Experimental investigation of machinability and geometrical behavior of Titanium Alloy (Ti–6Al–4V) using Abrasive Waterjet Circular cut using Response Surface Methodology-Desirability approach

2021 ◽  
Author(s):  
Umanath Karuppusamy ◽  
Devika D ◽  
Rashia Begum S
Keyword(s):  
Surface Roughness ◽  
Response Surface Methodology ◽  
Titanium Alloy ◽  
Response Surface ◽  
Process Parameters ◽  
Abrasive Waterjet ◽  
Optimum Level ◽  
Machining Parameters ◽  
Input Parameters ◽  
Desirability Approach

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.

EXPERIMENTAL STUDY OF SURFACE ROUGHNESS AND TAPER ANGLE IN ABRASIVE WATER JET MACHINING OF 7075 ALUMINUM COMPOSITE USING RESPONSE SURFACE METHODOLOGY

2019 ◽  
Vol 27 (03) ◽  
pp. 1950112 ◽  
Author(s):  
A. SHANMUGAM ◽  
K. KRISHNAMURTHY ◽  
T. MOHANRAJ
Keyword(s):  
Surface Roughness ◽  
Response Surface Methodology ◽  
Response Surface ◽  
Process Parameters ◽  
Water Pressure ◽  
Traverse Speed ◽  
Standoff Distance ◽  
Abrasive Waterjet ◽  
Machined Surface ◽  
Taper Angle

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.

Multi-Response Optimization of CNC WEDM Process Parameters for Machining Titanium Alloy Ti 6AI-4V Using Response Surface Methodology (RSM)

2014 ◽  
Vol 541-542 ◽  
pp. 354-358 ◽  
Author(s):  
C. Nandakumar ◽  
B. Mohan
Keyword(s):  
Surface Roughness ◽  
Response Surface Methodology ◽  
Titanium Alloy ◽  
Response Surface ◽  
Process Parameters ◽  
Material Removal Rate ◽  
Material Removal ◽  
Removal Rate ◽  
Response Optimization ◽  
Wedm Process

This research deals with the multi-response optimization of CNC WEDM process parameters for machining titanium alloy Ti 6AI-4V using Response Surface Methodology (RSM) to achieve higher Material Removal Rate (MRR) and lower surface roughness (Ra). The process parameters of CNC WEDM namely pulse-on time (TON), pulse-off time (TOFF) and wire feed rate (WF) were optimized to study the responses in terms of material removal rate and surface roughness. The surface plot and the contour plots were generated between the process parameters and the responses using MINITAB software. The results show that the Response surface methodology (RSM) is a powerful tool for providing experimental diagrams and statistical-mathematical models to perform the experiments appropriately and economically.

scholarly journals DEVELOPMENT OF NUMERICAL MODELS FOR THE PREDICTION OF TEMPERATURE AND SURFACE ROUGHNESS DURING THE MACHINING OPERATION OF TITANIUM ALLOY (Ti6Al14V)

2020 ◽  
Vol 60 (5) ◽  
pp. 369-390
Author(s):  
Ilesanmi Daniyan ◽  
Isaac Tlhabadira ◽  
Khumbulani Mpofu ◽  
Adefemi Adeodu
Keyword(s):  
Neural Network ◽  
Surface Roughness ◽  
Artificial Neural Network ◽  
Response Surface Methodology ◽  
Titanium Alloy ◽  
Response Surface ◽  
Process Parameters ◽  
Numerical Models ◽  
Physical Experiments ◽  
Artificial Neural Network Ann

Temperature and surface roughness are important factors, which determine the degree of machinability and the performance of both the cutting tool and the work piece material. In this study, numerical models obtained from the Response Surface Methodology (RSM) and Artificial Neural Network (ANN) techniques were used for predicting the magnitude of the temperature and surface roughness during the machining operation of titanium alloy (Ti6Al4V). The design of the numerical experiment was carried out using the Response Surface Methodology (RSM) for the combination of the process parameters while the Artificial Neural Network (ANN) with 3 input layers, 10 sigmoid hidden neurons and 3 linear output neurons were employed for the prediction of the values of temperature. The ANN was iteratively trained using the Levenberg-Marquardt backpropagation algorithm. The physical experiments were carried out using a DMU80monoBLOCK Deckel Maho 5-axis CNC milling machine with a maximum spindle speed of 18 000 rpm. A carbide-cutting insert (RCKT1204MO-PM S40T) was used for the machining operation. A professional infrared video thermometer with an LCD display and camera function (MT 696) with infrared temperature range of −50−1000 °C, was employed for the temperature measurement while the surface roughness of the work pieces were measured using the Mitutoyo SJ – 201, surface roughness machine. The results obtained indicate that there is high degree of agreement between the values of temperature and surface roughness measured from the physical experiments and the predicted values obtained using the ANN and RSM. This signifies that the developed RSM and ANN models are highly suitable for predictive purposes. This work can find application in the production and manufacturing industries especially for the control, optimization and process monitoring of process parameters.

