Experimental Investigation and Parametric Optimization in Abrasive Jet Machining on NICKEL 233 Alloy Using WASPAS

2019 ◽  
Vol 18 (04) ◽  
pp. 549-561
Author(s):  
S. Rajendra Prasad ◽  
K. Ravindranath ◽  
M. L. S. Devakumar
Keyword(s):  
Parametric Optimization ◽  
Removal Rate ◽  
Optimization Technique ◽  
Machining Parameters ◽  
Abrasive Jet Machining ◽  
Process Pressure ◽  
Conflicting Objectives ◽  
Machined Parts ◽  
Optimal Setting ◽  
First Time

Decision of finest machining parameters is very essential factors in any processing of machined parts. This article presents a multi-objective optimization technique, based on WASPAS method toward optimize the machining parameters in abrasive jet machining (AJM) process: pressure, nozzle to tip distance (NTD), and average grain diameter on NICKEL 233 alloy. Three conflicting objectives, Material Removal Rate (MRR), surface roughness (Ra) and taper angle (Ta) are simultaneously considered. The proposed technique weighted aggregated product sum assessment technique is investigation of parametric optimization on AJM process. Its outcome using tool in any ranges of responses in AJM process is the optimal setting of parameters are determined through experiments illustrated. Broad usage of Aerospace industries for NICKEL 233, generating a hole of the machining data first time in this work using AJM will be useful.

Parametric optimization in modified air abrasive jet machining

2019 ◽  
Vol 15 (3) ◽  
pp. 617-629
Author(s):  
S. Rajendra Prasad ◽  
K. Ravindranath K. Ravindranath ◽  
M.L.S. Devakumar M.L.S. Devakumar
Keyword(s):  
Optimization Technique ◽  
Mesh Size ◽  
Machining Parameters ◽  
Multi Objective Optimization ◽  
Content Type ◽  
Multi Objective ◽  
Abrasive Jet Machining ◽  
Alloy Material ◽  
Size Measure ◽  
First Time

Purpose The choice of best machining parameters is an extremely basic factor in handling of any machined parts. The purpose of this paper is to exhibit a multi-objective optimization technique; in view of weighted aggregate sum product assessment (WASPAS) technique toward upgrade the machining parameters in modified air abrasive jet machining (MAAJM) process: injecting pressure, stand-off distance (SOD), and abrasive mesh size measure with 100 rpm rotatable worktable on Nickel 233 alloy material. Three conflicting destinations, material removal rate (MRR), surface roughness (SR) and taper angles (Ta), respectively, are considered at the same time. The proposed procedure uses WASPAS, which is the examination of parametric optimization of the abrasive jet machining (AJM) process. The results was used any scopes of reactions in MAAJM process is the ideal setting of parameters are resolved through investigations represented. There is wide utilization of Nickel 233 in aviation enterprises; machining information on producing a hole utilizing MAAJM for the first time is given in this work, which will be helpful different industries. Design/methodology/approach This paper exhibits a multi-objective optimization technique; in view of WASPAS technique toward upgrade the machining parameters in MAAJM process: injecting pressure, SOD, and abrasive mesh size measure with 100 rpm rotatable worktable on Nickel 233 alloy material. Findings As an outcome of using the tool in any ranges of responses in the AJM process, the optimal setting of parameters is determined through experiments illustrated. The machining data of generating a hole using AJM are studied for the first time in this work, which will be useful for aerospace industries, where Nickel 233 is used broadly. Originality/value A new material in unconventional machining process and also a multi-objective optimization technique are adopted.

