MRR | p. 5 | 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/4" rel="prev"><</a></li><li class="PagedList-ellipses"><a class="PagedList-skipToPrevious" href="/paper-keyword/mrr/2" rel="prev">…</a></li><li><a href="/paper-keyword/mrr/3">3</a></li><li><a href="/paper-keyword/mrr/4">4</a></li><li class="active"><span>5</span></li><li><a href="/paper-keyword/mrr/6">6</a></li><li><a href="/paper-keyword/mrr/7">7</a></li><li class="PagedList-ellipses"><a class="PagedList-skipToNext" href="/paper-keyword/mrr/8" rel="next">…</a></li><li class="PagedList-skipToNext"><a href="/paper-keyword/mrr/6" rel="next">></a></li><li class="PagedList-skipToLast"><a href="/paper-keyword/mrr/8">>></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="/AMM.592-594.525">Multi Criteria Optimization of Electrochemical Discharge Micro-Machining Process during Micro-Channel Generation on Glass</a> </div> <div class="item-link volume-authors"> <div class="semibold-middle-text"> Authors: Bijan Mallick, B.R. Sarkar, B. Doloi, B. Bhattacharyya </div> </div> <div id="abstractTextBlock399314" class="volume-info volume-info-text volume-info-description"> Abstract: Electrochemical Discharge micro-machining process appears better utility with greater effectiveness in the modern micro-machining industrial field. Electrochemical discharge micro-machining process is involved to generate micro-channel as well as curve profile on glass for utilization as micro-fluidic device. This paper shows second order mathematical modeling of correlation between the machining criteria such as machining rate as a form of material removal rate (MRR), overcut (OC), machining depth (MD) with various process parameters like applied voltage (V), electrolyte concentration (wt %) and inter-electrode gap (IEG) (mm). The analysis of variance (ANOVA) has been performed to find out the adequacy of the developed models.This paper also shows the multi objective optimization to achieve the optimal parametric combination for maximum MRR, MD and minimum OC using response surface methodology (RSM). <i>Keywords:</i> <i>μ-ECDM,</i> <i>MRR,</i> <i>OC,</i> <i>MD,</i> <i>RSM,</i> <i>ANOVA,</i> <i>Glass.</i> </div> <div> <a data-readmore="{ block: '#abstractTextBlock399314', lines: 2, expandText: '...more', collapseText: '...less' }"></a> </div> <div class="page-number semibold-large-text"> 525 </div> </div> <div class="item-block"> <div class="item-link"> <a href="/AMM.592-594.282">Evaluation of Optimal Parameters for Machining Aluminium Alloy Al6061 in Wire EDM</a> </div> <div class="item-link volume-authors"> <div class="semibold-middle-text"> Authors: T. Bharathy, K. Thiruppathi, S. Raghuraman </div> </div> <div id="abstractTextBlock399116" class="volume-info volume-info-text volume-info-description"> Abstract: This paper discuss on the optimization of process parameters for the machining of Al6061 aluminium alloy in Wire Electrical Discharge Machining (WEDM). Al6061 has a significant use in various domains like aerospace, ordnance, and automotive sectors. Wire EDM is used in the fields of Dies, Moulds Precision Manufacturing and contour cutting. The experiments have been conducted by varying four process parameters such as Peak current, T<sub>on</sub>, T<sub>off</sub> and Servo feed in three different levels. The important output measurable parameters like material removal rate (MRR), Surface roughness (Ra) value of the machined surface for each experimental runs has been measured. Taguchi’s L9(3<sup>4</sup>) Orthogonal Array was employed to carry on the experiments, that agree with arbitrarily opted distinct combinations of the mentioned process parameter. All experiments have been conducted using Electronica Sprintcut WEDM. Grey relational analysis was employed to change over the multi-objective measure into a tantamount individual objective function. Taguchi technique was used to optimize the overall grey relational grade. Verification experiments were done to validate the optimal results. </div> <div> <a data-readmore="{ block: '#abstractTextBlock399116', lines: 2, expandText: '...more', collapseText: '...less' }"></a> </div> <div class="page-number semibold-large-text"> 282 </div> </div> <div class="item-block"> <div class="item-link"> <a href="/AMM.592-594.128">Desirability Fuzzy Approach for Optimizing Multiple Performance Characteristics in Machining Metal Matrix Composites</a> </div> <div class="item-link volume-authors"> <div class="semibold-middle-text"> Authors: Santosh K. Tamang, Muthumari Chandrasekaran </div> </div> <div id="abstractTextBlock399049" class="volume-info volume-info-text volume-info-description"> Abstract: In this work, a new approach for optimizing multiple performance characteristics in turning Al-SiCp metal matrix composite (MMC) is attempted. Desirability fuzzy approach is used to optimize process parameters <i>viz</i>., spindle speed (<i>N</i>), feed (<i>f</i>) and dept of cut (<i>d</i>) that minimizes surface roughness (<i>R</i><sub>a</sub>) and maximizes metal removal rate (<i>MRR</i>). The approach obtains desirability fuzzy grade value for the multiple responses using individual desirability value. The optimum parameters were obtained based on desirability fuzzy