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            <front>

                <journal-meta>
                                                                <journal-id>ij3dptdi</journal-id>
            <journal-title-group>
                                                                                    <journal-title>International Journal of 3D Printing Technologies and Digital Industry</journal-title>
            </journal-title-group>
                            <issn pub-type="ppub">2602-3350</issn>
                                        <issn pub-type="epub">2602-3350</issn>
                                                                                            <publisher>
                    <publisher-name>Kerim ÇETİNKAYA</publisher-name>
                </publisher>
                    </journal-meta>
                <article-meta>
                                        <article-id pub-id-type="doi">10.46519/ij3dptdi.1041325</article-id>
                                                                <article-categories>
                                            <subj-group  xml:lang="en">
                                                            <subject>Mechanical Engineering</subject>
                                                    </subj-group>
                                            <subj-group  xml:lang="tr">
                                                            <subject>Makine Mühendisliği</subject>
                                                    </subj-group>
                                    </article-categories>
                                                                                                                                                        <title-group>
                                                                                                                        <article-title>REDUCING SOUND INTENSITY BY OPTIMIZING CUTTING PARAMETERS ON CNC MILLING MACHINES</article-title>
                                                                                                                                        </title-group>
            
                                                    <contrib-group content-type="authors">
                                                                        <contrib contrib-type="author">
                                                                    <contrib-id contrib-id-type="orcid">
                                        https://orcid.org/0000-0002-3201-1789</contrib-id>
                                                                <name>
                                    <surname>Albayrak</surname>
                                    <given-names>Sirer</given-names>
                                </name>
                                                                    <aff>AĞRI İBRAHİM ÇEÇEN ÜNİVERSİTESİ</aff>
                                                            </contrib>
                                                    <contrib contrib-type="author">
                                                                    <contrib-id contrib-id-type="orcid">
                                        https://orcid.org/0000-0002-1225-8290</contrib-id>
                                                                <name>
                                    <surname>Mercan</surname>
                                    <given-names>Serdar</given-names>
                                </name>
                                                                    <aff>SIVAS CUMHURIYET UNIVERSITY</aff>
                                                            </contrib>
                                                    <contrib contrib-type="author">
                                                                    <contrib-id contrib-id-type="orcid">
                                        https://orcid.org/0000-0002-1899-2373</contrib-id>
                                                                <name>
                                    <surname>Karaçam</surname>
                                    <given-names>Hikmet</given-names>
                                </name>
                                                                    <aff>KARADENIZ TECHNICAL UNIVERSITY</aff>
                                                            </contrib>
                                                                                </contrib-group>
                        
                                        <pub-date pub-type="pub" iso-8601-date="20220430">
                    <day>04</day>
                    <month>30</month>
                    <year>2022</year>
                </pub-date>
                                        <volume>6</volume>
                                        <issue>1</issue>
                                        <fpage>62</fpage>
                                        <lpage>73</lpage>
                        
                        <history>
                                    <date date-type="received" iso-8601-date="20211224">
                        <day>12</day>
                        <month>24</month>
                        <year>2021</year>
                    </date>
                                                    <date date-type="accepted" iso-8601-date="20220330">
                        <day>03</day>
                        <month>30</month>
                        <year>2022</year>
                    </date>
                            </history>
                                        <permissions>
                    <copyright-statement>Copyright © 2017, International Journal of 3D Printing Technologies and Digital Industry</copyright-statement>
                    <copyright-year>2017</copyright-year>
                    <copyright-holder>International Journal of 3D Printing Technologies and Digital Industry</copyright-holder>
                </permissions>
            
                                                                                                <abstract><p>In the cutting process with machine tools in the Machinery Manufacturing Industry; while the desired surface integrity is ensured by the optimization of the cutting parameters, the noise level must be kept at a minimum to protect the health of the workers. The noise level can be reduced by using this optimization without compromising the surface roughness through processing of EN AW 6013 material on a CNC milling machine. Experimental design was examined in three variables, three levels and two target functions. The effects of these parameters on the target function were studied by performing experimental plans determined by &quot;Central Composite Design (CCT)&quot; of Response Surface Method (RSM)&quot;. To assess the sound intensity and surface roughness, mathematical models were developed by performing regression analysis on the experimental results. These developed models have been tested with control experiments and it has been seen that the models have acceptable error rates. The obtained regression equation is highly modeled with a validity of 93.29% for sound intensity and 97.33% for surface roughness. Therefore, cutting parameters were found to be related to sound intensity and surface roughness values.</p></abstract>
                                                                                    
