scholarly journals Optimization on Cryogenic Co2 Machining Parameters of AISI D2 Steel using Taguchi Based Grey Relational Approach and TOPSIS

2018 ◽  
Vol 7 (3.12) ◽  
pp. 885 ◽  
Author(s):  
V Balaji ◽  
S Ravi ◽  
P Naveen Chandran
Keyword(s):  
Performance Measures ◽  
Process Parameters ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Influence Of Process Parameters ◽  
Aisi D2 Steel ◽  
Aisi D2 ◽  
Grey Relational ◽  
Coated Carbide ◽  
D2 Steel

The Machinability, and the process parameter optimization of Cryogenic CO2 machining operation for AISI D2 steel have been investigated  based on the Taguchi based grey approach and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS).In this examination work, the measure of the work materials utilized was AISI D2 Steel of size is 150mm × 50 mm × 50m with SANDWIK influence CVD To TiN coated carbide cutting insert tool device embed was utilized. The time taken for machining is 5 min and profundity of cut were kept up steady with various lower cutting velocities, and diverse encourage rate. An L27 orthogonal array was selected for planning the experiment. Cutting speed, depth of cut and feed rate were considered as input process parameters. Cutting force (Fz) and surface roughness (Ra) were considered as the performance measures. These performance measures were optimized for the improvement of machinability, quality of product. A comparison is made between the multi-criteria decision making tools. Grey Relational Analysis (GRA) and TOPSIS are used to confirm and prove the similarity. To determine the influence of process parameters, Analysis of Variance (ANOVA) is employed. The end results of experimental investigation proved that the machining performance can be enhanced effectively with the assistance of the proposed approaches.   

Sustainable machining. Modeling and optimization of temperature and surface roughness in the milling of AISI D2 steel

2019 ◽  
Vol 71 (2) ◽  
pp. 267-277 ◽  
Author(s):  
Aqib Mashood Khan ◽  
Muhammad Jamil ◽  
Ahsan Ul Haq ◽  
Salman Hussain ◽  
Longhui Meng ◽  
...  
Keyword(s):  
Surface Roughness ◽  
Process Parameters ◽  
Empirical Modeling ◽  
Cutting Fluid ◽  
Depth Of Cut ◽  
Aisi D2 Steel ◽  
Content Type ◽  
Sustainable Machining ◽  
Aisi D2 ◽  
D2 Steel

Purpose Sustainable machining is a global consensus and the necessity to cope up the serious environmental threats. Minimum quantity lubrication (MQL) and nanofluids-based MQL(NFMQL) are state-of-the-art sustainable lubrication modes. The purpose of this study is to investigate the effect of process parameters, such as feed rate, depth of cut and cutting fluid flow rate, on temperature and surface roughness of the manufactured pieces during face milling of the AISI D2 steel. Design/methodology/approach A statistical technique called response surface methodology with Box–Behnken Design was used to design experimental runs, and empirical modeling was presented. Analysis of variance was carried out to evaluate the model’s accuracy and the validation of the applied technique. Findings A comprehensive analysis revealed the superiority of implementing NFMQL in comparison to MQL within the levels of process parameters. The comparison has shown a significant reduction of temperature under NFMQL at the tool-workpiece interface from 16.2 to 34.5 per cent and surface roughness from 11.3 to 12 per cent. Practical implications This research is useful for practitioners to predict the responses in workshop and select appropriate cutting parameters. Moreover, this research will be helpful to reduce the resource which will ultimately save energy consumption and cost. Originality/value To cope with the industrial challenges and tribological issues associated with the milling of AISI D2 steel, experiments were conducted in a distinct machining mode with innovative cooling/lubrication. Until now, few studies have addressed the key lubrication effects of Al2O3-based nanofluid on the machinability of D2 steel under NFMQL lubrication condition.

scholarly journals Optimization on Turning Parameters of 15-5PH Stainless Steel Using Taguchi Based Grey Approach and Topsis

2016 ◽  
Vol 63 (3) ◽  
pp. 397-412 ◽  
Author(s):  
D. Palanisamy ◽  
P. Senthil
Keyword(s):  
Stainless Steel ◽  
Performance Measures ◽  
Process Parameters ◽  
Cutting Speed ◽  
Depth Of Cut ◽  
Machining Performance ◽  
Influence Of Process Parameters ◽  
Order Preference ◽  
Grey Relational

Abstract The machinability and the process parameter optimization of turning operation for 15-5 Precipitation Hardening (PH) stainless steel have been investigated based on the Taguchi based grey approach and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). An L27 orthogonal array was selected for planning the experiment. Cutting speed, depth of cut and feed rate were considered as input process parameters. Cutting force (Fz) and surface roughness (Ra) were considered as the performance measures. These performance measures were optimized for the improvement of machinability quality of product. A comparison is made between the multi-criteria decision making tools. Grey Relational Analysis (GRA) and TOPSIS are used to confirm and prove the similarity. To determine the influence of process parameters, Analysis of Variance (ANOVA) is employed. The end results of experimental investigation proved that the machining performance can be enhanced effectively with the assistance of the proposed approaches.