Application of Teaching

2015 ◽  
Vol 2 (2) ◽  
pp. 1-16 ◽  
Author(s):  
Nandkumar N. Bhopale ◽  
Nilesh Nikam ◽  
Raju S. Pawade
Keyword(s):  
Tool Path ◽  
End Milling ◽  
Optimization Technique ◽  
Milling Process ◽  
Parameters Optimization ◽  
Machining Parameters ◽  
Machining Processes ◽  
Conflicting Objectives ◽  
Advanced Machining ◽  
Teaching Learning

Recently advanced machining processes are widely used by manufacturing industries in order to produce high quality precise and very complex products. These advanced machining processes involve large number of input parameters which may affect the cost and quality of the products. Selection of optimum machining parameters in such advanced machining processes is very important to satisfy all the conflicting objectives of the process. This algorithm is inspired by the teaching-learning process and it works on the effect of influence of a teacher on the output of learners in a class. This paper presents the application of Response Surface Methodology coupled with newly developed advanced algorithm Teaching Learning Based Optimization Technique (TLBO) is applied for the process parameters optimization for ball end milling process on Inconel 718 cantilevers. The machining and tool related parameters like spindle speed, milling feed, workpiece thickness and workpiece inclination with tool path orientation are optimized with considerations of multiple response like deflection, surface roughness, and micro hardness of plate.

Optimisation of Machining Parameters in Electrical Discharge Machining of LM25-RHA Composites

2017 ◽  
pp. 1-18
Author(s):  
Srikant Tiwari ◽  
Mohan Kumar Pradhan
Keyword(s):  
Conventional Method ◽  
Rice Husk ◽  
Electrical Discharge ◽  
Rice Husk Ash ◽  
Electrical Discharge Machining ◽  
Removal Rate ◽  
Machining Process ◽  
Electrode Wear ◽  
Machining Parameters ◽  
Optimal Setting

Aluminium composites are tough to machine by using conventional method. In order to increase machinability of aluminium-based composite a non-conventional method of machining has been used. Electrical Discharge Machining (EDM) is one of the kind of machining process which has often uses for machining of aluminium composites. The objective of this chapter is to determine the ideal setting of the process parameters on the electrical discharge machining while machining Aluminium-Rice Husk Ash (LM25-RHA) composites in which three different variation (4%, 8%, 12%) of Rice Husk Ash has been used. The parameters considered are pulse current (Ip), gap voltage (V) and pulse-on-time (Ton); whereas its effect are analysed on Electrode Wear Rate (EWR), Material Removal Rate (MRR) and Surface Roughness (Ra). The optimal setting of the parameters are determined through experiments planned, conducted and analysed using the Taguchi method.

Experimental and Mechanism Research on EDM Combined with Magnetic Field

2009 ◽  
Vol 416 ◽  
pp. 337-341 ◽  
Author(s):  
Ming Rang Cao ◽  
Yan Qing Wang ◽  
Sheng Qiang Yang ◽  
Weng Hui Li
Keyword(s):  
Magnetic Field ◽  
Surface Roughness ◽  
Material Removal Rate ◽  
Discharge Current ◽  
Material Removal ◽  
Discharge Channel ◽  
Removal Rate ◽  
Machining Parameters ◽  
Mechanism Research ◽  
First Time

The two disadvantages of EDM are the low material removal rate (MRR) and poor surface quality. In this investigation, EDM assisted by magnetic field (MFEDM) has been proposed for the first time to overcome above-mentioned disadvantages. Constant magnetic field was applied to the both sides of discharge channel perpendicularly to form a novel process. In experiment, EDM machine tool D703F was used to machine nonferromagnetic materials. The machining parameters discharge current and pulse duration were chosen to determine the effects on material removal rate and surface roughness.Experiment results indicate that the MRR of the combined machining is 1.2~3 times of EDM’s one. Furthermore, the value of surface roughness is also reduced. Therefore, the introduction of magnetic field to EDM has important academic and practical values to the development of EDM.

scholarly journals Evolutionary Techniques for Process Modelling and Optimization in Turning Ti-6al-4v Alloy

2019 ◽  
Vol 8 (4) ◽  
pp. 9377-9381
Keyword(s):  
Material Removal ◽  
Removal Rate ◽  
Optimization Technique ◽  
Process Modelling ◽  
Ti6al4v Alloy ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Nsga Ii ◽  
Expression Program ◽  
Modelling And Optimization