            
                                                            <kwd-group>
                                                    <kwd>Noise</kwd>
                                                    <kwd>  occupational health</kwd>
                                                    <kwd>  machine tools</kwd>
                                                    <kwd>  roughness</kwd>
                                                    <kwd>  EN AW 6013</kwd>
                                            </kwd-group>
                                                        
                                                                                                                                                    </article-meta>
    </front>
    <back>
                            <ref-list>
                                    <ref id="ref1">
                        <label>1</label>
                        <mixed-citation publication-type="journal">1.	Suraratchai, M., Limido, J., Mabru, C., Chieragatti, R., &quot;Modelling the influence of machined surface roughness on the fatigue life of aluminium alloy&quot;, International Journal of Fatigue., Vol.  30, Pages 2119–2126, 2008.</mixed-citation>
                    </ref>
                                    <ref id="ref2">
                        <label>2</label>
                        <mixed-citation publication-type="journal">2.	Hilbert, L. R., Bagge-Ravn, D., Kold, J., Gram, L., &#039;&#039;Influence of surface roughness of stainless steel on microbial adhesion and corrosion resistance&#039;&#039;, International Biodeterioration &amp; Biodegradation.,Vol. 52, Pages 175–185, 2003.</mixed-citation>
                    </ref>
                                    <ref id="ref3">
                        <label>3</label>
                        <mixed-citation publication-type="journal">3.	Hesselbach, J., Hoffmeister, H. W., Schuller, B. C., Loeis, K., &#039;&#039;Development of an active clamping system for noise and vibration reduction&#039;&#039;, CIRP Annals - Manufacturing Technology., Vol.59, Pages 395–398, 2010.</mixed-citation>
                    </ref>
                                    <ref id="ref4">
                        <label>4</label>
                        <mixed-citation publication-type="journal">4.	Sahoo, A. K., Sahoo, B., &#039;&#039;Performance studies of multilayer hard surface coatings (TiN/TiCN/Al2O3/TiN) of indexable carbide inserts in hard machining: Part-II (RSM, grey relational and techno economical approach)&#039;&#039;, Measurement., Vol. 46, Pages 2868–2884, 2013.</mixed-citation>
                    </ref>
                                    <ref id="ref5">
                        <label>5</label>
                        <mixed-citation publication-type="journal">5.	Lela, B., Bajić, D., Jozić, S., &#039;&#039;Regression analysis, support vector machines, and Bayesian neural network approaches to modeling surface roughness in face milling&#039;&#039;, International Journal of Advanced Manufacturing Technology., Vol.42, Pages 1082–1088, 2009.</mixed-citation>
                    </ref>
                                    <ref id="ref6">
                        <label>6</label>
                        <mixed-citation publication-type="journal">6.	Chavoshi, S. Z., Tajdari, M., &#039;&#039;Surface roughness modelling in hard turning operation of AISI 4140 using CBN cutting tool&#039;&#039;, International Journal of Material Forming., Vol.3, Pages 233–239, 2010.</mixed-citation>
                    </ref>
                                    <ref id="ref7">
                        <label>7</label>
                        <mixed-citation publication-type="journal">7.	Singh, D., Rao, P. V., &#039;&#039;A surface roughness prediction model for hard turning process&#039;&#039;, International Journal of Advanced Manufacturing Technology., Vol.32, Pages 1115–1124, 2007.</mixed-citation>
                    </ref>
                                    <ref id="ref8">
                        <label>8</label>
                        <mixed-citation publication-type="journal">8.	Yan, J., Li, L., &#039;&#039;Multi-objective optimization of milling parameters – the trade-offs between energy, production rate and cutting quality&#039;&#039;, Journal of Cleaner Production., Vol.52, Pages 462–471, 2013.</mixed-citation>
