MRR | p. 7 | Scientific.Net

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class="pagination"><li class="PagedList-skipToFirst"><a href="/paper-keyword/mrr/1"><<</a></li><li class="PagedList-skipToPrevious"><a href="/paper-keyword/mrr/6" rel="prev"><</a></li><li class="PagedList-ellipses"><a class="PagedList-skipToPrevious" href="/paper-keyword/mrr/3" rel="prev">…</a></li><li><a href="/paper-keyword/mrr/4">4</a></li><li><a href="/paper-keyword/mrr/5">5</a></li><li><a href="/paper-keyword/mrr/6">6</a></li><li class="active"><span>7</span></li><li><a href="/paper-keyword/mrr/8">8</a></li><li class="PagedList-skipToNext"><a href="/paper-keyword/mrr/8" rel="next">></a></li></ul></div> </div> <div class="block-volume-title normal-text-gray"> <p> Paper Title<span>Page</span> </p> </div> <div class="item-block"> <div class="item-link"> <a href="/AMR.383-390.3202">Parametric Optimization of PMEDM Process with Chromium Powder Suspended Dielectric for Minimum Surface Roughness and Maximum MRR</a> </div> <div class="item-link volume-authors"> <div class="semibold-middle-text"> Authors: Rajiv Kumar Garg, Kuldeep Ojha </div> </div> <div id="abstractTextBlock152808" class="volume-info volume-info-text volume-info-description"> Abstract: In this article, parametric optimization for material removal rate (MRR) and surface roughness (SR) study on the powder mixed electrical discharge machining (PMEDM) of EN-8 steel has been carried out. Response surface methodology (RSM) has been used to plan and analyze the experiments. Average current, duty cycle, diameter of electrode and concentration of micro-nickel powder added into dielectric fluid of EDM were chosen as process parameters to study the PMEDM performance in terms of MRR and SR. Experiments have been performed on newly designed experimental setup developed in laboratory. Most important parameters affecting selected performance measures have been identified and effects of their variations have been observed. </div> <div> <a data-readmore="{ block: '#abstractTextBlock152808', lines: 2, expandText: '...more', collapseText: '...less' }"></a> </div> <div class="page-number semibold-large-text"> 3202 </div> </div> <div class="item-block"> <div class="item-link"> <a href="/AMM.110-116.250">Simultaneous Optimization of Multiple Quality Characteristics in Electrical Discharge Diamond Cut-Off Grinding (EDDCG)</a> </div> <div class="item-link volume-authors"> <div class="semibold-middle-text"> Authors: S. K. S. Yadav, Vinod Yadava </div> </div> <div id="abstractTextBlock146057" class="volume-info volume-info-text volume-info-description"> Abstract: This paper presents the simultaneous optimization of multiple quality characteristics (Material removal rate and Average surface roughness) using Taguchi method for electrical discharge diamond cut-off grinding (EDDCG) during machining of cemented carbides material. The experiments are carried out on a self-developed electrical discharge diamond grinding setup in cut-off mode, In the present work four input parameters ( current, pulse on-time, duty factor and wheel RPM ) were selected in which each parameter was at three levels. The total degree of freedom (dof) has been calculated without considering the effects of interaction among the different control factors. Based on design of experiments (DOE), a standard L9 orthogonal array (OA) was taken for experimentation. The result shows the considerable improvement of 13.999dB in multiple S/N ratio as compared to initial condition. Also, the comparison of results from single and multi-objective optimization has been presented. </div> <div> <a data-readmore="{ block: '#abstractTextBlock146057', lines: 2, expandText: '...more', collapseText: '...less' }"></a> </div> <div class="page-number semibold-large-text"> 250 </div> </div> <div class="item-block"> <div class="item-link"> <a href="/AMM.110-116.1683">Performance Measurement and Data Analysis of Material Removal Rate for Wire Cut Electro Discharge Machining Process</a> </div> <div class="item-link volume-authors"> <div class="semibold-middle-text"> Authors: Vishal Parashar, A. Rehman, J.L. Bhagoria </div> </div> <div id="abstractTextBlock145822" class="volume-info volume-info-text volume-info-description"> Abstract: In this paper, statistical and regression analysis of material removal rate using design of experiments is proposed for WEDM operations. Experimentation was planned as per Taguchi’s mixed orthogonal array. Each experiment has been performed under different cutting conditions of gap voltage, pulse ON time, pulse OFF time, wire feed and dielectric flushing pressure. Stainless Steel grade 304L was selected as a work material to conduct the experiments. From experimental results, the material removal rate was determined for each machining performance criteria. Analysis of variance (ANOVA) technique was used to find out the variables affecting the material removal rate. Assumptions of ANOVA were discussed and carefully examined using analysis of residuals. Variation of the material