电火花加工
机械加工
电极
材料科学
冶金
机械工程
工具钢
放电
工程类
化学
物理化学
作者
Shoaib Mohammad,Mudasser Habib,Ammara Kanwal,Muhammad Asim,Muhammad Umar Farooq,Imran Zahid,Noreen Sher Akbar,Hussein Togun,Fahid Riaz
标识
DOI:10.1016/j.rineng.2024.103812
摘要
This work evaluates a novel approach of employing copper and graphite multi-material cladded electrodes in two configurations (copperin- graphiteout and graphitein- copperout) for their performance on material removal rate, surface roughness, tool wear ratio, overcut and depth of cut under electric discharge machining of D2 tool steel. Discharge current, pulse time ratio and spark voltage were taken as variable parameters and Taguchi L9 array was established to identify design of experiments (DOE) that are used for experimentation of each of the two configurations. It is found that the multi-material electrodes behave differently in different configurations under the same parametric conditions. Additionally, the differences as created on the machined surface by each of the material in either configuration yield interesting results which indicate feasibility of generating patterns/impressions in a single experiment run. The interfacial gaps as created between the cladded electrodes post machining are also quantified for evaluation of limitations. It is found that copperin- graphiteout configuration gives a maximum surface roughness value differential of 3.1 µm between the sections machined by individual materials in this configuration at certain parametric condition. Also, discharge current 4A, pulse time ratio 1.5 and spark voltage 6 V generate impression/pattern with a maximum depth of cut difference in both configurations (0.8 mm for copperin- graphiteout and 0.04 mm for graphitein- copperout). The interface gap at experiment condition where maximum height difference Δhmax. (mm) is achieved, is only around 5 % of the maximum interface gap for both configurations which indicates that the depth impressions could be generated without introducing much gap within cladded electrode interfaces.
科研通智能强力驱动
Strongly Powered by AbleSci AI