Current machining studies have reported effects of prevalent and common factors,while ultra⁃high finish requires holistic approach to identify all factors and investigate their effects on machining of hard to machine ...Current machining studies have reported effects of prevalent and common factors,while ultra⁃high finish requires holistic approach to identify all factors and investigate their effects on machining of hard to machine materials.In this work,a less investigated yet important factor,roughness of the uncut surface,was studied,and its effects on the individual response,i.e.,surface finish of the machined part,were found to be significant.AISI 316,which is mainly applied in strategic areas,was selected and three effective turning factors,cutting speed(A),feed rate(B),and roughness of the uncut surface(C)on three output responses including surface roughness of the machined surface(Ra),microhardness(HV),and material removal rate(MRR),were reported.Further,single response optimization of the individual output response and multi⁃response optimization of all the three responses were carried out.Taguchi L9 orthogonal array based signal⁃to⁃noise(S/N)ratio method was used for individual response optimization,and grey relational analysis(GRA)was employed for multi⁃response optimization.Effects of the process factors on the output responses were evaluated through inclusive statistical analyses.The individual response optimization revealed that there was a considerable effect of roughness of the uncut surface on the machining performance.Results of the GRA illustrated that the speed during the cutting process and the feed rate had substantial trace on the surface integrity(indicated by Ra and HV)and production rate(indicated by MRR),while roughness of the uncut surface did not have a significant effect.展开更多
文摘Current machining studies have reported effects of prevalent and common factors,while ultra⁃high finish requires holistic approach to identify all factors and investigate their effects on machining of hard to machine materials.In this work,a less investigated yet important factor,roughness of the uncut surface,was studied,and its effects on the individual response,i.e.,surface finish of the machined part,were found to be significant.AISI 316,which is mainly applied in strategic areas,was selected and three effective turning factors,cutting speed(A),feed rate(B),and roughness of the uncut surface(C)on three output responses including surface roughness of the machined surface(Ra),microhardness(HV),and material removal rate(MRR),were reported.Further,single response optimization of the individual output response and multi⁃response optimization of all the three responses were carried out.Taguchi L9 orthogonal array based signal⁃to⁃noise(S/N)ratio method was used for individual response optimization,and grey relational analysis(GRA)was employed for multi⁃response optimization.Effects of the process factors on the output responses were evaluated through inclusive statistical analyses.The individual response optimization revealed that there was a considerable effect of roughness of the uncut surface on the machining performance.Results of the GRA illustrated that the speed during the cutting process and the feed rate had substantial trace on the surface integrity(indicated by Ra and HV)and production rate(indicated by MRR),while roughness of the uncut surface did not have a significant effect.