removal rate with machining parameters was mathematically modeled by using the regression analysis method. The developed model was validated with a set of experimental data and appeared to be satisfactory. Signal to noise ratio was applied to measure the performance characteristics deviating from the actual value. Finally, experimental confirmation was carried out to identify the effectiveness of this proposed method. </div> <div> <a data-readmore="{ block: '#abstractTextBlock145822', lines: 2, expandText: '...more', collapseText: '...less' }"></a> </div> <div class="page-number semibold-large-text"> 1683 </div> </div> <div class="item-block"> <div class="item-link"> <a href="/AMR.341-342.400">Investigation of Liquid Nitrogen (LN<sub>2</sub>) as Coolant in Grinding of AISI D3 Steel</a> </div> <div class="item-link volume-authors"> <div class="semibold-middle-text"> Authors: G. Manimaran, Murugasan Pradeep Kumar </div> </div> <div id="abstractTextBlock142821" class="volume-info volume-info-text volume-info-description"> Abstract: In order to find the alternative to conventional oil based coolants on the basis of environmental aspects, the present work investigates the effectiveness of Liquid N<sub>2</sub> as eco friendly coolant in the grinding of AISI D3 steel with Aluminum oxide (Al<sub>2</sub>O<sub>3</sub> ) as grinding wheel. The experiment was examined in terms of surface roughness, grinding forces, grinding zone temperature, and material removal rate (MRR) in the Grinding of AISI D3 steel under various grinding conditions. The performances of liquid nitrogen cooling were compared with the conventional oil cooling and found that 30-32% reduction in the surface roughness, 30-34 % reduction in the grinding zone temperature, and about 8 % reduction in grinding forces were observed. It was also found that even at higher MRR, better surface quality obtained. In this study, it is clearly revealed that reduction in the grinding temperature leads to improvements in the grindability and cryogenic cooling by liquid N<sub>2</sub> as better coolant in the grinding of AISI D3 steel. </div> <div> <a data-readmore="{ block: '#abstractTextBlock142821', lines: 2, expandText: '...more', collapseText: '...less' }"></a> </div> <div class="page-number semibold-large-text"> 400 </div> </div> <div class="item-block"> <div class="item-link"> <a href="/AMR.335-336.535">Soft Modeling of Wire Electrical Discharge Machining of WC-Co Composite</a> </div> <div class="item-link volume-authors"> <div class="semibold-middle-text"> Authors: Veluswamy Muthuraman, Raju Ramakrishnan </div> </div> <div id="abstractTextBlock139863" class="volume-info volume-info-text volume-info-description"> Abstract: The prediction of optimal machining conditions for required surface roughness and material removal rate (MRR) plays a very significant role in process planning of wire electrical discharge machining (WEDM). Artificial neural networks (ANN) are widely applied to predict the performance characteristics of complex machining process like WEDM very accurately. This present work deals with the features of cutting operation by WEDM of tungsten carbide- cobalt composite(WC – Co) and an artificial neural networks(ANN) model in terms of machining parameters, developed to predict surface roughness(Ra) and material removal rate (MRR).The experiment was planned as per Taguchi’s L 27 orthogonal array. The predictive capacity of the models was validated. The test results indicate that the proposed models could adequately describe the performance indicators with the limits of the factors that are being investigated. Finally the accuracy of the developed ANN model was compared to the experimental values. It was observed that the proposed ANN model is good. </div> <div> <a data-readmore="{ block: '#abstractTextBlock139863', lines: 2, expandText: '...more', collapseText: '...less' }"></a> </div> <div class="page-number semibold-large-text"> 535 </div> </div> <div class="item-block"> <div class="item-link"> <a href="/KEM.487.293">Research on Material Removal Characteristics in Plane Lapping Method for Aspherical Surface Using Elastic Deformation</a> </div> <div class="item-link volume-authors"> <div class="semibold-middle-text"> Authors: Zhe Wu, Ju Long Yuan, Bing Hai Lv, Duc Nam Nguyen </div> </div> <div id="abstractTextBlock131462" class="volume-info volume-info-text volume-info-description"> Abstract: Plane lapping method using the elasticity of materials has many advantages comparing with current machining method for aspherical surface machining. Due to the deformation of the workpiece, the material removal characteristics of this method are different from the traditional lapping process of flat surface. In this paper, based on the Preston equation and plate theory, the theoretical model of the material remove rate is built in the case of proving experiment. Then the proving experiment of elastic deformation method is carried out, the recorded values fit well with theoretical ones, which shows that the theoretical