Turning of Ti6Al4V alloy presents a great challenge and opportunity for the machinist. In this paper, multi-target and process modelling advancement of a machining parameters in plain turning of Ti6Al4V alloy are presented using two evolutionary approaches namely Gene Expression Program (GEP) and Non-Dominated Sorting Genetic Algorithm II (NSGA II).The three controlling factors in turning namely, speed (N), feed rate (f)and depth of cut (Dc) are designed as a input parameters, while Material Removal Rate (MRR) and Surface Roughness(Ra) are the measured outputs. The data used in the GEP model is taken by doing several turning experiments within the experimental domain. As the responses MRR and Ra are conflicting in nature, so that NSGA-II has been used as it is a multi-objective optimization technique to obtain the optimal solutions.

Performance Analysis on Eco-friendly Machining of Ti6Al4V using Powder Mixed with Different Dielectrics in WEDM

2020 ◽  
Vol 17 (3) ◽  
pp. 8128-8139
Author(s):  
S. Chakraborty ◽  
S. Mitra ◽  
D. Bose
Keyword(s):  
Metal Removal ◽  
Removal Rate ◽  
Machining Process ◽  
Process Efficiency ◽  
Machining Parameters ◽  
Dielectric Fluids ◽  
High Emission ◽  
Pulse On Time ◽  
Pulse Off Time ◽  
Wedm Process

The recent scenario of modern manufacturing is tremendously improved in the sense of precision machining and abstaining from environmental pollution and hazard issues. In the present work, Ti6Al4V is machined through wire EDM (WEDM) process with powder mixed dielectric and analyzed the influence of input parameters and inherent hazard issues. WEDM has different parameters such as peak current, pulse on time, pulse off time, gap voltage, wire speed, wire tension and so on, as well as dielectrics with powder mixed. These are playing an essential role in WEDM performances to improve the process efficiency by developing the surface texture, microhardness, and metal removal rate. Even though the parameter’s influencing, the study of environmental effect in the WEDM process is very essential during the machining process due to the high emission of toxic vapour by the high discharge energy. In the present study, three different dielectric fluids were used, including deionised water, kerosene, and surfactant added deionised water and analysed the data by taking one factor at a time (OFAT) approach. From this study, it is established that dielectric types and powder significantly improve performances with proper set of machining parameters and find out the risk factor associated with the PMWEDM process.

Instability Parameter for Machined Parts

1983 ◽  
Vol 105 (3) ◽  
pp. 133-136 ◽  
Author(s):  
A. Israeli ◽  
J. Benedek
Keyword(s):  
Residual Stress ◽  
Residual Stresses ◽  
Single Point ◽  
Machining Parameters ◽  
Machining Processes ◽  
Etching Technique ◽  
Parametric Relationship ◽  
Machined Parts ◽  
Instability Parameter ◽  
Stress Profiles

The production of precision parts requires manufacturing processes which produce low residual stresses. This study was designed to investigate the parametric relationship between machining processes and residual stress distribution. Sets of steel specimens were single point turned at different feeds. The residual stress profiles of these specimens were monitored, using a continuous etching technique. A “Specific Instability Potential” parameter, derived from the strain energy of the residual stresses, was found to relate directly to the machining parameters. It is suggested that the Specific Instability Potential can be used as a parameter for specifying processing operations.

Quantification of tool chatter and metal removal rate using wavelet denoising and statistical approach

2018 ◽  
Vol 49 (2) ◽  
pp. 62-81 ◽  
Author(s):  
Shailendra Kumar ◽  
Bhagat Singh
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Metal Removal ◽  
Removal Rate ◽  
Statistical Significance ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Metal Removal Rate ◽  
Chatter Index ◽  
Tool Chatter

