Inam Ur Rehman , Rakesh Chaudhari , Jay Vora , Vivek Patel , Sakshum Khanna , Subraya Krishna Bhat
{"title":"通过比较田口和Box-Behnken设计方法对NiTi SMA电火花加工工艺的加工性能进行了实验研究","authors":"Inam Ur Rehman , Rakesh Chaudhari , Jay Vora , Vivek Patel , Sakshum Khanna , Subraya Krishna Bhat","doi":"10.1016/j.rsurfi.2025.100636","DOIUrl":null,"url":null,"abstract":"<div><div>The present study aims to investigate the wire electrical discharge machining (WEDM) performance of NiTi shape memory alloy (SMA) by using two widely accepted approaches of design of experiment: Taguchi and Box-Behnken design (BBD) of response surface methodology (RSM). The key important input variables of pulse-on time (T<sub>on</sub>), pulse-off time (T<sub>off</sub>), and discharge current (I<sub>p</sub>) were selected along with material removal rate (MRR), and surface roughness (SR) as response measures. Taguchi's L9 array and BBD with 15 runs were employed. Analysis of variance (ANOVA) and coefficient of determination (R<sup>2</sup>) validated the adequacy of the developed empirical relations. The teaching–learning-based optimization (TLBO) algorithm was further applied to identify optimal machining conditions. For the Taguchi design, optimal parameters were T<sub>on</sub> = 40 μs, T<sub>off</sub> = 18 μs, and I<sub>p</sub> = 4 A, yielding MRR = 1.5769 g/min and SR = 3.57 μm. For the BBD-RSM design, the optimal parameters were T<sub>on</sub> = 40 μs, T<sub>off</sub> = 17 μs, and I<sub>p</sub> = 5 A, resulting in MRR = 1.7321 g/min and SR = 3.38 μm. The optimal results for both designs have shown robust performance. However, the BBD-RSM design approach has outperformed the Taguchi design approach in both MRR and SR under the given conditions. The BBD-RSM design outperformed the Taguchi design, with enhancements of 9.84 % in MRR and 5.62 % in SR. This comparative analysis highlights the robustness of both approaches while demonstrating the superior optimization capability of the BBD-RSM design for machining NiTi SMA.</div></div>","PeriodicalId":21085,"journal":{"name":"Results in Surfaces and Interfaces","volume":"20 ","pages":"Article 100636"},"PeriodicalIF":0.0000,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Experimental investigations on the machining performance of the WEDM process of NiTi SMA by comparison of Taguchi and Box-Behnken design approaches\",\"authors\":\"Inam Ur Rehman , Rakesh Chaudhari , Jay Vora , Vivek Patel , Sakshum Khanna , Subraya Krishna Bhat\",\"doi\":\"10.1016/j.rsurfi.2025.100636\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>The present study aims to investigate the wire electrical discharge machining (WEDM) performance of NiTi shape memory alloy (SMA) by using two widely accepted approaches of design of experiment: Taguchi and Box-Behnken design (BBD) of response surface methodology (RSM). The key important input variables of pulse-on time (T<sub>on</sub>), pulse-off time (T<sub>off</sub>), and discharge current (I<sub>p</sub>) were selected along with material removal rate (MRR), and surface roughness (SR) as response measures. Taguchi's L9 array and BBD with 15 runs were employed. Analysis of variance (ANOVA) and coefficient of determination (R<sup>2</sup>) validated the adequacy of the developed empirical relations. The teaching–learning-based optimization (TLBO) algorithm was further applied to identify optimal machining conditions. For the Taguchi design, optimal parameters were T<sub>on</sub> = 40 μs, T<sub>off</sub> = 18 μs, and I<sub>p</sub> = 4 A, yielding MRR = 1.5769 g/min and SR = 3.57 μm. For the BBD-RSM design, the optimal parameters were T<sub>on</sub> = 40 μs, T<sub>off</sub> = 17 μs, and I<sub>p</sub> = 5 A, resulting in MRR = 1.7321 g/min and SR = 3.38 μm. The optimal results for both designs have shown robust performance. 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引用次数: 0
摘要
采用响应面法(RSM)中的田口设计(Taguchi)和Box-Behnken设计(BBD)两种被广泛接受的实验设计方法,对NiTi形状记忆合金(SMA)的线切割加工(WEDM)性能进行了研究。选取脉冲接通时间(Ton)、脉冲关闭时间(Toff)和放电电流(Ip)等关键重要输入变量,并以材料去除率(MRR)和表面粗糙度(SR)作为响应测度。田口的L9阵列和15分的BBD被使用。方差分析(ANOVA)和决定系数(R2)验证了所建立的经验关系的充分性。进一步应用基于教与学的优化算法(TLBO)辨识最优加工条件。Taguchi设计的最佳参数为Ton = 40 μs, Toff = 18 μs, Ip = 4 A, MRR = 1.5769 g/min, SR = 3.57 μm。对于BBD-RSM设计,最佳参数为Ton = 40 μs, Toff = 17 μs, Ip = 5 A,得到的MRR = 1.7321 g/min, SR = 3.38 μm。两种设计的最佳结果都显示出稳健的性能。然而,在给定条件下,BBD-RSM设计方法在MRR和SR方面都优于Taguchi设计方法。BBD-RSM设计优于田口设计,MRR提高了9.84%,sr提高了5.62%。对比分析突出了两种方法的鲁棒性,同时展示了BBD-RSM设计在加工NiTi SMA方面的卓越优化能力。
Experimental investigations on the machining performance of the WEDM process of NiTi SMA by comparison of Taguchi and Box-Behnken design approaches
The present study aims to investigate the wire electrical discharge machining (WEDM) performance of NiTi shape memory alloy (SMA) by using two widely accepted approaches of design of experiment: Taguchi and Box-Behnken design (BBD) of response surface methodology (RSM). The key important input variables of pulse-on time (Ton), pulse-off time (Toff), and discharge current (Ip) were selected along with material removal rate (MRR), and surface roughness (SR) as response measures. Taguchi's L9 array and BBD with 15 runs were employed. Analysis of variance (ANOVA) and coefficient of determination (R2) validated the adequacy of the developed empirical relations. The teaching–learning-based optimization (TLBO) algorithm was further applied to identify optimal machining conditions. For the Taguchi design, optimal parameters were Ton = 40 μs, Toff = 18 μs, and Ip = 4 A, yielding MRR = 1.5769 g/min and SR = 3.57 μm. For the BBD-RSM design, the optimal parameters were Ton = 40 μs, Toff = 17 μs, and Ip = 5 A, resulting in MRR = 1.7321 g/min and SR = 3.38 μm. The optimal results for both designs have shown robust performance. However, the BBD-RSM design approach has outperformed the Taguchi design approach in both MRR and SR under the given conditions. The BBD-RSM design outperformed the Taguchi design, with enhancements of 9.84 % in MRR and 5.62 % in SR. This comparative analysis highlights the robustness of both approaches while demonstrating the superior optimization capability of the BBD-RSM design for machining NiTi SMA.