Murugesan Mohanraj, Jung Dong Won
Department of Mechanical Engineering, Jeju National University, Jeju-Do 63243, Korea.
Materials (Basel). 2021 Feb 8;14(4):808. doi: 10.3390/ma14040808.
The single-point incremental forming process (SPIF) is one of the emerging manufacturing methods because of its flexibility in producing the desired complex shapes with higher formability at low-cost compared to traditional sheet forming methods. In this research work, we experimentally investigate the forming process to determine the influence of process parameters and their contribution to enhancing the formability without causing a fracture by combining the design of experiments (DOE), grey relational analysis (GRA), and statistical analysis of variance (ANOVA). The surface morphology and the energy dispersive X-ray spectroscopy (EDS) method are used to perform elemental analysis and examine the formed parts during three forming stages. The DOE procedure, a central composite design with a face-centered option, is devised for AA3003-H18 Al alloy sheet for modeling the real-time experiments. The response surface methodology (RSM) approach is adopted to optimize the forming parameters and recognize the optimal test conditions. The statistically developed model is found to have agree with the test measurements. The prediction model's capability in R2 is computed as 0.8931, indicating that the fitted regression model adequately aligns with the estimated grey relational grade (GRG) data. Other statistical parameters, such as root mean square error (RMSE) and average absolute relative error (AARE), are estimated as 0.0196 and 2.78%, respectively, proving the proposed regression model's overall closeness to the measured data. In addition, the prediction error range is identified as -0.05 to 0.05, which is significantly lower and the residual data are distributed normally in the design space with variance and mean of 3.3748 and -0.1232, respectively. ANOVA is performed to understand the adequacy of the proposed model and the influence of the input factors on the response variable. The model parameters, including step size, feed rate, interaction effect of tool radius and step size, favorably influence the response variable. The model terms (0.020 and 11.30), (0.018 and 12.16), and (0.026 and 9.72) are significant in terms of -value and F-value, respectively. The microstructural inspection shows that the thinning behavior tends to be higher as forming depth advances to its maximum; the deformation is uniform and homogeneous under the predefined test conditions.
单点增量成形工艺（SPIF）是一种新兴的制造方法，因为与传统板材成形方法相比，它在以低成本生产所需复杂形状且具有更高成形性方面具有灵活性。在本研究工作中，我们通过结合实验设计（DOE）、灰色关联分析（GRA）和方差统计分析（ANOVA），对成形工艺进行了实验研究，以确定工艺参数的影响及其对提高成形性而不导致断裂的贡献。利用表面形貌和能量色散X射线光谱（EDS）方法在三个成形阶段对成形零件进行元素分析和检查。针对AA3003-H18铝合金板材设计了DOE程序，即采用面心选项的中心复合设计，用于对实时实验进行建模。采用响应面方法（RSM）来优化成形参数并识别最佳测试条件。发现统计开发的模型与测试测量结果相符。预测模型在R2中的能力计算为0.8931，表明拟合回归模型与估计的灰色关联度（GRG）数据充分吻合。其他统计参数，如均方根误差（RMSE）和平均绝对相对误差（AARE），分别估计为0.0196和2.78%，证明了所提出的回归模型与测量数据总体上的接近程度。此外，预测误差范围确定为-0.05至0.05，该范围显著更低，且残差数据在设计空间中呈正态分布，方差和均值分别为3.3748和-0.1232。进行ANOVA以了解所提出模型的充分性以及输入因素对响应变量的影响。模型参数，包括步长、进给速度、刀具半径和步长的交互作用，对响应变量有有利影响。模型项（0.020和11.30）、（0.018和12.16）以及（0.026和9.72）分别在p值和F值方面具有显著性。微观结构检查表明，随着成形深度增加到最大值，变薄行为趋于更高；在预定义的测试条件下，变形是均匀且一致的。
