Multi-Objective Optimization of Microturning Process Parameters Using Particle Swarm Technique

2013 ◽  
Author(s):  
Nithin Tom Mathew ◽  
Kanthababu Mani
Keyword(s):  
Tool Wear ◽  
Process Parameters ◽  
Removal Rate ◽  
Computational Cost ◽  
Particle Swarm ◽  
Depth Of Cut ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Confirmation Test ◽  
First Time

In this work, for the first time an attempt has been made to carry out multi-objective optimization for tool based microturning process parameters using particle swarm optimization (PSO) technique. The input microturning process parameters considered are speed, feed and depth of cut. The output parameters considered are material removal rate (MRR), surface roughness (Ra) and tool wear (TW). The significant parameters are identified individually using ANOVA and main effect plots. However, it is observed that the main goal of the manufacturers is to produce high quality products in shorter interval of time. In order to meet the above objective, multi-objective optimization is carried out to achieve simultaneously higher MRR, low Ra and low TW using PSO. From the PSO analysis, it is observed that the combination of microturning parameters such as speed (18.25 m/min), feed (9.31 μm/rev) and depth of cut (14.61 μm) results in high MRR, low Ra and low tool wear. The PSO analysis indicates that it is a promising optimization algorithm due to its simplicity, low computational cost and good performance. A confirmation test was carried out to validate the predicted results.

Multi-Objective Optimization of Abrasive Waterjet Machining Process Parameters Using Particle Swarm Technique

2014 ◽  
Vol 1 (2) ◽  
pp. 62-79
Author(s):  
V. Murugabalaji ◽  
M. Kanthababu ◽  
J. Jegaraj ◽  
S. Saikumar
Keyword(s):  
Response Surface ◽  
Process Parameters ◽  
Particle Swarm ◽  
Mesh Size ◽  
Machining Process ◽  
Abrasive Waterjet ◽  
Depth Of Cut ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Abrasive Waterjet Machining

Multi-objective optimization is carried out for the first time to optimize abrasive water jet machining (AWJM) process parameters for graphite. Experiments are carried out by Response Surface Methodology (RSM) using Box-Behnken method. The input process parameters considered are pressure (P), traverse rate (TR) and mesh size (MS). Results are analyzed using Analysis of Variance (ANOVA) and response surface considering individually output parameters such as depth of cut (DOC) and surface roughness (Ra). ANOVA and response surface analyses indicated that similar combinations of AWJM process parameters such as high pressure (176 MPa), medium mesh size (# 100) and low traverse rate (1000 mm/min) resulted in higher depth of cut as well as lower Ra. Therefore, in order to verify the above combinations and to improve productivity, multi-objective optimization is carried out using Particle Swarm Optimization (PSO) to achieve higher depth of cut and low Ra together. From the PSO analysis, it is observed that pressure of 154 MPa, traverse rate of 1877 mm/min and mesh size of # 100 result in high depth of cut and low Ra together. The result obtained from the PSO is compared with that of ANOVA. The outcome of this study will be useful to the manufacturing engineers for selecting appropriate input AWJM process parameters for machining graphite, which has various applications such as aerospace, defence, etc.

scholarly journals Optimization of process parameters for surface roughness and tool wear in milling TC17 alloy using Taguchi with grey relational analysis

2021 ◽  
Vol 13 (2) ◽  
pp. 168781402199653
Author(s):  
Zhe Wang ◽  
Lei Li
Keyword(s):  
Surface Roughness ◽  
Tool Wear ◽  
Process Parameters ◽  
Critical Role ◽  
Optimization Method ◽  
Ratio Method ◽  
Multi Objective Optimization ◽  
Processing Efficiency ◽  
Multi Objective ◽  
Process Guidance

To improve machining quality and processing efficiency, the Taguchi analysis method is employed to design the milling tests of titanium alloy TC17. According to results based on the signal-to-noise ratio method, the cutting depth plays a critical role in improving the surface roughness and tool wear. The grey correlation analysis is a multi-objective optimization method that can help to acquire process parameters combination of the optimal surface roughness and the optimal tool wear. Finally, the correctness of multi-objective optimization results is verified through comparison experiments. The research results can provide process guidance and data reference for the actual production processing.

scholarly journals Predictive Modelling and Multi-Objective Optimization of Surface Integrity Parameters in Sustainable Machining Processes of Magnesium Alloy

