Machining of shape memory alloys(SMAs)without losing the shape memory effect could immensely extend their applications.Herein,the wire electric discharge machining process was used to machine NiTi—a shape memory allo...Machining of shape memory alloys(SMAs)without losing the shape memory effect could immensely extend their applications.Herein,the wire electric discharge machining process was used to machine NiTi—a shape memory alloy.The experimental methodology was designed using a Box-Behnken design approach of the response surface methodology.The effects of input variables including pulse on time,pulse off time,and current were investigated on the material removal rate,surface roughness,and microhardness.ANOVA tests were performed to check the robustness of the generated empirical models.Optimization of the process parameters was performed using a newly formulated,highly efficient heat transfer search algorithm.Validation tests were conducted and extended for analyzing the retention of the shape memory effect of the machined surface by differential scanning calorimetry.In addition,2D and 3D Pareto curves were generated that indicated the trade-offs between the selected output variables during the simultaneous output variables using the multi-objective heat transfer search algorithm.The optimization route yielded encouraging results.Single objective optimization yielded a maximum material removal rate of 1.49 mm^(3)/s,maximum microhardness 462.52 HVN,and minimum surface roughness 0.11μm.The Pareto curves showed conflicting effects during the wire electric discharge machining of the shape memory alloy and presented a set of optimal non-dominant solutions.The shape memory alloy machined using the optimized process parameters even indicated a shape memory effect similar to that of the starting base material.展开更多
文摘Machining of shape memory alloys(SMAs)without losing the shape memory effect could immensely extend their applications.Herein,the wire electric discharge machining process was used to machine NiTi—a shape memory alloy.The experimental methodology was designed using a Box-Behnken design approach of the response surface methodology.The effects of input variables including pulse on time,pulse off time,and current were investigated on the material removal rate,surface roughness,and microhardness.ANOVA tests were performed to check the robustness of the generated empirical models.Optimization of the process parameters was performed using a newly formulated,highly efficient heat transfer search algorithm.Validation tests were conducted and extended for analyzing the retention of the shape memory effect of the machined surface by differential scanning calorimetry.In addition,2D and 3D Pareto curves were generated that indicated the trade-offs between the selected output variables during the simultaneous output variables using the multi-objective heat transfer search algorithm.The optimization route yielded encouraging results.Single objective optimization yielded a maximum material removal rate of 1.49 mm^(3)/s,maximum microhardness 462.52 HVN,and minimum surface roughness 0.11μm.The Pareto curves showed conflicting effects during the wire electric discharge machining of the shape memory alloy and presented a set of optimal non-dominant solutions.The shape memory alloy machined using the optimized process parameters even indicated a shape memory effect similar to that of the starting base material.
