Abstract Polycarbonates have found important applications in various types of industries including optical, automotive, aerospace, biomedical, and defense manufacturing industries. Conventional mechanical machining has the capability to create complex multi-scale parts and components for various materials including polymeric materials. This study investigates the cutting forces generated during the machining of polycarbonate glass using the micro-milling process. The goal of this research is to machine high quality micro-channels in polycarbonates for microfluidic applications. Both experimental investigation and numerical simulations using the Finite Element Method (FEM) have been carried out to assess the cutting forces generated in three directions during machining of polycarbonate. The effectiveness of tool coating on the reduction of cutting forces has been investigated. It was found that with the careful combination of depth of cut and feed rate, the ductile mode machining of polycarbonate can be achieved, which produces lower cutting forces, that could result in improved surface finish and low tool wear. Both lower and higher of depths of cut were found to generate higher cutting forces due to dragging action and higher tool-workpiece contact area respectively. The Finite Element Method (FEM) was found to be effective in simulating the cutting forces with acceptable range of errors, and thus, could be used to predict cutting forces at the parametric combinations beyond the capacity of the machine or without carrying out further expensive experimentation, for which the chances of tool failure are higher.

中文翻译：

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聚碳酸酯玻璃微铣削切削力的实验和数值研究

摘要 聚碳酸酯在光学、汽车、航空航天、生物医学和国防制造等各种行业中都有重要的应用。传统的机械加工能够为包括聚合物材料在内的各种材料制造复杂的多尺度零件和组件。本研究调查了在使用微铣削工艺加工聚碳酸酯玻璃过程中产生的切削力。这项研究的目标是在聚碳酸酯中加工用于微流体应用的高质量微通道。使用有限元方法 (FEM) 进行了实验研究和数值模拟，以评估聚碳酸酯加工过程中在三个方向上产生的切削力。已经研究了刀具涂层对降低切削力的有效性。研究发现，通过仔细结合切削深度和进给率，可以实现聚碳酸酯的延展模式加工，从而产生较低的切削力，从而改善表面光洁度和降低刀具磨损。发现较低和较高的切削深度分别由于拖曳作用和较高的刀具-工件接触面积而产生较高的切削力。发现有限元方法 (FEM) 可有效模拟切削力，误差范围可接受，因此，可用于预测超出机器能力的参数组合下的切削力，或无需进行进一步昂贵的实验，为此工具失败的机会更高。