摘要：The present work involves in finding the optimal combination of cutting parameters, in dry turning of EN19 steel using a tungsten carbide tool of nose radius 0.4 mm. The experiments were conducted on a CNC turret lathe as per the designed L9 (3^3) orthogonal array. In order to optimize the Material Removal Rate (MRR), Arithmetic Average Roughness (R a ) and Average Peak - to - Valley Height Roughness (R z ) individually, Single objective Taguchi method has been employed. From the results, the optimal combination of cutting parameters for MRR is found at: 225 m/min, 0.15 mm/rev and 0.6 mm . Optimal combination of R a and R z is found at: 225 m/min, 0.05 mm/rev and 0.6 mm. A nalysis of variance (ANOVA) is used to find the influence of cutting parameters on the responses. ANOVA results re vealed that speed and feed has high influence on MRR . S peed has high influence in affecting the Roughness parameters. Linear regression models for the responses were prepared using the MINITAB - 16 software. From the results, it is found that the models prepared are more significant and accurate.
关键词：EN19 steel; ; ; Surface ; roughness; ; Taguchi; Regression; ; ; ANOVA. ; ; ; ; ; var currentpos;timer; function initialize() { timer=setInterval("scrollwindow()";10);} function sc(){clearInterval(timer); }function scrollwindow() { currentpos=document.body.scrollTop; window.scroll(0;++currentpos); if (currentpos != document.body.scrollTop) sc();} document.onmousedown=scdocument.ondblclick=initialize Maheswara Rao Ch.; Venkatasubbaiah K.; Suresh Ch. / International Journal of Lean Thinking ; Volume 7; Issue 2 (December 2016) ; ; 25 ; ; 1. Introduction ; In manufacturing industries; the challenges that the engineers come across are to find the optimal cutting ; parameters for the desired output and to maximize the performance using the available resources. In ; metal cutting processes; the fundamental metal removal operation is turning. In turning; the major ; desired outputs are material removal rate; productivity; quality; machining time; tool life and machining ; cost; etc. (H yanda et al. (2010); H K Vijaya Kumar et al. (2014)) C Ibrahim; 2006 conducted ; experiments to find the effect of cutting parameters on surface roughness in the machining of AISI304 ; and AISI316 steels using CVD multi-layer coated cemented carbide tools. The results showed that the ; cutting speed has high significance on surface roughness. G Shivam et al. (2016) conducted experiments ; on CNC lathe by taking cutting speed; feed and depth of cut as process parameters and MRR and SR as ; outputs. The Cutting speed and depth of cut are the most influencing parameters on surface roughness ; and material removal rate respectively. ; ; In the present work; an experiment has been made to find the ; optimal combination of cutting parameters and their influence on Material Removal Rate (MRR) and ; Surface Roughness (R ; a ; and R ; z ; ) characteristics. There are many factors which influence the responses. ; (R Gupta and A Diwedi; 2014; K Pavan Kumar Reddy et al. (2014)) Surface roughness is referred as ; the deviations measured from the mean value. It depends on many factors like machining parameters ; (Cutting speed; feed rate; depth of cut; cutting fluid); cutting tool properties (Tool material; tool shape; ; nose radius; rake angle; cutting edge; side cutting edge angle); work piece properties (hardness; length ; and diameter) and cutting phenomenon (Cutting force vibrations; chip formations; friction in the cutting ; zone); etc. ; ; (T Rama Krishna et al. (2014)) S Devendra et al. (2016) conducted a study to investigate the ; effect of nose radius on surface roughness in CNC turning of Aluminium 6061 in dry condition. Nose ; radius is identified as the most influencing parameter on surface roughness. S R Bheem et al. (2015) ; investigated the effect of cutting parameters on surface roughness and material removal rate during the ; turning of metal matrix composite. Results revealed that the feed is the most influencing parameter on ; surface roughness followed by the depth of cut and speed. It is customary to optimize all the influencing ; parameters in order to achieve a high material removal rate and good surface finish. Surface finish plays ; an important role in the evaluation of the quality of the product. Surface roughness affects the major ; functional attributes like contact causing surface friction; wear; light reflection; heat transmission; ability ; of distributing and holding a lubricant; coating and fatigue resistance; etc. (D Selvaraj and P ; Chandramohan; 2010) F Vishal; 2013 employed Taguchi method and Analysis of variance to find out ; the influence of cutting parameters on material removal rate and surface roughness. Feed rate is found ; to be the most influencing parameter on the surface roughness. Y Sahijpaul and S Gurpreet; 2013 ; analyzed the effect of cutting parameters on surface roughness while turning of EN8 steel. They ; concluded that the feed rate is the most influencing parameter on the surface roughness. ; ; The Surface ; roughness can be measured in terms of various parameters like R ; a ; ; R ; q ; ; R ; z ; ; R ; t ; ; R ; v ; ; R ; p ; ; R ; pm ; ; S ; k ; and K; etc. ; Where; R ; a ; : Arithmetic Average (AA) or Centre Line Average (CLA); R ; q ; : Root Mean Square (RMS); ; R ; z ; : Average Peak-to-Valley height; R ; t ; : Extreme value height descriptor (R ; y ; ; R ; max ; ) or Maximum Peak- ; to-Valley height; R ; v ; : Maximum valley depth (or) Mean to Lowest Valley height; R ; p ; : Maximum Peak ; height (or) Maximum Peak to Mean height; R ; pm ; : Average Peak to mean height; S ; k ; : Skewness and K: ; Kurtosis; etc. Among all the roughness parameters; R ; a ; and R ; z ; are most significant from contact stiffness ; and surface wear point of view. (Ch Maheswara Rao and K Venkatasubbaiah; 2016a; Ch Maheswara ; Rao and K Venkatasubbaiah; 2016c) Hence; in this work Arithmetic Average (R ; a ; ) and Average Peak- ; to-Valley height (R ; z ; ) are considered as the major experimental responses along with the material ; removal rate (MRR). ; For the present work; medium carbon steel EN19 is considered as work piece. EN19 steel is significant ; and most commonly used material because of its exclusive properties like high tensile strength; good