Materials ◽  
2021 ◽  
Vol 14 (13) ◽  
pp. 3547
Author(s):  
Mohd Danish ◽  
Saeed Rubaiee ◽  
Hassan Ijaz
Keyword(s):  
Surface Roughness ◽  
Magnesium Alloy ◽  
Magnesium Alloys ◽  
Surface Integrity ◽  
Removal Rate ◽  
Cryogenic Cooling ◽  
Depth Of Cut ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Cooling Conditions

Magnesium alloys are widely used in numerous engineering applications owing to their superior structural characteristics. However, the machining of magnesium alloy is challenging because of its poor machinability characteristics. Therefore, this paper investigates the machining of magnesium alloys under different sustainable cooling conditions. The machining was performed by varying cutting velocity, feed rate, and depth of cut under dry and cryogenic cooling conditions. The primary focus of the paper is to develop a predictive model for surface roughness under different machining environments. The models developed were found to be in excellent agreement with experimental results, with only 0.3 to 1.6% error. Multi-objective optimization were also performed so that the best surface finish together with high material removal rate could be achieved. Furthermore, the various parameters of surface integrity (i.e., surface roughness, micro-hardness, micro-structures, crystallite size, and lattice strain) were also investigated.

Multi-Objective Optimization of CNC Turning Machining Parameters

2014 ◽  
Vol 1016 ◽  
pp. 172-176 ◽  
Author(s):  
Sharad Kumar Pradhan ◽  
Surendra Kumar Saini
Keyword(s):  
Material Removal Rate ◽  
Material Removal ◽  
Removal Rate ◽  
Spindle Speed ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Multi Objective Optimization ◽  
Cnc Turning ◽  
Multi Objective ◽  
Machining Parameter

An experimental investigation into CNC turning operation on Brass C36000 alloy as work piece material which is widely used for various industrial applications is performed. Multi objective optimization is carried out to find out the influencing machining parameters among spindle speed (rpm), feed (mm per revolution) and depth of cut (mm) for CNC turning of Brass C36000 alloy with surface finish and Material Removal Rate as performance parameters using Taguchi method. Taguchi orthogonal array [L27(33)] is used for the experimental design. All experiments are conducted using EMCO Concept Turn 250 machine tool with carbide insert cutting tool. The optimization result shows that feed is the most significant turning machining parameter for surface roughness while depth of cut has high influence on material removal rate followed by spindle speed during CNC turning of Brass C36000 alloy. Above results is further validated using ANOVA approach.

Multi-Objective Optimization using Grey Relational Taguchi Analysis in Machining

2016 ◽  
Vol 6 (4) ◽  
pp. 45-64 ◽  
Author(s):  
Nirmal S. Kalsi ◽  
Rakesh Sehgal ◽  
Vishal S. Sharma
Keyword(s):  
Metal Cutting ◽  
Removal Rate ◽  
Cutting Tools ◽  
Cutting Speed ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Recent Approach ◽  
Grey Relational

Multi-objective optimization is becoming important day by day due to increase in complexity of the processes and expectations of more reliable solutions. In view of the complexity of the process, controlling the machining parameters without compromising on the response parameters is a tedious process. In the recent approach, researchers have used many combinations of available techniques to solve multi performance characteristic problems depending upon the situation and accuracy desired in the results, to make the results more reliable. In this paper, the authors have pronounced and used a combination of grey relational and Taguchi based analysis to optimize a multi-objective metal cutting process to yield maximum performance of cutting tools in turning. Main cutting force, power consumption, tool wear and material removal rate were evaluated used L18 orthogonal array considering cutting speed, feed rate and depth of cut, using cryogenically treated and untreated tungsten carbide cutting tool inserts.

MULTI-OBJECTIVE OPTIMIZATION OF TURNING PARAMETERS USING THE COMBINED MOORA AND ENTROPY METHOD

2016 ◽  
Vol 40 (1) ◽  
pp. 101-111 ◽  
Author(s):  
B. Singaravel ◽  
T. Selvaraj ◽  
S. Vinodh
Keyword(s):  
Removal Rate ◽  
Cutting Speed ◽  
Entropy Method ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Multi Objective Optimization ◽  
Nose Radius ◽  
Multi Objective ◽  
Entropy Measurement ◽  
Coated Carbide

Selection of optimum machining parameters in machining operations leads to good functional attributes for the machined components and increased productivity. In this work, machining parameters and nose radius are optimized in turning of EN25 steel with coated carbide tool by the application of combined Multi-Objective Optimization by Ratio Analysis (MOORA) and entropy measurement method. The selected machining parameters are cutting speed, feed rate, depth of cut and nose radius for minimization of surface roughness, micro-hardness and maximization of Material Removal Rate (MRR). Entropy concept has been used to assign the weight criteria of each objective being considered. The optimum combination of machining parameters and nose radius are obtained using normalized assessment values. The results obtained in the analysis are validated and the results based on turning process responses can be effectively improved.