Hard Turning of AISI D2 Steel by Polycrystalline Cubic Boron Nitride (PCBN)

2015 ◽  
Vol 766-767 ◽  
pp. 649-654
Author(s):  
A. Srithar ◽  
K. Palanikumar ◽  
B. Durgaprasad
Keyword(s):  
Boron Nitride ◽  
Hard Turning ◽  
Cubic Boron Nitride ◽  
Machining Process ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Aisi D2 Steel ◽  
Polycrystalline Cubic Boron Nitride ◽  
Aisi D2 ◽  
D2 Steel

The machining of hard turning is performed on hardened steel in the range of 45 to 68 Rockwell hardness using a variety of tool materials such as Polycrystalline cubic boron nitride (PCBN) , Polycrystalline diamond (PCD) and Cubic boron nitride (CBN). It is an alternative to conventional grinding process is a flexible and effective machining process for hardened metals and hence broadly used in various applications such as dies, moulds, tools, gears, cams, shafts, axles, bearings and forgings. Although the process is performed within small depth of cut and feed rates, estimates to reduce machining time as high as 60 % in hard turning. This paper discusses the importance of hard turning of AISI D2 steel. In this study, Experimental investigations are carried out on conventional lathe using prefixed the cutting conditions. The responses studied in the investigation are cutting forces (Fa, Ft and Fz). The cutting parameters considered for the investigation are cutting speed, feed and depth of cut. The influence of machining parameters on response is studied and presented in detail.

Optimization and Performance Analysis of Uncoated and Coated Carbide Inserts during Hard Turning AISI D2 Steel Using Hybrid GRA-PCA Technique

2016 ◽  
Vol 852 ◽  
pp. 151-159 ◽  
Author(s):  
N. Senthilkumar ◽  
V. Selvakumar ◽  
T. Tamizharasan
Keyword(s):  
Tool Wear ◽  
Optimization Technique ◽  
Principal Component ◽  
Aisi D2 Steel ◽  
Aisi D2 ◽  
Four Levels ◽  
Grey Relational ◽  
Coated Carbide ◽  
Coated Cemented Carbide ◽  
D2 Steel

In this analysis turning parameter optimization is performed during machining AISI D2 steel with uncoated and coated cemented carbide cutting inserts using a hybrid multi-objective optimization technique Grey relational analysis (GRA) and Principal Component analysis (PCA). A L16 Taguchi’s orthogonal array design is selected for basic experimental design considering four levels for the chosen four parameters. Output performance measures viz., tool wear, roughness on finished surface and material removed are evaluated by determining grey relational coefficient, and deriving multi response performance index (MRPI) using principal components. Contribution of coated cutting insert is 72.87% towards the MRPI and 17.15% contribution by feed rate, as determined from Analysis of Variance (ANOVA). Confirmation experiment performed with optimum conditions provides lower tool wear, higher material removal and good surface finish. The MRPI of the confirmation experiment is also confirmed by calculating the confidence interval.

DEVELOPMENT OF SURFACE ROUGHNESS PREDICTION MODEL FOR HARD TURNING ON AISI D2 STEEL USING CUBIC BORON NITRIDE INSERT

2017 ◽  
Vol 80 (1) ◽  
Author(s):  
Amrifan Saladin Mohruni ◽  
Muhammad Yanis ◽  
Edwin Kurniawan
Keyword(s):  
Surface Roughness ◽  
Boron Nitride ◽  
Feed Rate ◽  
Hard Turning ◽  
Cubic Boron Nitride ◽  
Cutting Speed ◽  
Machining Parameters ◽  
Aisi D2 Steel ◽  
Aisi D2 ◽  
D2 Steel

Hard turning is an alternative to traditional grinding in the manufacturing industry for hardened ferrous alloy material above 45 HRC. Hard turning has advantages such as lower equipment cost, shorter setup time, fewer process steps, greater part geometry flexibility and elimination of cutting fluid. In this study, the effect of cutting speed and feed rate on surface roughness in hard turning was experimentally investigated. AISI D2 steel workpiece (62 HRC) was machined with Cubic Boron Nitride (CBN) insert under dry machining. A 2k-factorial design with 4 centre points as an initial design of experiment (DOE) and a central composite design (CCD) as augmented design were used in developing the empirical mathematical models. They were employed for analysing the significant machining parameters. The results show that the surface roughness value decreased (smoother) with increasing cutting speed. In contrary, surface roughness value increased significantly when the feed rate increased. Optimum cutting speed and feed rate condition in this experiment was 105 m/min and 0.10 mm/rev respectively with surface roughness value was 0.267 µm. Further investigation revealed that the second order model is a valid surface roughness model, while the linear model cannot be used as a predicted model due to its lack of fit significance.

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