                    </ref>
                                    <ref id="ref9">
                        <label>9</label>
                        <mixed-citation publication-type="journal">9.	Şahinoğlu, A., Rafighi, M., &#039;&#039;Investigation of Vibration, Sound level, Machine Current and Surface Roughness Values of AISI 4140 During Machining on the Lathe&#039;&#039;, Arabian Journal for Science and Engineering., Vol.45, Pages 765–778, 2020.</mixed-citation>
                    </ref>
                                    <ref id="ref10">
                        <label>10</label>
                        <mixed-citation publication-type="journal">10.	Asiltürk, I., Akkuş, H., &#039;&#039;Determining the effect of cutting parameters on surface roughness in hard turning using the Taguchi method&#039;&#039;, Measurement., Vol. 44, Pages 1697–1704, 2011.</mixed-citation>
                    </ref>
                                    <ref id="ref11">
                        <label>11</label>
                        <mixed-citation publication-type="journal">11.	Özel, T., Karpat, Y., &#039;&#039;Predictive modeling of surface roughness and tool wear in hard turning using regression and neural networks&#039;&#039;, International Journal of Machine Tools and Manufacture.,Vol. 45,Pages 467–479, 2005.</mixed-citation>
                    </ref>
                                    <ref id="ref12">
                        <label>12</label>
                        <mixed-citation publication-type="journal">12.	Basak, S., Dixit, U. S., Davim, J. P., &#039;&#039;Application of radial basis function neural networks in optimization of hard turning of AISI D2 cold-worked tool steel with a ceramic tool, Proceedings of the Institution of Mechanical Engineers&#039;&#039;, Part B: Journal of Engineering Manufacture.,Vol. 221, Pages 987–998, 2007.</mixed-citation>
                    </ref>
                                    <ref id="ref13">
                        <label>13</label>
                        <mixed-citation publication-type="journal">13.	Singh, D., Venkateswara Rao, P., &#039;&#039;Optimization of tool geometry and cutting parameters for hard turning&#039;&#039;, Materials and Manufacturing Processes., Vol. 22, Pages 15–21, 2007.</mixed-citation>
                    </ref>
                                    <ref id="ref14">
                        <label>14</label>
                        <mixed-citation publication-type="journal">14.	Kalidass, S., Palanisamy, P., &#039;&#039;Prediction of Surface Roughness for AISI 304 Steel with Solid Carbide Tools in End Milling Process Using Regression and ANN Models&#039;&#039;, Arabian Journal for Science and Engineering., Vol.39, Pages 8065–8075, 2014.</mixed-citation>
                    </ref>
                                    <ref id="ref15">
                        <label>15</label>
                        <mixed-citation publication-type="journal">15.	Kuram, E., Ozcelik, B., &#039;&#039;Micro-milling performance of AISI 304 stainless steel using Taguchi method and fuzzy logic modelling&#039;&#039;, Journal of Intelligent Manufacturing., Vol.27, Pages 817–830, 2016.</mixed-citation>
                    </ref>
                                    <ref id="ref16">
                        <label>16</label>
                        <mixed-citation publication-type="journal">16.	Bagaber, S. A., Yusoff, A. R., &#039;&#039;Multi-objective optimization of cutting parameters to minimize power consumption in dry turning of stainless steel 316&#039;&#039;, Journal of Cleaner Production., Vol.157, Pages 30–46, 2017.</mixed-citation>
                    </ref>
                                    <ref id="ref17">
                        <label>17</label>
                        <mixed-citation publication-type="journal">17.	Bouzid, L., Yallese, M. A., Chaoui, K., Mabrouki, T., Boulanouar, L., &#039;&#039;Mathematical modeling for turning on AISI 420 stainless steel using surface response methodology, Proceedings of the Institution of Mechanical Engineers&#039;&#039;, Part B: Journal of Engineering Manufacture., Vol.229, Pages 45–61, 2014.</mixed-citation>
                    </ref>
                                    <ref id="ref18">
                        <label>18</label>