MULTI-OBJECTIVE OPTIMIZATION OF EDM PROCESS PARAMETERS FOR MACHINING OF HYBRID ALUMINUM METAL MATRIX COMPOSITES (Al7075/TiC/B4C) USING GENETIC ALGORITHM

2019 ◽  
Vol 26 (10) ◽  
pp. 1950071 ◽  
Author(s):  
K. PONAPPA ◽  
K. S. K. SASIKUMAR ◽  
M. SAMBATHKUMAR ◽  
M. UDHAYAKUMAR
Keyword(s):  
Genetic Algorithm ◽  
Process Parameters ◽  
Pulse Current ◽  
Metal Removal ◽  
Removal Rate ◽  
Optimum Process ◽  
Multi Objective Optimization ◽  
Influence Of Process Parameters ◽  
Scanning Electron Microscope Study ◽  
Multi Objective

This study deals with the investigation on the effect of Electrical Discharge Machining (EDM) parameters during machining of hybrid composite (Al 7075/TiC/B4C). The optimum process parameters of die sinking EDM like pulse current, pulse duration and gap voltage on metal removal rate, tool wear rate and surface finish were investigated. Full factorial experimental design was selected for experiments. Analysis of variance was employed to study the influence of process parameters and their interactions on response variables. Among the process parameters considered, it was observed that the pulse current was found to be more influential in affecting MRR, TWR and SR. The other parameters have little effect on the response variable. Multi-objective optimization study was also performed using genetic algorithm to find the optimum parameter setting for controversial objective function combination such as high MRR and low SR and High MRR and low TWR. Scanning electron microscope study was performed to study the surface characteristics.

Multi objective optimization of ECG process under fuzzy environment

2015 ◽  
Vol 11 (3) ◽  
pp. 350-371 ◽  
Author(s):  
G K Bose
Keyword(s):  
Process Parameters ◽  
Supply Voltage ◽  
Optimization Technique ◽  
Research Work ◽  
Experimental Studies ◽  
Depth Of Cut ◽  
Multi Objective Optimization ◽  
Content Type ◽  
Multi Objective ◽  
Machining Parameter

Purpose – In the present research work electrochemical grinding (ECG) process is applied to machine Al2O3/Al interpenetrating phase composite. The purpose of this paper is to present a new approach to optimize the ECG process parameters while machining alumina-aluminum (Al2O3 – Al) interpenetrating phase composites (IPC) used in automotive, aircraft and manufacture of space ships applying Taguchi-based experimental studies and fuzzy multi-criteria decision-making techniques. Design/methodology/approach – The present work identifies the process variables that have significant consequences during ECG of Al2O3/Al IPC. The Taguchi L9 orthogonal array is selected for design of experiments and the analysis is carried out following signal to noise ratio. The analysis of variance is carried out to establish the factors that significantly influence the responses. The present work also investigates the multi objective optimization of ECG process parameters using VIseKriterijumsa Optimizacija I Kompromisno Resenje (VIKOR) and Grey relational analysis (GRA) to establish the reference ranking from a set of alternatives in the presence of conflicting criteria. Findings – Material removal rate, surface finish, overcut and cutting force are shown to depend on the type of electrolyte, supply voltage, depth of cut and electrolyte flow rate. It is found that voltage and electrolyte concentration are important. The optimal machining parameter combination for ECG process is determined using fuzzy set theory, VIKOR and GRA. Substantial improvement in machining performance takes place. Practical implications – A variety of manufacturing techniques are available for processing of Al2O3 – Al metal matrix composites. Generally manufacturers favor low cost modus operandi. Therefore ECG process is the best alternative for processing of MMCs in the present commercial sectors. The experimental investigation approach can act as useful and an efficient guideline for manufacturing. Originality/value – The characteristic features of the ECG process are reflected through Taguchi design-based experimental studies with various process parametric combinations. Application of multi-response optimization technique for evaluation of best parametric combination for machining Al2O3 – Al IPC material using ECG process is a first-of-its-kind approach in literature.

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