Parametric Study of Pulsed CO2 Laser Surface Treatment of Alumina Ceramics

2015 ◽  
Vol 15 (3) ◽  
pp. 301-308
Author(s):  
A. Bharatish ◽  
H. N. Narasimha Murthy ◽  
Ajithkumar Radder ◽  
V. Mamatha ◽  
B. Anand ◽  
...  
Keyword(s):  
Surface Roughness ◽  
Material Removal Rate ◽  
Laser Power ◽  
Material Removal ◽  
Removal Rate ◽  
Scanning Speed ◽  
Pulse Frequency ◽  
Alumina Ceramics ◽  
Laser Surface Treatment ◽  
Grey Relational

AbstractThis paper focuses on investigating the influence of laser power, pulse frequency and scanning speed on material removal rate and surface roughness during CO2 laser surface treatment of alumina ceramics. Pulse frequency and laser power were the significant factors influencing the material removal rate and surface roughness, respectively. Adequate response surface models were established to correlate the laser parameters and the measured responses. Grey relational analysis predicted the optimal responses at 90 W laser power, 5 kHz pulse frequency and 400 mm/s scanning speed. Desirability function based Multi objective optimization results indicated that minimum material removal rate (0.5117 mm3/s) and surface roughness (0.5968 µm) are achieved at 90 W laser power, 5 kHz pulse frequency and 337.37 mm/s scanning speed which were in close agreement with Grey Relational results. Increase in homogeneity and smoothness of the laser treated alumina surface along with formation of micro recast particles away from the laser traverse path were evidenced by the SEM micrographs.

Comparative Performance In Hard Turning Of AISI 1015 Steel With Carbide Insert Using Orthogonal Array Design And Grey Relational Analysis Under Spray Impingement Cooling And Dry Environment

2014 ◽  
Vol 4 (3) ◽  
pp. 1-32 ◽  
Author(s):  
Purna Chandra Mishra ◽  
Dipti Kanta Das ◽  
Susant Kumar Sahu
Keyword(s):  
Surface Roughness ◽  
Material Removal Rate ◽  
Orthogonal Array ◽  
Material Removal ◽  
Removal Rate ◽  
Cutting Temperature ◽  
Impingement Cooling ◽  
Spray Impingement ◽  
Grey Relational ◽  
Carbide Insert

This study investigates the effects of cutting parameters on surface roughness (Ra), cutting temperature (T0C) at the chip tool interface and the material removal rate (MRR mm3/min) during hard machining of AISI 1015 (43 HRC) steel using carbide insert under dry and spray impingement cooling environment. A combined technique using orthogonal array and analysis of variance (ANOVA) was employed to investigate the contribution of spindle speed, feed rate, depth of cut and air pressure on responses. Utilization of IR camera is been effective to calculate the temperature at the interface of workpiece and the tool. It is observed that with spray impingement cooling, cutting performance improves compared to dry cutting. The predicted multi response optimization setting (N3-f1-d1-P2) ensures minimization of surface roughness, cutting temperature and maximization of material removal rate. Finally optimal result was validated by confirmatory test and the improvement in grey relational grade was found to be 0.288.

Optimization of WEDM Process Parameters of Hybrid Composites (A413 / B4C / Fly Ash) Using Grey Relational Analysis

2014 ◽  
Vol 592-594 ◽  
pp. 658-662 ◽  
Author(s):  
J. Milton Peter ◽  
J. Udaya Prakash ◽  
T.V. Moorthy
Keyword(s):  
Surface Roughness ◽  
Fly Ash ◽  
Process Parameters ◽  
Material Removal Rate ◽  
Grey Relational Analysis ◽  
Material Removal ◽  
Hybrid Composites ◽  
Removal Rate ◽  
Relational Analysis ◽  
Grey Relational

This paper presents an optimum method to find the significant parameters affecting Wire Electrical Discharge machining (WEDM) performance using Grey relational analysis. A413 Aluminium Alloy reinforced with 20 microns of Boron Carbide and 75 microns of Fly Ash, hybrid composites was fabricated using stir casting technique. Experiments have been conducted with the process parameters like pulse on time, pulse off time, wire feed, gap voltage and weight percentage reinforcement with three different levels. The influence of each parameter on the responses material removal rate and surface roughness is established using analysis of variances (ANOVA). The optimal machining-parameters setting for minimum surface roughness and maximum material removal rate was obtained by applying Grey relational analysis.

