Optimization of Process Parameters Based on Multi-Process and Multi-Evaluation Index for Function Ceramics in CMP

2013 ◽  
Vol 797 ◽  
pp. 266-272
Author(s):  
Zi Hua Hu ◽  
Jiao Peng ◽  
Man Ke Gao
Keyword(s):  
Surface Roughness ◽  
Process Parameters ◽  
Material Removal Rate ◽  
Material Removal ◽  
Removal Rate ◽  
Orthogonal Experiment ◽  
Weight Ratio ◽  
Optimization Method ◽  
Evaluation Index ◽  
Optimization Of Process Parameters

To enhance polishing quality, polishing efficiency and improve the backward state based on single-process way for function ceramics in CMP, a new optimization method of process parameters based on multi-process and multi-evaluation theory is put forward. Firstly, based on experimental data obtained from orthogonal experiment, the optimal combinations of process parameters are got separately in term of surface roughness and material removal rate, which is optimized by Taguchi method in each process. Secondly, combining analysis of evaluation index weight ratio with analysis of variance, the final optimal combination of process parameters is received under the integrated evaluation of surface roughness and material removal rate. Finally, the contrast verification results show that the proposed optimization method is effective.

Optimization of Process Parameters in Plasma Arc Cutting Applying Genetic Algorithm and Fuzzy Logic

2018 ◽  
pp. 123-139
Author(s):  
Nehal Dash ◽  
Apurba Kumar Roy ◽  
Sanghamitra Debta ◽  
Kaushik Kumar
Keyword(s):  
Genetic Algorithm ◽  
Surface Roughness ◽  
Fuzzy Logic ◽  
Process Parameters ◽  
Material Removal Rate ◽  
Material Removal ◽  
Removal Rate ◽  
Plasma Arc ◽  
Plasma Arc Cutting ◽  
Optimization Of Process Parameters

Plasma Arc Cutting (PAC) process is a widely used machining process in several fabrication, construction and repair work applications. Considering gas pressure, arc current and torch height as the inputs and among all possible outputs, in the present work Material Removal Rate and Surface Roughness would be considered as factors that determines the quality, machining time and machining cost. In order to reduce the number of experiments Design of Experiments (DOE) would be carried out. In later stages applications of Genetic Algorithm (GA) and Fuzzy Logic would be used for Optimization of process parameters in Plasma Arc Cutting (PAC). The output obtained would be minimized and maximized for Surface Roughness and Material Removal Rate respectively using Genetic Algorithm (GA) and Fuzzy Logic.

Multi Response Optimization of Process Parameters of Abrasive Water Jet Machining for Stainless Steel AISI 304 Using VIKOR Approach Coupled with Signal to Noise Ratio Methodology

2015 ◽  
Vol 14 (02) ◽  
pp. 107-121 ◽  
Author(s):  
Vedansh Chaturvedi ◽  
Diksha Singh
Keyword(s):  
Surface Roughness ◽  
Process Parameters ◽  
Material Removal Rate ◽  
Material Removal ◽  
Removal Rate ◽  
Aisi 304 ◽  
Steel Aisi ◽  
Machining Characteristics ◽  
Stainless Steel Aisi ◽  
Experimental Runs

As the population of the world is continuously increasing, demand of the mechanical manufactured products is also increasing. Machining is the most important process in any mechanical manufacturing, and in machining two factors, i.e. material removal rate (MRR) and surface roughness (SR) are the most important responses. If the MRR is high, the product will get desired shape in minimum time so the production rate will be high, but we could not scarify with the surface finishing also because in close tolerance limit parts like in automobile industry, if the surface is rough exact fit cannot take place. The term optimization is intensively related to the field of quality engineering. Abrasive water jet machining is an important unconventional machining, in order to obtain better response, i.e. material removal rate and surface roughness. Various process parameters of AWJM need to be observed and selected to improve machining characteristics. Better machining characteristics can be achieved by optimizing various process parameters of AWJM. This study considers four process control parameters such as transverse speed, standoff distance, abrasive flow rate and water pressure. The response is taken to be material removal rate and surface roughness. The work piece for stainless steel AISI 304 material of size 15 cm × 10 cm × 2 cm is selected for experiments. Sixteen experimental runs (two trials for each experimental runs) were carried out for calculating MRR and SR and average value of these two trials have been taken for analysis. MRR is normalized according to higher-is-better and SR is normalized according to lower is better. The experiment data analysis is done and VIKOR index is found. Finally, the analysis of VIKOR index using S/N ratio is done and found the most significant factor for AWJM and predicted optimal parameters setting for higher material removal rate and lower surface roughness. Verification of the improvement in quality characteristics has been made through confirmation test with the predicted optimal parameters setting. It is found that the determined optimum combination of AWJM parameters gives the lowest VIKOR INDEX which shows the successful implementation of VIKOR Method coupled with S/N ratio in AWJM.

