Vellore Institute of Technology (VIT) is a private university located in&nbsp;Tamil Nadu, India. Founded in 1984, as Vellore Engineering College, the institution offers 20 undergraduate, 34 postgraduate, four integrated and four research programs. It has campuses in Vellore, Amravati, Bhopal and Chennai.

VIT is one of the top ranked private universities in India according to NIRF, THE and QS Rankings.&nbsp;Govt. of India has recognized&nbsp;VIT, Vellore as an&nbsp;Institution of Eminence. This has allowed VIT to take independent quality initiatives and move up in world ranking.

&nbsp;

&nbsp;

VIT University

In this work, machinability studies of AISI D2 steel on a die-sinking electrical discharge machine (EDM) using brass tool has been reported. A response surface methodology (RSM) is adopted to establish effect of various process parameters on important responses. Data envelopment analysis (DEA) is adopted to obtain relative efficiency for each experimental run treating them as decision making units (DMUs). Considering the relative efficiency as an equivalent response, the effect of each processing parameter is analysed and the optimal setting is reported. With the best combination of parameter setting, a thermo-physical model is developed to validate the optimal setting. Copyright © 2015 Inderscience Enterprises Ltd.

Department of Manufacturing Engineering

School of Mechanical Engineering

Vellore Campus

World University root node

International Journal of Productivity and Quality Management

Multi-response optimisation of EDM parameters using data envelopment analysis

In the present study, a Box-Behnken design of experiment strategy is adopted to obtain necessary information from a proposed numerical simulation model using thermal-structural analysis with reduced number of runs. Influence of important process parameters on several output responses has been studied to gain insight into machining performance. The numerical model is validated through conducting necessary experiments. Subsequently, artificial neural network (ANN) is used to establish relation between input parameters and the responses. The model provides an inexpensive and time saving alternative to study the performance of machining before actual cutting operation. The model can be used for selecting ideal process states to improve machining efficiency. Copyright © 2015 Inderscience Enterprises Ltd.

A thermal-structural model for process performance analysis

In the present work, computational fluid dynamics (CFD) together with multi-objective optimization study of an internally finned tube has been performed using the response surface methodology (RSM). For the optimization, the Box-Behnken of response surface methodology (RSM) is exploited from the Design Expert 7.0.0 software. The effects of the fin height, fin width and the fin number on the heat transfer enhancement in the form of Nusselt number (Nu) and friction factor multiplied by Reynolds number (fRe) have been investigated. The results of the numerical model are compared with the analytical results for validation of the model. Finally a non-dominated sorting genetic algorithm (NSGA) has been proposed for the multi objective optimization of the responses. It was found that numerical and RSM can be applied for optimization of heat transfer analysis of internally finned tube. The results show that at the lower level of fin height, the Nusselt number has an increasing trend with the increase in fin number but decreases beyond fin number of 7. Similar trend is also observed at higher level of fin height. Moreover, it is found that the contribution of fin thickness, for variations of Nusselt number (Nu) and (fRe), is not significant as compared to fin height and fin number.

Journal of Thermal Engineering

Multi - objective optimization of a three-dimensional internally finned tube based on Response Surface Methodology (RSM)

AA6061 aluminum alloy is widely used for fabrication of light weight structures requiring a high strength to weight ratio in aerospace, naval, rail and automotive industries. As compared to the traditional fusion welding processes which are commonly used for joining structural aluminum alloys, friction stir welding (FSW) process is an emerging solid state joining process in which the material that is being welded does not melt and recast. In view of this, the present work proposes an experimental investigation, to analyze the effect of welding parameters such as welding speed, tool rotational speed and tool profile on welding strength. The experimental architecture is planned as per Taguchi's L9 orthogonal array so as to extract maximum information with minimum experimental runs. The study revealed that welding speed is an important parameter for the variation of tensile strength. © 2015 Elsevier Ltd.