Tool chatter is an unavoidable phenomenon encountered in machining processes. Acquired raw chatter signals are contaminated with various types of ambient noises. Signal processing is an efficient technique to explore chatter as it eliminates unwanted background noise present in the raw signal. In this study, experimentally recorded raw chatter signals have been denoised using wavelet transform in order to eliminate the unwanted noise inclusions. Moreover, effect of machining parameters such as depth of cut ( d), feed rate ( f) and spindle speed ( N) on chatter severity and metal removal rate has been ascertained experimentally. Furthermore, in order to quantify the chatter severity, a new parameter called chatter index has been evaluated considering aforesaid denoised signals. A set of 15 experimental runs have been performed using Box–Behnken design of experiment. These experimental observations have been used to develop mathematical models for chatter index and metal removal rate considering response surface methodology. In order to check the statistical significance of control parameters, analysis of variance has been performed. Furthermore, more experiments are conducted and these results are compared with the theoretical ones in order to validate the developed response surface methodology model.

A Mechanistic Approach to the Prediction of Material Removal Rates in Rotary Ultrasonic Machining

1995 ◽  
Vol 117 (2) ◽  
pp. 142-151 ◽  
Author(s):  
Z. J. Pei ◽  
D. Prabhakar ◽  
P. M. Ferreira ◽  
M. Haselkorn
Keyword(s):  
Material Removal Rate ◽  
Material Removal ◽  
Removal Rate ◽  
Diamond Particle ◽  
Machining Parameters ◽  
Ultrasonic Machining ◽  
Rotary Ultrasonic Machining ◽  
Stabilized Zirconia ◽  
Mechanistic Approach ◽  
Wide Range

An approach to modeling the material removal rate (MRR) during rotary ultrasonic machining (RUM) of ceramics is proposed and applied to predicting the MRR for the case of magnesia stabilized zirconia. The model, a first attempt at predicting the MRR in RUM, is based on the assumption that brittle fracture is the primary mechanism of material removal. To justify this assumption, a model parameter (which models the ratio of the fractured volume to the indented volume of a single diamond particle) is shown to be invariant for most machining conditions. The model is mechanistic in the sense that this parameter can be observed experimentally from a few experiments for a particular material and then used in prediction of MRR over a wide range of process parameters. This is demonstrated for magnesia stabilized zirconia, where very good predictions are obtained using an estimate of this single parameter. On the basis of this model, relations between the material removal rate and the controllable machining parameters are deduced. These relationships agree well with the trends observed by experimental observations made by other investigators.

Multiresponse Optimization of Al Alloy-SiC Composite Machining Parameters for Minimum Tool Wear and Maximum Metal Removal Rate

2013 ◽  
Vol 135 (2) ◽  
Author(s):  
Rajesh Kumar Bhushan
Keyword(s):  
Tool Wear ◽  
Metal Removal ◽  
Removal Rate ◽  
Cutting Speed ◽  
Depth Of Cut ◽  
Al Alloy ◽  
Machining Parameters ◽  
Metal Removal Rate ◽  
Nose Radius ◽  
Multiresponse Optimization

Optimization in turning means determination of the optimal set of the machining parameters to satisfy the objectives within the operational constraints. These objectives may be the minimum tool wear, the maximum metal removal rate (MRR), or any weighted combination of both. The main machining parameters which are considered as variables of the optimization are the cutting speed, feed rate, depth of cut, and nose radius. The optimum set of these four input parameters is determined for a particular job-tool combination of 7075Al alloy-15 wt. % SiC (20–40 μm) composite and tungsten carbide tool during a single-pass turning which minimizes the tool wear and maximizes the metal removal rate. The regression models, developed for the minimum tool wear and the maximum MRR were used for finding the multiresponse optimization solutions. To obtain a trade-off between the tool wear and MRR the, a method for simultaneous optimization of the multiple responses based on an overall desirability function was used. The research deals with the optimization of multiple surface roughness parameters along with MRR in search of an optimal parametric combination (favorable process environment) capable of producing desired surface quality of the turned product in a relatively lesser time (enhancement in productivity). The multi-objective optimization resulted in a cutting speed of 210 m/min, a feed of 0.16 mm/rev, a depth of cut of 0.42 mm, and a nose radius of 0.40 mm. These machining conditions are expected to respond with the minimum tool wear and maximum the MRR, which correspond to a satisfactory overall desirability.

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