grade value and the response table/response graph for each level of the machining parameters was obtained. It is observed that the combination of turning parameters as <i>N</i>=1200 rpm, <i>f</i>=0.22 mm/rev and <i>d</i>=1.0 mm (i.e., <i>N</i><sub>3</sub>–<i>f</i><sub>2</sub>–<i>d</i><sub>3</sub>) were obtained as optimal parameters producing minimum <i>R</i><sub>a</sub> and maximum <i>MRR</i> as 2.64 μm and 33.19 cm<sup>3</sup>/min respectively. Confirmation test of the predicted result shows that the error is within the range of 1.0 %. This clearly shows the proposed approach is found simple and effective tool for optimizing the complicated multiple performance characteristics. </div> <div> <a data-readmore="{ block: '#abstractTextBlock399049', lines: 2, expandText: '...more', collapseText: '...less' }"></a> </div> <div class="page-number semibold-large-text"> 128 </div> </div> <div class="item-block"> <div class="item-link"> <a href="/AMM.556-562.395">Research of EDM Titanium Alloy TC11 Based on GM(1,N) Model and BP Neural Network</a> </div> <div class="item-link volume-authors"> <div class="semibold-middle-text"> Authors: Ji Gao, Yao Sun, Di Wang </div> </div> <div id="abstractTextBlock391016" class="volume-info volume-info-text volume-info-description"> Abstract: In order to predict the influences of electrical discharge machining (EDM) and enhance material removal rate (MRR). A model was presented for predictions of MRR in EDM TC11 test piece based on the construction method of gray GM(1,N) model and BP neural network model (GNNM).The results show that the GNNM is credible with the maximum absolute error 3.58%, the minimum absolute error 0.01% and the mean error 0.53%were obtained .The results indicated that the model can reflect the technological law of EDM TC11 and successfully predict its processing speed .The paper provides references and basis for selecting processing parameters of EDM TC11 and has practical significance. </div> <div> <a data-readmore="{ block: '#abstractTextBlock391016', lines: 2, expandText: '...more', collapseText: '...less' }"></a> </div> <div class="page-number semibold-large-text"> 395 </div> </div> <div class="item-block"> <div class="item-link"> <a href="/AMM.550.53">Experimental Investigation of Process Parameters in Wire Electrical Discharge Machining by Response Surface Methodology on IS2062 Steel</a> </div> <div class="item-link volume-authors"> <div class="semibold-middle-text"> Authors: R.Arun Bharathi, P.Ashoka Varthanan, K. Manoj Mathew </div> </div> <div id="abstractTextBlock384289" class="volume-info volume-info-text volume-info-description"> Abstract: The objective of the present work is to predict the optimal set of process parameters such as peak current (IP), pulse on/off time (T<sub>ON</sub>/T<sub>OFF</sub>) 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). </div> <div> <a data-readmore="{ block: '#abstractTextBlock384289', lines: 2, expandText: '...more', collapseText: '...less' }"></a> </div> <div class="page-number semibold-large-text"> 53 </div> </div> <div class="item-block"> <div class="item-link"> <a href="/AMM.541-542.354">Multi-Response Optimization of CNC WEDM Process Parameters for Machining Titanium Alloy Ti 6AI-4V Using Response Surface Methodology (RSM)</a> </div> <div class="item-link volume-authors"> <div class="semibold-middle-text"> Authors: C. Nandakumar, B. Mohan </div> </div> <div id="abstractTextBlock374349" class="volume-info volume-info-text volume-info-description"> Abstract: 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 (T<sub>ON</sub>), pulse-off time (T<sub>OFF</sub>) 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. </div> <div> <a data-readmore="{ block: '#abstractTextBlock374349', lines: 2, expandText: '...more', collapseText: '...less' }"></a> </div> <div class="page-number semibold-large-text"> 354 </div> </div> <div class="item-block"> <div class="item-link"> <a href="/AMR.903.51">Influence of Workpiece Shape on MRR and EWR in EDM of Steel</a> </div> <div class="item-link volume-authors"> <div class="semibold-middle-text"> Authors: Alexis Mouangue Nanimina, Ahmad Majdi Abdul Rani, Mohd Amri Lajis, Turnad Lenggo Ginta, T.V.V.L.N. Rao </div> </div> <div id="abstractTextBlock348624" class="volume-info volume-info-text volume-info-description"> Abstract: Shape of workpiece, electrode orientation and flushing system play important role in electrical discharge machining (EDM) process. Low material removal rate and relatively high electrode wear ratio are some of the disadvantages of EDM process. This can be due to the flushing modes. Workpiece shape has a significant effect in effectiveness of dielectric flushing flow and orientation during EDM process. This research work is conducted to analyze the influence of various workpiece shapes. Square cavity, L shape, flat shape and U shape were machined with same cross-section electrode material. Test parameters are material removal rate (MRR) and electrode wear ratio (EWR). Experiment results show slight difference in MRR and EWR values for different shapes. U shape presents the highest MRR and the lowest EWR occurs in flat shape compared to cavity and L shapes. It can be concluded that flat and