The wire electrical discharge machining（EDM） of 6061 aluminium alloy in terms of material removal rate,kerf/slit width,surface finish and wear of electrode wire for different pulse on time and wire tension was studi...The wire electrical discharge machining（EDM） of 6061 aluminium alloy in terms of material removal rate,kerf/slit width,surface finish and wear of electrode wire for different pulse on time and wire tension was studied.Eight experiments were carried out in a wire EDM machine by varying pulse on time and wire tension.It is found that the material removal rate increases with the increase of pulse on time though the wire tension does not affect the material removal rate.It seems that the higher wire tension facilitates steady machining process,which generates low wear in wire electrode and better surface finish.The surface roughness does not change notably with the variation of pulse on time.The appearance of the machined surfaces is very similar under all the machining conditions.The machined surface contains solidified molten material,splash of materials and blisters.The increase of the pulse on time increases the wear of wire electrode due to the increase of heat input.The wear of wire electrode generates tapered slot which has higher kerf width at top side than that at bottom side.The higher electrode wear introduces higher taper.展开更多
Experimentation data of perspex glass sheet cutting, using CO2 laser, with missing values were modelled with semi-supervised artificial neural networks. Factorial design of experiment was selected for the verification...Experimentation data of perspex glass sheet cutting, using CO2 laser, with missing values were modelled with semi-supervised artificial neural networks. Factorial design of experiment was selected for the verification of orthogonal array based model prediction. It shows improvement in modelling of edge quality and kerf width by applying semi-supervised learning algorithm, based on novel error assessment on simulations. The results are expected to depict better prediction on average by utilizing the systematic randomized techniques to initialize the neural network weights and increase the number of initialization. Missing values handling is difficult with statistical tools and supervised learning techniques; on the other hand, semi-supervised learning generates better results with the smallest datasets even with missing values.展开更多
This paper describes the application of orthogonal test design coupled with non-linear regression analysis to optimize abrasive suspension jet （AS J） cutting process and construct its cutting model. Orthogonal test ...This paper describes the application of orthogonal test design coupled with non-linear regression analysis to optimize abrasive suspension jet （AS J） cutting process and construct its cutting model. Orthogonal test design is applied to cutting stainless steel. Through range analysis on experiment results, the optimal process conditions for the cutting depth and the kerr ratio of the bottom width to the top width can be determined. In addition, the analysis of ranges and variances are all employed to identify various factors： traverse rate, working pressure, nozzle diameter, standoff distance which denote the importance order of the cutting parameters affecting cutting depth and the kerf ratio of the bottom width to the top width. ~rthermore, non-linear regression analysis is used to establish the mathematical models of the cutting parameters based on the cutting depth and the kerr ratio. Finally, the verification experiments of cutting parameters＇ effect on cutting performance, which show that optimized cutting parameters and cutting model can significantly improve the prediction of the cutting ability and quality of ASJ.展开更多
WEDM is used in machining conductive materials where it is required to obtained complicated and intricate shapes with high accuracy.Various applications are in the field of automobile,medical industries,aerospace etc....WEDM is used in machining conductive materials where it is required to obtained complicated and intricate shapes with high accuracy.Various applications are in the field of automobile,medical industries,aerospace etc.WEDM is an economical machining option with short product development cycle.Surface roughness,kerf width,Material removal rate,Recast layer hardness and surface microhardness in WEDM are most important responses.In this paper,effect of varied Wire tension on SR,KW,MRR,RCL hardness and surface microhardness on AISI 304 have been investigated.Pulse on time,pulse off time,current and dielectric fluid are taken as fixed parameter.Results show that Wire tension influences the SR,MRR and Surface microhardness and has no effect on kerf width in case of Stainless steel304.展开更多
文摘The wire electrical discharge machining（EDM） of 6061 aluminium alloy in terms of material removal rate,kerf/slit width,surface finish and wear of electrode wire for different pulse on time and wire tension was studied.Eight experiments were carried out in a wire EDM machine by varying pulse on time and wire tension.It is found that the material removal rate increases with the increase of pulse on time though the wire tension does not affect the material removal rate.It seems that the higher wire tension facilitates steady machining process,which generates low wear in wire electrode and better surface finish.The surface roughness does not change notably with the variation of pulse on time.The appearance of the machined surfaces is very similar under all the machining conditions.The machined surface contains solidified molten material,splash of materials and blisters.The increase of the pulse on time increases the wear of wire electrode due to the increase of heat input.The wear of wire electrode generates tapered slot which has higher kerf width at top side than that at bottom side.The higher electrode wear introduces higher taper.
文摘Experimentation data of perspex glass sheet cutting, using CO2 laser, with missing values were modelled with semi-supervised artificial neural networks. Factorial design of experiment was selected for the verification of orthogonal array based model prediction. It shows improvement in modelling of edge quality and kerf width by applying semi-supervised learning algorithm, based on novel error assessment on simulations. The results are expected to depict better prediction on average by utilizing the systematic randomized techniques to initialize the neural network weights and increase the number of initialization. Missing values handling is difficult with statistical tools and supervised learning techniques; on the other hand, semi-supervised learning generates better results with the smallest datasets even with missing values.
基金supported by the Science and Technology Development Foundation of Shanghai Municipal Science and Technology Commission (Grant No.037252022)
文摘This paper describes the application of orthogonal test design coupled with non-linear regression analysis to optimize abrasive suspension jet （AS J） cutting process and construct its cutting model. Orthogonal test design is applied to cutting stainless steel. Through range analysis on experiment results, the optimal process conditions for the cutting depth and the kerr ratio of the bottom width to the top width can be determined. In addition, the analysis of ranges and variances are all employed to identify various factors： traverse rate, working pressure, nozzle diameter, standoff distance which denote the importance order of the cutting parameters affecting cutting depth and the kerf ratio of the bottom width to the top width. ~rthermore, non-linear regression analysis is used to establish the mathematical models of the cutting parameters based on the cutting depth and the kerr ratio. Finally, the verification experiments of cutting parameters＇ effect on cutting performance, which show that optimized cutting parameters and cutting model can significantly improve the prediction of the cutting ability and quality of ASJ.
文摘WEDM is used in machining conductive materials where it is required to obtained complicated and intricate shapes with high accuracy.Various applications are in the field of automobile,medical industries,aerospace etc.WEDM is an economical machining option with short product development cycle.Surface roughness,kerf width,Material removal rate,Recast layer hardness and surface microhardness in WEDM are most important responses.In this paper,effect of varied Wire tension on SR,KW,MRR,RCL hardness and surface microhardness on AISI 304 have been investigated.Pulse on time,pulse off time,current and dielectric fluid are taken as fixed parameter.Results show that Wire tension influences the SR,MRR and Surface microhardness and has no effect on kerf width in case of Stainless steel304.