Experimental Investigation of Process Parameters in Wire Electrical Discharge Machining by Response Surface Methodology on IS2062 Steel

2014 ◽  
Vol 550 ◽  
pp. 53-61
Author(s):  
R.Arun Bharathi ◽  
P.Ashoka Varthanan ◽  
K. Manoj Mathew
Keyword(s):  
Surface Roughness ◽  
Response Surface Methodology ◽  
Response Surface ◽  
Process Parameters ◽  
Machining Parameters ◽  
Peak Current ◽  
Custom Design ◽  
Pulse On Time ◽  
Pulse Off Time ◽  
Off Time

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).

Parametric Optimization in Drilling Operation Using Response Surface Approach

2016 ◽  
Vol 1137 ◽  
pp. 117-131
Author(s):  
Kamaljit Singh Boparai ◽  
Sandeep Singh ◽  
Amritpal Singh
Keyword(s):  
Surface Roughness ◽  
Response Surface Methodology ◽  
Response Surface ◽  
Process Parameters ◽  
Metal Cutting ◽  
Parametric Optimization ◽  
Machining Parameters ◽  
Surface Approach ◽  
Contour Plots ◽  
Cutting Processes

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.

Modeling of the machining parameters in turning of Al-5052/TiC/SiC composites: a statistical modeling approach using grey relational analysis (GRA) and response surface methodology (RSM)

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Venkateshwar Reddy Pathapalli ◽  
Meenakshi Reddy Reddigari ◽  
Eswara Kumar Anna ◽  
P. Srinivasa Rao ◽  
D V. Ramana Reddy
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Metal Matrix ◽  
Machining Parameters ◽  
Matrix Composites ◽  
Content Type ◽  
Relational Analysis ◽  
Desirability Approach ◽  
Grey Relational ◽  
Grey Taguchi

PurposeMetal matrix composites (MMC) has been a section which gives an overview of composite materials and owing to those exceptional physical and mechanical properties, particulate-reinforced aluminum MMCs have gained increasing interest in particular engineering applications. Owing to the toughness and abrasive quality of reinforcement components such as silicon carbide (SiC) and titanium carbide (TiC), such materials are categorized as difficult materials for machining. The work aims to develop the model for evaluating the machinability of the materials via the response surface technique by machining three distinct types of hybrid MMCs.Design/methodology/approachThe combined effects of three machining parameters, namely “cutting speed” (s), “feed rate” (f) and “depth of cut” (d), together with three separate composite materials, were evaluated with the help of three performance characteristics, i.e. material removal rate (MRR), cutting force (CF) and surface roughness (SR). Response surface methodology and analysis of variance (ANOVA) both were initially used for analyzing the machining parameters results.FindingsThe contours were developed to observe the combined process parameters along with their correlations. The process variables were concurrently configured using grey relational analysis (GRA) and the composite desirability methodology. Both the GRA and composite desirability approach obtained similar results.Practical implicationsThe results obtained in the present paper will be helpful for decision-makers in manufacturing industries, who work on metal cutting area especially composites, to select the suitable solution by implementing the Grey Taguchi and modeling techniques.Originality/valueThe originality of this research is to identify the suitability of process parameters combination based on the obtained research results. The optimization of machining parameters in turning of hybrid metal matrix composites is carried out with two different methods such as Grey Taguchi and composite desirability approach.

scholarly journals Effect of Process Parameters on the Surface Roughness and Kerf Width of Mild Steel during Plasma Arc Cutting Using Response Surface Methodology

2020 ◽  
Vol 5 (1) ◽  
Author(s):  
Ekhaesomi A Agbonoga ◽  
Oyewole Adedipe ◽  
Uzoma G Okoro ◽  
Fidelis J Usman ◽  
Kafayat T Obanimomo ◽  
...  
Keyword(s):  
Surface Roughness ◽  
Response Surface Methodology ◽  
Response Surface ◽  
Analysis Of Variance ◽  
Process Parameters ◽  
Cutting Speed ◽  
Gas Pressure ◽  
Kerf Width ◽  
Plasma Arc ◽  
Plasma Arc Cutting

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

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