Li Rongrong, Yao Qian, Xu Wei, Li Jingya, Wang Xiaodong Alice
Co-Innovation Center of Efficient Processing and Utilization of Forest Resources, Nanjing Forestry University, Nanjing 210037, China.
Anhui Product Quality Supervision & Inspection Research Institute, Hefei 230051, China.
Materials (Basel). 2022 Jan 24;15(3):879. doi: 10.3390/ma15030879.
The cutting power consumption of milling has direct influence on the economic benefits of manufacturing particle boards. The influence of the milling parameters on the cutting power were investigated in this study. Experiments and data analyses were conducted based on the response surface methodology. The results show that the input parameters had significant effects on the cutting power. The high rake angle reduced the cutting force. Thus, the cutting power decreased with the increase in the rake angle and the cutting energy consumption was also reduced. The cutting power increased with the rotation speed of the main shaft and the depth of milling induced the impact resistance between the milling tool and particle board and the material removal rate. The -values of the created models and input parameters were less than 0.05, which meant they were significant for cutting power and power efficiency. The depth of milling was the most important factor, followed by the rotation speed of the main shaft and then the rake angle. Due to the high values of R of 0.9926 and 0.9946, the quadratic models were chosen for creating the relationship between the input parameters and response parameters. The predicted values of cutting power and power efficiency were close to the actual values, which meant the models could perform good predictions. To minimize the cutting power and maximize the power efficiency for the particle board, the optimized parameters obtained via the response surface methodology were 2°, 6991.7 rpm, 1.36 mm for rake angle, rotation speed of the main shaft and depth of milling, respectively. The model further predicted that the optimized parameters combination would achieve cutting power and power efficiency values of 52.4 W and 11.9%, respectively, with the desirability of 0.732. In this study, the influence of the input parameters on the cutting power and power efficiency are revealed and the created models were useful for selecting the milling parameters for particle boards, to reduce the cutting power.
铣削的切削功率消耗直接影响刨花板制造的经济效益。本研究考察了铣削参数对切削功率的影响。基于响应面法进行了实验和数据分析。结果表明，输入参数对切削功率有显著影响。较大的前角降低了切削力。因此，切削功率随前角的增大而降低，切削能耗也随之降低。切削功率随主轴转速的增加而增加，铣削深度会影响铣刀与刨花板之间的抗冲击性和材料去除率。所建立模型和输入参数的p值均小于0.05，这意味着它们对切削功率和功率效率具有显著性。铣削深度是最重要的因素，其次是主轴转速，然后是前角。由于决定系数R分别为0.9926和0.9946，因此选择二次模型来建立输入参数与响应参数之间的关系。切削功率和功率效率的预测值与实际值接近，这意味着模型能够进行良好的预测。为了使刨花板的切削功率最小化并使功率效率最大化，通过响应面法获得的优化参数分别为：前角2°、主轴转速6991.7 rpm、铣削深度1.36 mm。该模型进一步预测，优化后的参数组合将分别实现切削功率和功率效率值为52.4 W和11.9%，可取性为0.732。本研究揭示了输入参数对切削功率和功率效率的影响，所建立的模型有助于选择刨花板的铣削参数，以降低切削功率。
