Parametric Optimization in Drilling Operation Using Response Surface Approach

2016 ◽  
Vol 1137 ◽  
pp. 117-131
Author(s):  
Kamaljit Singh Boparai ◽  
Sandeep Singh ◽  
Amritpal Singh

Modeling and optimization of machining parameters are the indispensable elements in modern metal cutting processes. The present study realize the interaction of drilling input process parameters such as spindle speed, feed rate and number of holes and their influence on the surface roughness, diameter and position of hole obtained in drilling of mild steel. The contour plots were generated to highlights the interaction of process parameters as well as their effect on responses. An empirical model of surface roughness, diameter and position of hole was developed using response surface methodology (RSM). The model fitted and measured values were quite close, which indicates that the developed models can be effectively used to predict the respective response. The process parameters are optimized using desirability-based approach response surface methodology.

2021 ◽  
Author(s):  
Umanath Karuppusamy ◽  
Devika D ◽  
Rashia Begum S

Abstract In the current study, the research explored the effect of the process parameters on the Titanium Alloy (Ti–6Al–4V) to improve the machining, surface and geometric characteristics of the circular cut-off profile by determining the optimum parameters for the Abrasive Water Jet Machining (AWJM). The input parameters considered are the Abrasive Flow Rate (AFR), Stand-off Distance (SoD), and Traverse Rate (TR). There are various input parameters to evaluate output parameters like Circularity, Cylindricity, and Surface Roughness (SR) of the circular cut profile. The experiments are conducted using Central Composite Design (CCD) in the Response Surface Methodology (RSM). Analysis of variance (ANOVA) is carried out to define most influenced process parameters and percentage of contribution. The RSM is used to predict the mathematical models for formulating the objective function using experimental results. RSM desirability approach is included in the method for determining optimum levels and discerning impacts on response variables of machining parameters. Confirmation tests with an optimum level of machining parameters have been completed to determine the adequacy of the RSM. In addition to that, the cutting profiles are also analysed using Scanning Electron Microscope (SEM). The Atomic Force Microscope(AFM) is often used to verify the minimum Surface Roughness of the AWJM machined surface.


2013 ◽  
Vol 13 (1-2) ◽  
pp. 31-36
Author(s):  
Sadineni Rama Rao ◽  
G. Padmanabhan

AbstractElectrochemical machining (ECM) is increasing its importance in machining of metal matrix composites (MMC) due to some specific advantages which can be exploited during machining operation. In ECM the quality of the surface produced is also depends on the workpiece physical and electrical properties along with the process parameters like voltage, feed rate, electrolyte concentration, type of electrolyte, current, gap between electrodes etc. Therefore, in the present work the percentage of reinforcement of the particulates in the matrix is considered one of the process parameters along with the applied voltage, electrode feed rate and electrolyte concentration. A mathematical prediction model of the radial over cut (ROC) was developed using response surface methodology (RSM). The effects of electrochemical machining parameters on the Radial over cut were evaluated. The contour plots were drawn to study the effect of various process parameters and their interaction. In this work the predicted values and measured values are quite close to each other. Therefore, the developed model can be effectively used to predict the radial over cut on electrochemical machining of Al-B4C composites.


2014 ◽  
Vol 550 ◽  
pp. 53-61
Author(s):  
R.Arun Bharathi ◽  
P.Ashoka Varthanan ◽  
K. Manoj Mathew

The objective of the present work is to predict the optimal set of process parameters such as peak current (IP), pulse on/off time (TON/TOFF) and spark gap voltage (SV) to achieve minimum Surface roughness (Ra), wire consumption rate (WCR) and maximum material removal rate (MRR). In this work, experiments were carried out by pulse arc discharges generated between ZnO coated brass wire and specimen (IS2062 steel) suspended in deionized water dielectric. The experiments were designed based on the above mentioned four factors, each having three levels. Custom design based Response Surface Methodology (RSM) is used in this research. 21 runs of experiments were constructed based on custom design procedure and results of the experimentation were analyzed analytically as well as graphically. Moreover the surface roughness after machining was measured by Taylor Hobson Surtronic device. Second order regression model has been developed for predicting Ra, WCR and MRR in terms of interactive and higher order machining parameters through RSM, utilizing relevant experimental data as obtained through experimentation. The research outcome identifies significant parametersand their effect on process performance on IS2062 steel. The results revealed that peak current, pulse on-time and their interactions have significant effects on Ra, whereas pulse off time and peak current have significant effects on MRR and it is also observed that peak current and interaction between peak current and pulse off time have significant effects on WCR. The adequacy of the above proposed models has been tested through the analysis of variance (ANOVA).


2020 ◽  
Vol 5 (1) ◽  
Author(s):  
Ekhaesomi A Agbonoga ◽  
Oyewole Adedipe ◽  
Uzoma G Okoro ◽  
Fidelis J Usman ◽  
Kafayat T Obanimomo ◽  
...  