Materials Today: Proceedings

Parametric Investigation of Friction Stir Welding on AA6061 Using Taguchi technique

Present work proposes a thermo-numerical model for accurate prediction of material removal and tool erosion for electrical discharge machining (EDM) process. The data collected for the numerical analysis is based on Box-Behnken’s experimental design, a popular response surface methodology (RSM) approach. The numerical model is validated by comparing experimental results on a die sinking EDM machine. A sequentially coupled thermo-structural model has also been proposed to estimate the residual stress distribution on the work piece. Analysis of variance is conducted to identify significant parameters. Regression analysis is conducted on the model to develop valid mathematical models relating responses with process parameters. Finally, a multi objective particle swam (MOPSO) algorithm has been adopted for simultaneous optimization of responses. The proposed model can be employed for selecting ideal process states to improve process productivity and finishing capabilities. © Springer International Publishing Switzerland 2015.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

A particle swarm approach embedded with numerical analysis for multi-response optimization in electrical discharge machining

Present research proposes an optimization methodology for the selection of best process parameters in multi-response situation. Experiments have been conducted on a die-sinking electric discharge machine under different conditions of process parameters. A response surface methodology (RSM) is adopted to establish effect of various process parameters such as discharge current (Ip), pulse on time (Ton), duty factor (τ) and flushing pressure (Fp) on four important responses like material removal rate (MRR), tool wear rate (TWR), surface roughness (Ra) and circularity (r1/r2) of machined component. Since the natures of responses are contradicting in nature, it is difficult to find a single combination of machining parameters that provides the best performance satisfying all responses simultaneously. In order to achieve best machining condition, an equivalent single response capable of representing all individual responses is needed. The work includes data envelopment analysis (DEA) to obtain relative efficiency for each experimental run treating as decision making unit (DMU). Each DMU is evaluated using LINGO software to obtain relative efficiency. The relative efficiency is ranked in ascending order and average ranked value (ARV) is calculated to find the optimal solution. Finally, the optimal setting capable of improving all the responses simultaneously is found to be Ip=7 amp, Ton= 200 ,μs, τ =90% and Fp = 0.4 kg/cm 2. With this best combination of factorial level, the experimental values of responses are obtained as MRR=13.9600 mm3/min, TWR=0.0201 mm3/min, Ra=4.9300 μm and circularity= 0.8401. © 2012 Published by Elsevier Ltd.

Fulltext

Procedia Engineering

A DEA approach for optimization of multiple responses in electrical discharge machining of AISI D2 steel

Electrochemical machining (ECM) is one of the non-conventional machining processes which is mostly used to machine difficult-to-machine materials such as super alloys, Ti-alloys, stainless steel, alloy steel etc. The major requirement of the process is that work piece should be electrically conducting in nature. A large number of parameters influence material removal rate (MRR) and surface roughness (SR) of parts produced by ECM. Usually, tool makers use thumb rules and machine manuals to set optimal parameters for the process. In this work, response surface methodology is adopted to study the effect of four important parameters such as current, voltage, flow rate of electrolyte and inter-electrode gap on MRR and SR. Statistically validated regression equation are developed relating response like MRR and SR with input parameters. Finally, a non-dominated sorted genetic algorithm is used to find out the optimal process parameters that simultaneously maximize MRR and minimize SR. The set of Pareto solutions provide flexibility to the tool makers to choose the best setting depending on applications. © 2012 Published by Elsevier Ltd.

Multi-objective optimization of electrochemical machining of hardened steel using NSGA II

In the present work, a thermal-structural model is presented to analyze the process parameters and their effect on three important responses such as material removal rate, tool wear rate and residual stresses on work piece in electrical discharge machining (EDM) process. The numerical model is validated conducting experiments on a die-sinking EDM machine. The numerical method provides an inexpensive and time saving alternative to study the performance of machining before actual cutting operation. A Box-Behnkin design of response surface methodology is adopted to collect data for analysis. Regression analysis is conducted to develop equations relating responses with process parameters. Finally, non-dominated sorting genetic algorithm is used to obtain pareto optimal solution for multi objective optimization. © 2012 Published by Elsevier Ltd.

Thermal-structural analysis of electrical discharge machining process

This article presents a new automated modelling system to aid in collaborative designing with heterogeneous computer-aided design (CAD) agents. It is a multi-user based modelling process but is less time consuming. The article presents an effective data transmission and transformation technique to ease the mode of information sharing. The complete assembling system has been considered as a discrete event system with an automated coordinator. The automated coordinator has all the logical inputs to make the decisions. Our idea focuses on application of automata theory to the coordination of heterogeneous CAD systems. The proposed methodology has been applied to an illustrated example taken from literature for a better understanding of the model. © 2011 Taylor & Francis.