Abrasive Assisted Electro Chemical Machining of Aluminum-Boron Carbide-Graphite Hybrid Composite

2014 ◽  
Vol 591 ◽  
pp. 89-93 ◽  
Author(s):  
M. Sankar ◽  
R. Baskaran ◽  
K. Rajkumar ◽  
A. Gnanavelbabu
Keyword(s):  
Boron Carbide ◽  
Process Parameters ◽  
Material Removal Rate ◽  
Material Removal ◽  
Medium Optimization ◽  
Removal Rate ◽  
Statistical Techniques ◽  
Graphite Composite ◽  
Abrasive Medium ◽  
Optimization Of Process Parameters

In this paper, attempts have been made to model and optimize process parameters in Abrasive assisted Electro-Chemical Machining (AECM) of Aluminium-Boron carbide-Graphite composite using cylindrical copper tool electrodes with SiC abrasive medium. Optimization of process parameters is based on the statistical techniques with four independent input parameters such as voltage, current, reinforcement and feed rate were used to assess the AECM process performance in terms of material removal rate. The obtained results are compared with without abrasive assisted electro chemical machining of Aluminium-Boron carbide-Graphite composite. Abrasive assisted ECM process exhibited higher material removal rate from composite material when compared with without abrasive assisted ECM.

Optimization of Process Parameters on Ti-6Al-4V Using Central Composite Design Method

2011 ◽  
Vol 189-193 ◽  
pp. 1393-1400 ◽  
Author(s):  
M.M. Rahman
Keyword(s):  
Surface Roughness ◽  
Wear Rate ◽  
Process Parameters ◽  
Material Removal Rate ◽  
Material Removal ◽  
Removal Rate ◽  
Machining Process ◽  
Peak Current ◽  
Long Pulse ◽  
Pulse On Time

Electrical discharge machining (EDM) is relatively modern machining process having distinct advantages over other machining processes and able to machine Ti-alloys effectively. This paper attempts to investigate the effects of process parameters on output response of titanium alloy Ti-6Al-4V in EDM utilizing copper tungsten as an electrode and positive polarity of the electrode. Mathematical models for material removal rate (MRR), electrode wear rate (EWR) and surface roughness (SR) are developed in this paper. Design of experiments method and response surface methodology techniques are implemented. The validity test of the fit and adequacy of the proposed models has been carried out through analysis of variance. It can be seen that as the peak current increases the TWR decreases till certain ampere and then increases. The excellent surface finish is investigated in this study at short pulse on time and in contrast the long pulse duration causes the lowest EWR. Long pulse off time provides minimum EWR and the impact of pulse interval on EWR depends on peak current. The result leads to wear rate of electrode and economical industrial machining by optimizing the input parameters. It found that the peak current, servo voltage and pulse on time are significant in material removal rate and surface roughness. Peak current has the greater impact on surface roughness and material removal rate.

Optimization of WEDM Process Parameters

2014 ◽  
Vol 592-594 ◽  
pp. 831-835 ◽  
Author(s):  
Vikram Singh ◽  
Sharad Kumar Pradhan
Keyword(s):  
Surface Roughness ◽  
Response Surface ◽  
Process Parameters ◽  
Material Removal Rate ◽  
Material Removal ◽  
Removal Rate ◽  
Machining Parameters ◽  
Pulse On Time ◽  
Pulse Off Time ◽  
Wedm Process

The objective of the present work is to investigate the effects of various WEDM process parameters like pulse on time, pulse off time, corner servo, flushing pressure, wire feed rate, wire tension, spark gap voltage and servo feed on the material removal rate (MRR) & Surface Roughness (SR) and to obtain the optimal settings of machining parameters at which the material removal rate (MRR) is maximum and the Surface Roughness (SR) is minimum in a range. In the present investigation, Inconel 825 specimen is machined by using brass wire as electrode and the response surface methodology (RSM) is for modeling a second-order response surface to estimate the optimum machining condition to produce the best possible response within the experimental constraints.

scholarly journals Intelligent optimization of wire-EDM parameters for surface roughness and material removal rate while machining WC-Co composite

2021 ◽  
Vol 49 (3) ◽  
pp. 756-763
Author(s):  
Kapil Gupta
Keyword(s):  
Surface Roughness ◽  
Response Surface Methodology ◽  
Response Surface ◽  
Process Parameters ◽  
Material Removal Rate ◽  
Material Removal ◽  
Removal Rate ◽  
Hybrid Technique ◽  
Wire Edm ◽  
Abc Algorithm

This work presents the wire-EDM of WC-Co composite and optimization of process parameters using an integrated technique of response surface methodology (RSM), Vise Kriterijumska Optimizacija Kompromisno Resenje (VIKOR) and artificial bee colony (ABC) algorithm to obtain the best set of machinability indicators. Wire feed (WF), servo voltage (SV), pulse off-time (Pon) and pulse on-time (Poff) are the variable process parameters, whereas root mean square roughness (Rq), average surface roughness (Ra) and material removal rate (MRR) are the machinability indicators considered in the present work. A total of twenty nine experiments have been conducted based on Box Behnken design (BBD) technique of response surface methodology. VIKOR has been used for normalization of responses and followed by solving empirical models using ABC algorithm to obtain optimized process parameters setting. WF-12 m/min, SV-65V, Pon-116 µs, Poff-20 µs are the optimum wire-EDM parameters obtained by intelligent RSM-VIKOR-ABC technique that produced best values of Ra-4.51 µm, Rq-5.64 µm, MRR-0.061 mm3 /min simultaneously. The validation test confirmed an improvement up to 15% in the response characteristics which proved the effectiveness of this novel hybrid technique for optimization. The optimum parameter setting is for ready industrial reference to attain best surface quality and process productivity for WC-Co composite machining by wire-EDM.

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