This study investigated the effects of process parameters of plasma arc cutting (PAC) of low carbon steel material using analysis of variance. Three process parameters, cutting speed, cutting current and gas pressure were considered and experiments were conducted based on response surface methodology (RSM) via the box-Behnken approach. Process responses viz. surface roughness (Ra) and kerf width of cut surface were measured for each experimental run. Analysis of Variance (ANOVA) was performed to get the contribution of process parameters on responses. Cutting current has the most significant effect of 33.43% on the surface roughness and gas pressure has the most significant effect on  kerf width of  41.99% . For minimum surface roughness and minimum kerf width, process parameters were optimized using the RSM. Keywords: Cutting speed, cutting current, gas pressure,   surface roughness, kerf width


2019 ◽  
Vol 27 (03) ◽  
pp. 1950112 ◽  
Author(s):  
A. SHANMUGAM ◽  
K. KRISHNAMURTHY ◽  
T. MOHANRAJ

Surface roughness and taper angle of an abrasive waterjet machined surface of 7075 Aluminum metal matrix composite were deliberately studied. Response surface methodology design of experiments and analysis of variance were used to design the experiments and to identify the effect of process parameters on surface roughness and taper angle. The jet traverse speed and jet pressure were the most significant process parameters which influence the surface roughness and taper angle, respectively. Increasing the pressure and jet traverse speed results in increasing the surface roughness and taper angle. At the same time, decreasing the standoff distance and jet traverse speed possibly enhances both the responses. The optimal process parameters of 1[Formula: see text]mm as standoff distance, 192[Formula: see text]MPa as water pressure and 30[Formula: see text]mm[Formula: see text]min[Formula: see text] as jet traverse speed were identified to obtain the minimum value of surface roughness and taper angle. Based on the optimal parameters, the confirmation test was conducted. The mathematical equation was obtained from the experimental data using regression analysis; it was observed that the error was less than 5% of the experimentally measured values.


2014 ◽  
Vol 984-985 ◽  
pp. 118-123 ◽  
Author(s):  
S. Periyasamy ◽  
M. Aravind ◽  
D. Vivek ◽  
K.S. Amirthagadeswaran

In this study, the response surface methodology was used to optimize the process parameters of constant speed horizontal spindle surface grinding. The experiments were conducted based on the design expert software. The surface roughness characteristics were investigated in AISI 1080 steel plates using A60V5V grinding wheels. The optimum parameters for minimum surface roughness were found using Design Expert software. The parameters for a particular surface roughness value can also be determined using the results of this experiment. This results shows that feed has a greater effect on surface roughness and feed has medium effect on surface roughness. While dressing depth of cut has a very minimal effect on surface roughness.


2016 ◽  
Vol 16 (2) ◽  
pp. 75-88 ◽  
Author(s):  
Munish Kumar Gupta ◽  
P. K. Sood ◽  
Vishal S. Sharma

AbstractIn the present work, an attempt has been made to establish the accurate surface roughness (Ra, Rq and Rz) prediction model using response surface methodology with Box–Cox transformation in turning of Titanium (Grade-II) under minimum quantity lubrication (MQL) conditions. This surface roughness model has been developed in terms of machining parameters such as cutting speed, feed rate and approach angle. Firstly, some experiments are designed and conducted to determine the optimal MQL parameters of lubricant flow rate, input pressure and compressed air flow rate. After analyzing the MQL parameter, the final experiments are performed with cubic boron nitride (CBN) tool to optimize the machining parameters for surface roughness values i. e., Ra, Rq and Rz using desirability analysis. The outcomes demonstrate that the feed rate is the most influencing factor in the surface roughness values as compared to cutting speed and approach angle. The predicted results are fairly close to experimental values and hence, the developed models using Box-Cox transformation can be used for prediction satisfactorily.


Author(s):  
Bikash Choudhuri ◽  
Ruma Sen ◽  
Subrata Kumar Ghosh ◽  
Subhash Chandra Saha

Wire electric discharge machining is a non-conventional machining wherein the quality and cost of machining are influenced by the process parameters. This investigation focuses on finding the optimal level of process parameters, which is for better surface finish, material removal rate and lower wire consumption for machining stainless steel-316 using the grey–fuzzy algorithm. Grey relational technique is applied to find the grey coefficient of each performance, and fuzzy evaluates the multiple performance characteristics index according to the grey relational coefficient of each response. Response surface methodology and the analysis of variance were used for modelling and analysis of responses to predict and find the influence of machining parameters and their proportion of contribution on the individual and overall responses. The measured values from confirmation experiments were compared with the predicted values, which indicate that the proposed models can be effectively used to predict the responses in the wire electrical discharge machining of AISI stainless steel-316. It is found that servo gap set voltage is the most influential factor for this particular steel followed by pulse off time, pulse on time and wire feed rate.


2012 ◽  
Vol 622-623 ◽  
pp. 1280-1284 ◽  
Author(s):  
Pragya Shandilya ◽  
P.K. Jain ◽  
N.K. Jain

Wire electric discharge machining (WEDM) is one of the most popular non-conventional machining processes for machining metal matrix composites (MMCs). The present research work deals the parametric optimization of the input process parameters for response parameter during WEDM of SiCp/6061 Al metal matrix composite (MMC). Response surface methodology (RSM) and genetic algorithm (GA) integrated with each other to optimize the process parameters. RSM has been used to plan and analyze the experiments. Four WEDM parameters namely servo voltage, pulse-on time, pulse-off time and wire feed rate were varied to study their effect on the quality of cut in SiCp/6061 Al MMC using cutting width (kerf) as response parameter. The relationship between kerf and machining parameters has been developed by using RSM. The mathematical model thus than developed was then employed on GA to optimized the process parameters.


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