scholarly journals Application of TOPSIS for multi response optimization of Process Parameters in dry hard turning of AISI 52100 steel

2021 ◽  
Vol 13 (1) ◽  
pp. 211-224
Author(s):  
P. UMAMAHESWARRAO ◽  
D. RANGARAJU ◽  
K. N. S. SUMAN ◽  
B. RAVISANKAR
Keyword(s):  
Surface Roughness ◽  
Process Parameters ◽  
Hard Turning ◽  
Rake Angle ◽  
Depth Of Cut ◽  
Nose Radius ◽  
Workpiece Surface ◽  
Aisi 52100 ◽  
Machining Force ◽  
Aisi 52100 Steel

In the present work by employing the Technique for order of preference by similarity to ideal solution (TOPSIS) machining parameters optimization is performed with polycrystalline cubic boron nitride (PCBN) tools while AISI 52100 steel hard turning (HT). Based on the CCD of RSM, 32 experimental runs were performed by varying cutting speed, feed, depth of cut, nose radius, and negative rake angle to identify the optimal level of the process parameters. In this study, the multiple performance characteristics measured are machining force, surface roughness, and workpiece surface temperature. To ascertain the impact of cutting parameters on responses, Analysis of Variance (ANOVA) was deployed. An optimum combination of input process parameters for the multiple performance characteristics should be as follows: speed 200 rpm, feed 0.1 mm/rev, depth of cut 0.8 mm, nose radius 1.2 mm, and negative rake angle 45º leading to the value of optimum response variables machining force 561.163 N, Surface roughness 0.507μm and workpiece surface temperature 84.38°C.

scholarly journals Machining force comparison for surface defect hard turning and conventional hard turning of AISI 52100 steel

2021 ◽  
Vol 13 (3) ◽  
pp. 205-214
Author(s):  
P. U MAMAHESWARRAO ◽  
D. RANGARAJU ◽  
K. N. S. SUMAN ◽  
B. RAVISANKAR
Keyword(s):  
Hard Turning ◽  
Surface Defect ◽  
Cutting Speed ◽  
Tool Geometry ◽  
Depth Of Cut ◽  
Nose Radius ◽  
Aisi 52100 ◽  
Machining Force ◽  
Aisi 52100 Steel ◽  
The Impact

In this article, a recently developed method called surface defect machining (SDM) for hard turning has been adopted and termed surface defect hard turning (SDHT). The main purpose of the present study was to explore the impact of cutting parameters like cutting speed, feed, depth of cut, and tool geometry parameters such as nose radius and negative rake angle of the machining force during surface defect hard turning (SDHT) of AISI 52100 steel in dry condition with Polycrystalline cubic boron nitride (PCBN) tool; and results were compared with conventional hard turning (CHT). Experimentation is devised and executed as per Central Composite Design (CCD) of Response Surface Methodology (RSM). Results reported that an average machining force was decreased by 22% for surface defect hard turning (SDHT) compared to conventional hard turning (CHT).

Achieving Optimal Process Parameters during Hard Turning of AISI 52100 Bearing Steel Using Hybrid GRA-PCA

2019 ◽  
Vol 818 ◽  
pp. 87-91 ◽  
Author(s):  
P. Umamaheswarrao ◽  
D. Ranga Raju ◽  
K.N.S. Suman ◽  
B. Ravi Sankar
Keyword(s):  
Hard Turning ◽  
Cubic Boron Nitride ◽  
Cutting Speed ◽  
Cutting Parameters ◽  
Rake Angle ◽  
Bearing Steel ◽  
Depth Of Cut ◽  
Nose Radius ◽  
Aisi 52100 ◽  
Input Parameters

In the present work hard turning of AISI 52100 steel has been performed using Polycrystalline cubic boron nitride (PCBN) tools. The input parameters considered are cutting speed, feed, depth of cut, nose radius and negative rake angle and the measured responses are machining force and workpiece surface temperature. Experiments are planned as per Central Composite Design (CCD) of Response Surface Methodology (RSM). The effect of input parameters and their interactions are discussed with main effects plot. Further, the multi-objective optimization scheme is proposed by adopting Grey Relational Analysis (GRA) coupled with Principle Component Analysis (PCA). Results demonstrated that speed is the most significant factor affecting the responses followed by negative rake angle, feed, depth of cut, and nose radius. The optimum cutting parameters obtained are cutting speed 1000 rpm, feed 0.02 mm/rev, depth of cut 0.5 mm, Nose radius 1 mm and Negative rake angle 5o.

Parametric Investigations on Surface Roughness of Hard Turned AISI 52100 Steel

2017 ◽  
Vol 867 ◽  
pp. 171-176 ◽  
Author(s):  
B. Ravi Sankar ◽  
P. Umamaheswarrao ◽  
Shaik Nawaz Sharief ◽  
T. Suresh ◽  
Rayudu Raju
Keyword(s):  
Surface Roughness ◽  
Interaction Effect ◽  
Hard Turning ◽  
Cutting Tools ◽  
Great Influence ◽  
Bearing Steel ◽  
Nose Radius ◽  
Aisi 52100 ◽  
Aisi 52100 Steel ◽  
Main Effects

The present work is aimed to investigate the effect of the turning parameters on the surface roughness produced during hard turning of AISI 52100 bearing steel with PCBN cutting tools. The experiments are devised using Taguchi L27 orthogonal array and analysis is carried out using MINITAB 14 software. The influence of individual parameters is discussed with main effects plot and the combined parametric effect is presented with interaction effects plot. From the results it is observed that speed and nose radius has a great influence on surface roughness. The interaction effect is significant for speed and feed combination.

A Regression Model for Force and Surface Roughness Estimation during Hard Turning

2011 ◽  
Vol 299-300 ◽  
pp. 1167-1170 ◽  
Author(s):  
Gaurav Bartarya ◽  
S.K. Choudhury
Keyword(s):  
Surface Roughness ◽  
Hard Turning ◽  
Goodness Of Fit ◽  
Cutting Parameters ◽  
Anova Analysis ◽  
Aisi 52100 ◽  
Aisi 52100 Steel ◽  
Factorial Design Of Experiments ◽  
Full Factorial ◽  
Surface Roughness Estimation

Forces in Hard turning can be used to evaluate the performance of the process. Cutting parameters have their own influence on the cutting forces on the tool. The present work is an attempt to develop a force prediction model based on full factorial design of experiments for machining EN31 steel (equivalent to AISI 52100 steel) using uncoated CBN tool. The force and surface roughness regression models were developed using the data from various set of experiments with in the range of parameters selected. The predictions from the models were compared with the measured force and surface roughness values. The ANOVA analysis was undertaken to test the goodness of fit of data.

scholarly journals TOPSIS BASED OPTIMIZATION OF PROCESS PARAMETERS WHILE HARD TURNING OF AISI 52100 STEEL

2019 ◽  
Vol 2 (2) ◽  
pp. 28-31 ◽  
Author(s):  
P. Umamaheswarrao ◽  
D. Ranga Raju ◽  
Kns Suman ◽  
B. Ravi Sankar
Keyword(s):  
Process Parameters ◽  
Hard Turning ◽  
Optimization Of Process Parameters ◽  
Aisi 52100 ◽  
Aisi 52100 Steel
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