model of material removal property is valid and the variation of MRR is related to the deformed profile of workpiece. </div> <div> <a data-readmore="{ block: '#abstractTextBlock131462', lines: 2, expandText: '...more', collapseText: '...less' }"></a> </div> <div class="page-number semibold-large-text"> 293 </div> </div> <div class="item-block"> <div class="item-link"> <a href="/AMR.264-265.985">Pareto Optimization of Electro Discharge Machining of Titanium Nitride-Aluminium Oxide Composite Material Using Genetic Algorithm</a> </div> <div class="item-link volume-authors"> <div class="semibold-middle-text"> Authors: Souren Mitra, Soumya Sarkar, Goutam Paul, D. Bhaduri, Sampad Biswas </div> </div> <div id="abstractTextBlock106299" class="volume-info volume-info-text volume-info-description"> Abstract: Titanium nitride-aluminium oxide (TiN-Al2O3) is a new generation ceramic composite material having potential for many industrial applications as it possess high resistance to thermal degradation, anti-wear and anti-abrasion properties. In the present research the characteristic features of EDM process are explored through Taguchi methodology based experimental studies with various process parametric combinations. Finally the process has been optimized using Genetic algorithm based Pareto optimization search. From Pareto optimal search the technology guideline for optimal parameter settings have been selected. The present research approach is extremely useful for maximizing the productivity while maintaining the geometrical accuracy within desired limit. </div> <div> <a data-readmore="{ block: '#abstractTextBlock106299', lines: 2, expandText: '...more', collapseText: '...less' }"></a> </div> <div class="page-number semibold-large-text"> 985 </div> </div> <div class="item-block"> <div class="item-link"> <a href="/AMR.189-193.1393">Optimization of Process Parameters on Ti-6Al-4V Using Central Composite Design Method</a> </div> <div class="item-link volume-authors"> <div class="semibold-middle-text"> Authors: M.M. Rahman </div> </div> <div id="abstractTextBlock102707" class="volume-info volume-info-text volume-info-description"> Abstract: Electrical discharge machining (EDM) is relatively modern machining process having distinct advantages over other machining processes and able to machine Ti-alloys effectively. This paper attempts to investigate the effects of process parameters on output response of titanium alloy Ti-6Al-4V in EDM utilizing copper tungsten as an electrode and positive polarity of the electrode. Mathematical models for material removal rate (MRR), electrode wear rate (EWR) and surface roughness (SR) are developed in this paper. Design of experiments method and response surface methodology techniques are implemented. The validity test of the fit and adequacy of the proposed models has been carried out through analysis of variance. It can be seen that as the peak current increases the TWR decreases till certain ampere and then increases. The excellent surface finish is investigated in this study at short pulse on time and in contrast the long pulse duration causes the lowest EWR. Long pulse off time provides minimum EWR and the impact of pulse interval on EWR depends on peak current. The result leads to wear rate of electrode and economical industrial machining by optimizing the input parameters. It found that the peak current, servo voltage and pulse on time are significant in material removal rate and surface roughness. Peak current has the greater impact on surface roughness and material removal rate. </div> <div> <a data-readmore="{ block: '#abstractTextBlock102707', lines: 2, expandText: '...more', collapseText: '...less' }"></a> </div> <div class="page-number semibold-large-text"> 1393 </div> </div> <div class="item-block"> <div class="item-link"> <a href="/AMR.143-144.1434">Experimental Analysis on Technology of Piezoelectric Self-Adaptive Micro-EDM</a> </div> <div class="item-link volume-authors"> <div class="semibold-middle-text"> Authors: Xiu Zhuo Fu, Qin He Zhang, Guang Hua Bao, Yu Jie Zhu </div> </div> <div id="abstractTextBlock90412" class="volume-info volume-info-text volume-info-description"> Abstract: Micro electrical discharge machining (micro-EDM) has some shortcomings such as poor material removal rate (MRR) and high electrode wear ratio (EWR) etc, in order to overcome these demerits, a new piezoelectric self-adaptive micro-EDM, based on inverse piezoelectric effect, was developed in this paper. The structure and working principle of this new technology are different from traditional micro-EDM. Piezoelectric actuator used as the micro driven mechanism and it is simple. This new technology can realize self-elimination in the working process because of its special structure. Working principles and process of the new system were analyzed in this paper. The effect of parameters such as voltage, capacitance, and resistance on MRR, EWR and surface roughness was analyzed. Statistical analyses of the results show that voltage, capacitance