additionally, paired T test has been performed to quantify the difference between the predicted and experimental results.
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Perveen, A., Rahman, M. & Wong, Y.S. Modeling and simulation of cutting forces generated during vertical micro-grinding. Int J Adv Manuf Technol 71, 1539–1548 (2014). https://doi.org/10.1007/s00170-013-5572-y
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DOI: https://doi.org/10.1007/s00170-013-5572-y