Effect of high cutting speed on surface integrity of AISI 4340 steel during turning

1990 ◽  
Vol 6 (4) ◽  
pp. 371-375 ◽  
Author(s):  
A. B. Sadat
1976 ◽  
Vol 98 (3) ◽  
pp. 999-1006 ◽  
Author(s):  
J. A. Bailey ◽  
S. Jeelani ◽  
S. E. Becker

The effect of cutting speed and tool wear land length on the surface integrity of quenched and tempered AISI 4340 steel machined under dry, unlubricated orthogonal conditions is determined. The surface region of machined test pieces is examined using optical microscopy, scanning electron microscopy, X-ray microprobe analysis, microhardness measurements, and profilometry. In addition, tool forces are measured and tool temperatures calculated. The results of the investigation show that during machining a damaged surface region is produced which is quite different from the bulk of the material. It is found when cutting at low speeds with sharp cutting tools that the damage is restricted to a variety of geometrical defects associated with the surface. It is found when cutting at high speeds or with tools having large artificially controlled wear lands that considerable subsurface damage involving changes in metallurgical structure and hardness is produced. The results are interpreted in terms of the type of chip produced during machining, the temperatures generated during machining, and the interaction between the tool nose region and workpiece. It is suggested that observations based on scanning electron microscopy are more indicative of the true surface condition than surface roughness measurements.


SINERGI ◽  
2019 ◽  
Vol 23 (2) ◽  
pp. 139
Author(s):  
M. Sobron Yamin Lubis ◽  
Erwin Siahaan ◽  
Steven Darmawan ◽  
Adianto Adianto ◽  
Ronald Ronald

In the metal machining process, cutting speed and feed rate are cutting parameters that affect the surface quality of the workpiece produced. The use of improper cutting parameters can cause the workpiece surface to be rough, and the cutting toolage to be shorter. This study was conducted to determine the effect of cutting parameters and the use of carbide tools on the surface roughness of metal steel workpieces. The research was carried out using the experimental method of AISI 4340 steel metal workpiece turning using cutting tool coated. Five variations of cutting speed used are: 140 m/min, 150 m/min, 160 m/min, 170 m/min, 180 m/min and three variations in feed rate: 0.25 mm/rev, 0.3 mm/rev, 0.35 mm/rev. After the turning process, the surface roughness of the workpiece is measured using a surface tester. From the results of the study, it was found that the surface roughness value was directly proportional to the feed rate and inversely proportional to the cutting speed. The smallest surface roughness value is 9.56 μm on cutting speed 180 m / min, and feed rate is 0.25 mm/rev. 


2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
M. Kaladhar

PurposeThe present study spotlights the single and multicriteria decision-making (MCDM) methods to determine the optimal machining conditions and the predictive modeling for surface roughness (Ra) and cutting tool flank wear (VB) while hard turning of AISI 4340 steel (35 HRC) under dry environment.Design/methodology/approachIn this study, Taguchi L16 design of experiments methodology was chosen. The experiments were performed under dry machining conditions using TiSiN-TiAlN nanolaminate PVD-coated cutting tool on which Taguchi and responses surface methodology (RSM) for single objective optimization and MCDM methods like the multi-objective optimization by ratio analysis (MOORA) were applied to attain optimal set of machining parameters. The predictive models for each response and multiresponse were developed using RSM-based regression analysis. S/N ratios, analysis of variance (ANOVA), Pareto diagram, Tukey's HSD test were carried out on experimental data for profound analysis.FindingsOptimal set of machining parameters were obtained as cutting speed: at 180 m/min., feed rate: 0.05 mm/rev., and depth of cut: 0.15 mm; cutting speed: 145 m/min., feed rate: 0.20 mm/rev. and depth of cut: 0.1 mm for Ra and VB, respectively. ANOVA showed feed rate (96.97%) and cutting speed (58.9%) are dominant factors for Ra and VB, respectively. A remarkable improvement observed in Ra (64.05%) and VB (69.94%) after conducting confirmation tests. The results obtained through the MOORA method showed the optimal set of machining parameters (cutting speed = 180 m/min, feed rate = 0.15 mm/rev and depth of cut = 0.25 mm) for minimizing the Ra and VB.Originality/valueThis work contributes to realistic application for manufacturing industries those dealing with AISI 4340 steel of 35 HRC. The research contribution of present work including the predictive models will provide some useful guidelines in the field of manufacturing, in particular, manufacturing of gear shafts for power transmission, turbine shafts, fasteners, etc.


Author(s):  
Chathakudath Sukumaran Sumesh ◽  
Dawood Sheriff Akbar ◽  
Hari Shankar Purandharadass ◽  
Raghunandan J. Chandrasekaran

Turning is one of the most used metal removal operations in the industry. It can remove material faster, giving reasonably good surface quality apart from geometrical requirements. Conformity of geometry is one of the most significant requirements of turned components to perform their intended functions. Apart from dimensional requirements, the important geometrical necessities are Circularity, Straightness, Cylindricity, Perpendicularity, etc. Since they have a direct influence on the functioning of the components, the effect of the cutting parameters on them has greater significance. In this paper experiments are carried out to examine the effect of turning parameters such as cutting speed, feed rate, and depth of cut on responses like; straightness, roundness, surface roughness, and material removal rate during turning of AISI 4340 steel. Analysis of Variance (ANOVA) is performed and the influence of parameters on each response is studied. The optimal values of parameters obtained from the study are further confirmed by conducting experiments.


Sign in / Sign up

Export Citation Format

Share Document