Abbas Adel T, Al-Abduljabbar Abdulhamid A, Alnaser Ibrahim A, Aly Mohamed F, Abdelgaliel Islam H, Elkaseer Ahmed
Department of Mechanical Engineering, College of Engineering, King Saud University, Riyadh 11421, Saudi Arabia.
Department of Mechanical Engineering, School of Sciences and Engineering, The American University in Cairo, AUC Avenue, New Cairo 11835, Egypt.
Materials (Basel). 2022 Mar 12;15(6):2106. doi: 10.3390/ma15062106.
This article reports an extended investigation into the precision hard turning of AISI 4340 alloy steel when machined by two different types of inserts: wiper nose and conventional round nose. It provides a closer look at previously published work and aims at determining the optimal process parameters for simultaneously minimizing surface roughness and maximizing productivity. In the mathematical models developed by the authors, surface roughness at different cutting speeds, depths of cut and feed rates is treated as the objective function. Three robust multi-objective techniques, (1) multi-objective genetic algorithm (MOGA), (2) multi-objective Pareto search algorithm (MOPSA) and (3) multi-objective emperor penguin colony algorithm (MOEPCA), were used to determine the optimal turning parameters when either the wiper or the conventional insert is used, and the results were experimentally validated. To investigate the practicality of the optimization algorithms, two turning scenarios were used. These were the machining of the combustion chamber of a gun barrel, first with an average roughness (Ra) of 0.4 µm and then with 0.8 µm, under conditions of high productivity. In terms of the simultaneous achievement of both high surface quality and productivity in precision hard turning of AISI 4340 alloy steel, this work illustrates that MOPSA provides the best optimal solution for the wiper insert case, and MOEPCA results are the best for the conventional insert. Furthermore, the results extracted from Pareto front plots show that the wiper insert is capable of successfully meeting both the requirements of Ra values of 0.4 µm and 0.8 µm and high productivity. However, the conventional insert could not meet the 0.4 µm Ra requirement; the recorded global minimum was Ra = 0.454 µm, which reveals the superiority of the wiper compared to the conventional insert.
本文报道了一项关于使用两种不同类型刀片（修光刃刀片和传统圆头刀片）对AISI 4340合金钢进行精密硬车削的深入研究。它更深入地审视了之前发表的工作，旨在确定同时最小化表面粗糙度和最大化生产率的最佳工艺参数。在作者开发的数学模型中，将不同切削速度、切削深度和进给率下的表面粗糙度作为目标函数。使用了三种稳健的多目标技术：（1）多目标遗传算法（MOGA）、（2）多目标帕累托搜索算法（MOPSA）和（3）多目标帝企鹅群算法（MOEPCA），来确定使用修光刃刀片或传统刀片时的最佳车削参数，并通过实验对结果进行了验证。为了研究优化算法的实用性，使用了两种车削场景。即在高生产率条件下，对枪管燃烧室进行加工，首先平均粗糙度（Ra）为0.4 µm，然后为0.8 µm。就AISI 4340合金钢精密硬车削中同时实现高表面质量和生产率而言，这项工作表明，对于修光刃刀片情况，MOPSA提供了最佳的最优解，而对于传统刀片，MOEPCA的结果最佳。此外，从帕累托前沿图中提取的结果表明，修光刃刀片能够成功满足Ra值为0.4 µm和0.8 µm以及高生产率的要求。然而，传统刀片无法满足0.4 µm的Ra要求；记录的全局最小值为Ra = 0.454 µm，这揭示了修光刃刀片相对于传统刀片的优越性。