Optimization Design for Gun-Receiver Materials Belt Grinding Based on Orthogonal Experimental Method and Grey Relational Analysis

2013 ◽  
Vol 797 ◽  
pp. 55-60
Author(s):  
Yu Hui Chen ◽  
Yun Huang ◽  
Yao Huang
Keyword(s):  
Surface Roughness ◽  
Material Removal Rate ◽  
Grey Relational Analysis ◽  
Material Removal ◽  
Optimization Design ◽  
Removal Rate ◽  
Belt Grinding ◽  
Abrasive Belt ◽  
Relational Analysis ◽  
Grey Relational

In order to change the current situation of gun-receiver manual polishing, the paper presents a new process for abrasive belt grinding of gun-receiver material (C50 steel). Orthogonal test were conducted with abrasive belt grinding of C50 steel to do research on material removal rate and surface roughness. The best parameter combination to the optimization design which can guarantee high material removal rate and low surface roughness was obtained by using grey relational analysis method and verified by experiments. The above mentioned research not only can improve the removal rate of C50 steel, but also do help to prolong the service life of the belt. Whats more, it can guide a theoretical significance and practical value to the production practice.

scholarly journals Use of Multi-Objective Optimization Technique (Taguchi-GRA Approach) in Dry Hard Turning of Inconel 625

2020 ◽  
Vol 12 (2) ◽  
pp. 133-142
Author(s):  
Chinmaya PADHY ◽  
Pariniti SINGH
Keyword(s):  
Surface Roughness ◽  
Material Removal Rate ◽  
Material Removal ◽  
Hard Turning ◽  
Removal Rate ◽  
Optimization Technique ◽  
Cutting Speed ◽  
Inconel 625 ◽  
Depth Of Cut ◽  
Grey Relational

Current developments in manufacturing industries consider developing a suitable optimization technique for achieving improved machining performance. This study investigates the optimum values of machining parameters required namely –cutting speed (v), feed rate (f) and depth-of-cut (d) during dry hard turning of Inconel 625 with the aim of enhancing the productivity by minimizing surface roughness (Ra), cutting force (Fc), whereas maximizing material removal rate(MRR). This kind of multi-response process variable (MRP) problems usually known as multi-objective optimizations (MOOs) are solved with the help of Taguchi- Grey Relational Approach (T-GRA). Thus, here is a study conducted to apply Taguchi and Grey relational analysis to optimize multiple performance characteristics during dry hard turning of Inconel -625. As a result, the attained process variables, viz., cutting speed (60 m/min), feed rate (0.3 mm/rev), depth- of- cut (0.25mm) lead to value of optimum response variables –mean cutting force (340 N), surface roughness (0.998 μm) and material removal rate (0.786 mm3/min). In this setup, PVD coated carbide tool inserts were used for dry hard machining (turning) operation.

Effects of Process Parameters on Surface Roughness and MRR in the hard turning of EN 36 steel

2018 ◽  
pp. 102-110
Author(s):  
Amritpal Singh ◽  
Rakesh Kumar
Keyword(s):  
Surface Roughness ◽  
Material Removal Rate ◽  
Material Removal ◽  
Hard Turning ◽  
Control Parameter ◽  
Removal Rate ◽  
Cutting Speed ◽  
Depth Of Cut ◽  
Cutting Condition ◽  
Dry Cutting

In the present study, Experimental investigation of the effects of various cutting parameters on the response parameters in the hard turning of EN36 steel under the dry cutting condition is done. The input control parameters selected for the present work was the cutting speed, feed and depth of cut. The objective of the present work is to minimize the surface roughness to obtain better surface finish and maximization of material removal rate for better productivity. The design of experiments was done with the help of Taguchi L9 orthogonal array. Analysis of variance (ANOVA) was used to find out the significance of the input parameters on the response parameters. Percentage contribution for each control parameter was calculated using ANOVA with 95 % confidence value. From results, it was observed that feed is the most significant factor for surface roughness and the depth of cut is the most significant control parameter for Material removal rate.

Effect of SiC-Cu Electrode on Material Removal Rate, Tool Wear and Surface Roughness in EDM Process

2020 ◽  
Vol 38 (9A) ◽  
pp. 1406-1413
Author(s):  
Yousif Q. Laibia ◽  
Saad K. Shather
Keyword(s):  
Surface Roughness ◽  
Tool Wear ◽  
Material Removal Rate ◽  
Material Removal ◽  
Electrical Discharge Machining ◽  
Removal Rate ◽  
304 Stainless Steel ◽  
Tool Electrode ◽  
Pulse Time ◽  
Edm Process

Electrical discharge machining (EDM) is one of the most common non-traditional processes for the manufacture of high precision parts and complex shapes. The EDM process depends on the heat energy between the work material and the tool electrode. This study focused on the material removal rate (MRR), the surface roughness, and tool wear in a 304 stainless steel EDM. The composite electrode consisted of copper (Cu) and silicon carbide (SiC). The current effects imposed on the working material, as well as the pulses that change over time during the experiment. When the current used is (8, 5, 3, 2, 1.5) A, the pulse time used is (12, 25) μs and the size of the space used is (1) mm. Optimum surface roughness under a current of 1.5 A and the pulse time of 25 μs with a maximum MRR of 8 A and the pulse duration of 25 μs.

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