Improving Sustainability Index of Grey Cast Iron Finish Cutting Through High-Speed Dry Turning and Cutting Parameters Optimization Using Taguchi-Based Bayesian Method
Improving Sustainability Index of Grey Cast Iron Finish Cutting Through High-Speed Dry Turning and Cutting Parameters Optimization Using Taguchi-Based Bayesian Method
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DOI：
10.1007/s40684-022-00457-5
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发表时间：
2022-08
影响因子：
4.2
通讯作者：
J. Herwan;T. Misaka;S. Kano;H. Sawada;Yoshiyuki Furukawa;O. Ryabov
中科院分区：
文献类型：
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作者：
J. Herwan;T. Misaka;S. Kano;H. Sawada;Yoshiyuki Furukawa;O. Ryabov
灰铸铁是世界上最常见的金属铸造产品。因此，实现这种特殊材料的可持续生产将对整个金属行业的可持续性问题产生重大影响。本文试图通过高速干式车削工艺来提高灰铸铁车削的可持续性。使用田口方法研究了切削参数对产品可持续性指数（PSI）的三个评估指标（即能耗（EC）、刀具成本（TC）和表面粗糙度（SR））的影响。信噪比（S/N）分析表明，最小切割深度（0.1 mm）为所有三种评估提供了最佳性能。同时，切削速度和进给量在获得最佳性能方面存在冲突。为了帮助决策，田口的贝叶斯优化方法，提出了抑制的样本数量，以获得最佳的切削参数的方法的能力进行了演示。并对最佳切削条件的确定进行了分析。
Grey cast iron (GCI) is the most common metal casting product in the world. Therefore, achieving sustainable production for this particular material will provide a significant impact on the sustainability issue of metal industries in general. This paper attempts to enhance the sustainability of grey cast iron turning through a high speed, dry turning process. The effect of cutting parameters on three assessments of product sustainability index (PSI) called energy consumption (EC), tool cost (TC), and surface roughness (SR) was investigated using the Taguchi method. The analysis of the signal to noise (S/N) ratio shows that the minimum depth of cut (0.1 mm) gives the optimal performance for all three assessments. Meanwhile, the cutting speed and feed rate reveal a conflict in obtaining the best performance. To help with making a decision, a Taguchi-based Bayesian optimization method was proposed and the capability of the method on suppressing the number of samples to obtain the optimum cutting parameters was demonstrated. Furthermore, the reasons for the optimum cutting condition were also presented.