                        <mixed-citation publication-type="journal">18.	Zerti, O., Yallese, M. A., Zerti, A., Belhadi, S., Girardin, F., &#039;&#039;Simultaneous improvement of surface quality and productivity using grey relational analysis based taguchi design for turning couple (AISI D3 steel/ mixed ceramic tool (Al2O3 + TiC))&#039;&#039;, International Journal of Industrial Engineering Computations., Vol.9, Pages 173–194, 2018.</mixed-citation>
                    </ref>
                                    <ref id="ref19">
                        <label>19</label>
                        <mixed-citation publication-type="journal">19.	Bouzid, L., Boutabba, S., Yallese, M. A., Belhadi, S., Girardin, F., &#039;&#039;Simultaneous optimization of surface roughness and material removal rate for turning of X20Cr13 stainless steel&#039;&#039;, International Journal of Advanced Manufacturing Technology., Vol.74,Pages 879–891, 2014.</mixed-citation>
                    </ref>
                                    <ref id="ref20">
                        <label>20</label>
                        <mixed-citation publication-type="journal">20.	Karabulut, Ş., &#039;&#039;Optimization of surface roughness and cutting force during AA7039/Al2O3 metal matrix composites milling using neural networks and Taguchi method&#039;&#039;, Measurement: Journal of the International Measurement Confederation.,Vol. 66,Pages 139–149, 2015.</mixed-citation>
                    </ref>
                                    <ref id="ref21">
                        <label>21</label>
                        <mixed-citation publication-type="journal">21.	Campatelli, G., Lorenzini, L., Scippa, A., &#039;&#039;Optimization of process parameters using a Response Surface Method for minimizing power consumption in the milling of carbon steel&#039;&#039;, Journal of Cleaner Production., Vol.66, Pages 309–316, 2014.</mixed-citation>
                    </ref>
                                    <ref id="ref22">
                        <label>22</label>
                        <mixed-citation publication-type="journal">22.	Nur Sabreena, A. H., Nor Azma, Y., Mohamad, O., &#039;&#039;Article Response Surface Methodology for Optimisation of Parameters for Extraction of Stevia Rebaudiana Using Water, H 2 0&#039;&#039;, | Iioabj |., Vol.7, Pages 459–466, 2016.</mixed-citation>
                    </ref>
                                    <ref id="ref23">
                        <label>23</label>
                        <mixed-citation publication-type="journal">23.	Choudhury, I. A., El-Baradie, M. A., &#039;&#039;Surface roughness prediction in the turning of high-strength steel by factorial design of experiments&#039;&#039;, Journal of Materials Processing Technology., Vol.67, Pages 55–61, 1997.</mixed-citation>
                    </ref>
                                    <ref id="ref24">
                        <label>24</label>
                        <mixed-citation publication-type="journal">24.	Dabnun, M. A., Hashmi, M. S. J., El-Baradie, M. A., &#039;&#039;Surface roughness prediction model by design of experiments for turning machinable glass–ceramic (Macor)&#039;&#039;, Journal of Materials Processing Technology., Vol. 164–165, Pages 1289–1293, 2005.</mixed-citation>
                    </ref>
                                    <ref id="ref25">
                        <label>25</label>
                        <mixed-citation publication-type="journal">25.	Kopač, J., Bahor, M., Interaction of the technological history of a workpiece material and the machining parameters on the desired quality of the surface roughness of a product, Journal of Materials Processing Technology.,Vol. 92–93,Pages 381–387, 1999.</mixed-citation>
                    </ref>
                                    <ref id="ref26">
                        <label>26</label>
                        <mixed-citation publication-type="journal">26.	Puertas Arbizu, I., Luis Pérez, C. J., &#039;&#039;Surface roughness prediction by factorial design of experiments in turning processes&#039;&#039;, Journal of Materials Processing Technology.,Vol. 143–144, Pages 390–396, 2003.</mixed-citation>
                    </ref>
                            </ref-list>
                    </back>
    </article>
