@article{kong_dong_cohen_2017, title={Modeling of the dynamic machining force of vibration-assisted nanomachining process}, volume={28}, url={http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=ORCID&SrcApp=OrcidOrg&DestLinkType=FullRecord&DestApp=WOS_CPL&KeyUT=WOS:000407982200011&KeyUID=WOS:000407982200011}, DOI={10.1016/j.jmapro.2017.05.028}, abstractNote={Nanofabrication technology is very important for many emerging engineering and scientific applications. Among different nanofabrication technologies, vibration-assisted nanomachining provides a low-cost easy-to-setup approach for producing structures with nano-scale resolution. It is very important to understand the mechanism for this nanomachining process and predict the involved machining force, so as to provide guidelines to achieve higher productivity and reduce tip wear. In this work, a machining force model for the tip-based nanomachining process was developed and validated. We analyzed the instantaneous engagement between the cutting tool (AFM tip) and the workpiece (PMMA film) during each tip rotation cycle for the vibration-assisted nanomachining process. A discrete voxel method was adopted to calculate the material removal rate at each moment, and an empirical machining force model is developed by correlating the machining force with material removal rate, which is a function of the input parameters of the nanomachining process. The machining force model was verified by experiments over a large range of machining conditions, and the coefficients in the force model were obtained by minimizing the Mean Square Error (MSE) method by comparing the predicted machining force from the model and measured machining force from the experiments. The results show a good fit between the predicted machining force and the measured machining force.}, journal={Journal of Manufacturing Processes}, author={Kong, X. C. and Dong, Jingyan and Cohen, Paul}, year={2017}, pages={101–108} }
 @article{kong_cohen_dong_2016, title={Predictive modeling of feature dimension for tip-based nano machining process}, volume={24}, ISSN={["1526-6125"]}, url={http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=ORCID&SrcApp=OrcidOrg&DestLinkType=FullRecord&DestApp=WOS_CPL&KeyUT=WOS:000389166500004&KeyUID=WOS:000389166500004}, DOI={10.1016/j.jmapro.2016.06.013}, abstractNote={The tip-based vibration-assisted nanomachining process can fabricate three-dimensional (3D) features with nanometer scale resolution. To control the feature dimension accurately in process planning, we need to understand the relationship between feature dimension and machining parameters including setpoint force, XY vibration amplitude and feed rate. In this article, we conducted full factorial experiments to analyze the relationship between feature dimension and machining parameters. Based on analysis of variance (ANOVA), we determined the significant factors in determining the feature dimension. The feature width is mainly controlled by XY vibration amplitude, and the feature depth is controlled XY vibration, setpoint force and feed rate. In order to predict the feature dimension in nanomachining and provide instructions for machining parameter selection, a semi-empirical mechanical model was built first. Then simplified regression models were also investigated, with all models displaying good predictive capability. The results show good fit between predicted feature depth and measured feature depth, for most machining conditions. These models provide good capability in process planning for implementation of this process.}, journal={JOURNAL OF MANUFACTURING PROCESSES}, author={Kong, Xiangcheng and Cohen, Paul H. and Dong, Jingyan}, year={2016}, month={Oct}, pages={338–345} }
 @inproceedings{kong_zhang_dong_cohen_2015, title={Machining force modeling of vibration-assisted nano-machining process}, DOI={10.1115/MSEC2015-9423}, abstractNote={Nanofabrication technology is very important for many emerging engineering and scientific applications. Among different nanofabrication technologies, vibration-assisted nano-machining provides a low cost easy-to-setup approach to produce structures with nano-scale resolution. It is critical to understand the mechanism for the nano-machining process and predict the cutting force, so as to provide guidelines to achieve higher productivity and reduce tip wear. In this article, a machining force model for tip-based nano-machining process is developed and validated. We analyze the instantaneous engagement area between cutting tool (AFM tip) and workpiece (PMMA film) at the given tip position for the vibration-assisted nano-machining process. A discrete voxel method is adopted to calculate the material removal rate at each moment, and an empirical machining force model is developed by correlating the cutting force with material removal rate. The model was verified by experiments over a large range of machining conditions, and the coefficients and parameters in the force model was obtained using Mean Square Error (MSE) method by comparing the predicted machining force from the force model and measured machining force from experiments. The results show good fit between predicted machining force and measured machining force.}, booktitle={Proceedings of the ASME 10th International Manufacturing Science and Engineering Conference, 2015, vol 2}, author={Kong, X. C. and Zhang, L. and Dong, J. Y. and Cohen, P. H.}, year={2015} }