U shapes result in good EDM machining quality due to good dielectric flow and flushing conditions in the area of EDM machining. </div> <div> <a data-readmore="{ block: '#abstractTextBlock348624', lines: 2, expandText: '...more', collapseText: '...less' }"></a> </div> <div class="page-number semibold-large-text"> 51 </div> </div> <div class="item-block"> <div class="item-link"> <a href="/AMR.816-817.23">Parametric Optimization of PMEDM Process with Chromium Powder Suspended Dielectric for Triangular Electrodes</a> </div> <div class="item-link volume-authors"> <div class="semibold-middle-text"> Authors: Rajiv Kumar Garg, Kuldeep Ojha </div> </div> <div id="abstractTextBlock332365" 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: '#abstractTextBlock332365', lines: 2, expandText: '...more', collapseText: '...less' }"></a> </div> <div class="page-number semibold-large-text"> 23 </div> </div> <div class="item-block"> <div class="item-link"> <a href="/AMM.372.495">Dry Machining of Brass Using Titanium Carbonitride (TiCN) Coated Tool</a> </div> <div class="item-link volume-authors"> <div class="semibold-middle-text"> Authors: Tasnim Firdaus Ariff, Mohd Syahidan Kamarudin, Mohd Amiruddin Haron </div> </div> <div id="abstractTextBlock316408" class="volume-info volume-info-text volume-info-description"> Abstract: Dry machining is environmentally friendly, clean and safe to be performed. Regardless of decreasing tool life due to lack of lubricants, choosing dry machining over wet machining may be a wiser choice since the cost of purchasing and disposing the cutting fluids can contribute to a higher cost. Wear rates, tool wear intensities and material removal rates (MRR) of TiCN coated tools using both dry and traditional wet machining on brass were studied with the aim in finding the optimum cutting condition from four different cutting speeds (207, 279, 372 and 498 m/min) with two sets of cutting parameters; depth of cut and feed rate (<i>d </i>= 0.1 mm, <i>f</i> = 0.2 mm/rev and <i>d </i>= 0.2 mm, <i>f </i>= 0.4 mm/rev). Temperatures at the tool-chip interface were measured to analyze the effects of temperature rise during dry machining. Cost analysis on machining cost per piece between dry and wet machining was performed. The optimum cutting condition for wet and dry machining of brass using TiCN coated cutting tool was found to be 498 m/min at <i>d </i>= 0.2 mm, <i>f </i>= 0.4 mm/rev. The tool tip temperature obtained from dry machining did not influence tool wear since the temperature rise is quite similar to the wet machining temperatures. The machining for the dry machining reduced to about 25-76% per piece when compared with wet machining. </div> <div> <a data-readmore="{ block: '#abstractTextBlock316408', lines: 2, expandText: '...more', collapseText: '...less' }"></a> </div> <div class="page-number semibold-large-text"> 495 </div> </div> <div class="item-block"> <div class="item-link"> <a href="/AMR.748.273">Optimization of Process Parameters of Rotary Ultrasonic Machining Based on Taguchis Method</a> </div> <div class="item-link volume-authors"> <div class="semibold-middle-text"> Authors: Basem M.A. Abdo, S.M. Darwish, A.M. Al-Ahmari, A.M. El-Tamimi </div> </div> <div id="abstractTextBlock305081" class="volume-info volume-info-text volume-info-description"> Abstract: In this Research, Taguchi optimization methodology is used to optimize Rotary Ultrasonic Machining (RUM) parameters for face milling of zirconia ceramic. The influence of the RUM parameters such as vibration frequency, vibration amplitude, spindle speed, feed rate, and depth of cut on cutting force and material removal rate (MRR) is studied. A three-level orthogonal array table is used to determine the signal-to-noise (S/N) ratios based on Taguchis design of experiments. Furthermore, analysis of variance (ANOVA) has been performed to study the relative significance of the different factors on cutting force and MRR of zirconia ceramic. Finally, verification tests were carried out to compare the predicted values of the outputs with their experimental values in order to confirm the effectiveness of the Taguchi Optimization. </div> <div> <a data-readmore="{ block: '#abstractTextBlock305081', lines: 2, expandText: '...more', collapseText: '...less' }"></a> </div> <div class="page-number semibold-large-text"> 273 </div> </div> <div class="block-bottom-pagination"> <div class="pager-info"> Showing 41 to 50 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/4" rel="prev"><</a></li><li class="PagedList-ellipses"><a class="PagedList-skipToPrevious" href="/paper-keyword/mrr/2" rel="prev">…</a></li><li><a href="/paper-keyword/mrr/3">3</a></li><li><a href="/paper-keyword/mrr/4">4</a></li><li class="active"><span>5</span></li><li><a href="/paper-keyword/mrr/6">6</a></li><li><a href="/paper-keyword/mrr/7">7</a></li><li class="PagedList-ellipses"><a class="PagedList-skipToNext" href="/paper-keyword/mrr/8" rel="next">…</a></li><li class="PagedList-skipToNext"><a href="/paper-keyword/mrr/6" rel="next">></a></li><li class="PagedList-skipToLast"><a href="/paper-keyword/mrr/8">>></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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