significantly influence MRR, EWR and surface roughness. Resistance R1 and R2 has much influence on MRR and relative small effect on EWR and surface roughness. </div> <div> <a data-readmore="{ block: '#abstractTextBlock90412', lines: 2, expandText: '...more', collapseText: '...less' }"></a> </div> <div class="page-number semibold-large-text"> 1434 </div> </div> <div class="item-block"> <div class="item-link"> <a href="/AMM.29-32.862">Study on Simulation of EDM Milling Technology Based on MATLAB</a> </div> <div class="item-link volume-authors"> <div class="semibold-middle-text"> Authors: Yun Peng Zhang, Wei Zhao, An Zhou Zhang </div> </div> <div id="abstractTextBlock82923" class="volume-info volume-info-text volume-info-description"> Abstract: Due to the complexity of electrical discharge machining (EDM) milling technology, an artificial nerve network simulation and prediction model based on MATLAB for EDM milling technology is proposed. The three -layer BP neural network model is built by applying MATLAB technology and combining with the database toolbox and artificial neural network toolbox in MATLAB, it has the ability of getting experimental data from EDM milling technology database and calculating by neural network and then outputting the prediction result. Finally, the model is used to simulate the relations between material removal rate (MRR), surface roughness and process parameters, and analyzed the technological rule. It is proved that the prediction error is controlled within 10% and the simulation result can successfully map the technological rule of EDM milling technology. </div> <div> <a data-readmore="{ block: '#abstractTextBlock82923', lines: 2, expandText: '...more', collapseText: '...less' }"></a> </div> <div class="page-number semibold-large-text"> 862 </div> </div> <div class="block-bottom-pagination"> <div class="pager-info"> Showing 61 to 70 of 76 Paper Titles </div> <div class="pagination-container"><ul class="pagination"><li class="PagedList-skipToFirst"><a href="/paper-keyword/mrr/1"><<</a></li><li class="PagedList-skipToPrevious"><a href="/paper-keyword/mrr/6" rel="prev"><</a></li><li class="PagedList-ellipses"><a class="PagedList-skipToPrevious" href="/paper-keyword/mrr/3" rel="prev">…</a></li><li><a href="/paper-keyword/mrr/4">4</a></li><li><a href="/paper-keyword/mrr/5">5</a></li><li><a href="/paper-keyword/mrr/6">6</a></li><li class="active"><span>7</span></li><li><a href="/paper-keyword/mrr/8">8</a></li><li class="PagedList-skipToNext"><a href="/paper-keyword/mrr/8" rel="next">></a></li></ul></div> </div> </div> </div> </div> </div> </div> <div class="social-icon-popup"> <a href="https://www.facebook.com/Scientific.Net.Ltd/" target="_blank" rel="noopener" title="Scientific.Net"><i class="inline-icon facebook-popup-icon social-icon"></i></a> <a href="https://twitter.com/Scientific_Net/" target="_blank" rel="noopener" title="Scientific.Net"><i class="inline-icon twitter-popup-icon social-icon"></i></a> <a href="https://www.linkedin.com/company/scientificnet/" target="_blank" rel="noopener" title="Scientific.Net"><i class="inline-icon linkedin-popup-icon social-icon"></i></a> </div> </div> <div class="sc-footer"> <div class="footer-fluid"> <div class="container"> <div class="row"> <div class="footer-menu col-md-12 col-sm-12 col-xs-12"> <ul class="list-inline menu-font"> <li><a href="/ForLibraries">For Libraries</a></li> <li><a href="/ForPublication/Paper">For Publication</a></li> <li><a href="/insights" target="_blank">Insights</a></li> <li><a href="/DocuCenter">Downloads</a></li> <li><a href="/Home/AboutUs">About Us</a></li> <li><a href="/PolicyAndEthics/PublishingPolicies">Policy & Ethics</a></li> <li><a href="/Home/Contacts">Contact Us</a></li> <li><a href="/Home/Imprint">Imprint</a></li> <li><a href="/Home/PrivacyPolicy">Privacy Policy</a></li> <li><a href="/Home/Sitemap">Sitemap</a></li> <li><a href="/Conferences">All Conferences</a></li> <li><a href="/special-issues">All Special Issues</a></li> <li><a href="/news/all">All News</a></li> <li><a href="/read-and-publish-agreements">Read & Publish Agreements</a></li> </ul> </div> </div> </div> </div> <div class="line-footer"></div> <div class="footer-fluid"> <div class="container"> <div class="row"> <div class="col-xs-12"> <a href="https://www.facebook.com/Scientific.Net.Ltd/" target="_blank" rel="noopener" title="Scientific.Net"><i class="inline-icon facebook-footer-icon social-icon"></i></a> <a href="https://twitter.com/Scientific_Net/" target="_blank" rel="noopener" title="Scientific.Net"><i class="inline-icon twitter-footer-icon social-icon"></i></a> <a href="https://www.linkedin.com/company/scientificnet/" target="_blank" rel="noopener" title="Scientific.Net"><i class="inline-icon linkedin-footer-icon social-icon"></i></a> </div> </div> </div> </div> <div class="line-footer"></div> <div class="footer-fluid"> <div class="container"> <div class="row"> <div class="col-xs-12 footer-copyright"> <p> © 2024 Trans Tech Publications Ltd. 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