Machinability study and ANN-MOALO-based multi-response optimization during Eco-Friendly machining of EN-GJL-250 cast iron
The current work examines the performance of Minimum Quantity Lubrication when turning of EN-GJL-250 cast iron compared to dry and wet cooling methods. The Taguchi design L 36 has been chosen for the planification of experimentation. Then, ANOVA has been established after data acquisition in order t...
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| Veröffentlicht in: | International journal of advanced manufacturing technology 2021-11, Vol.117 (3-4), p.1179-1192 |
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| container_title | International journal of advanced manufacturing technology |
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| creator | Laouissi, Aissa Nouioua, Mourad Yallese, Mohamed Athmane Abderazek, Hammoudi Maouche, Hichem Bouhalais, Mohamed Lamine |
| description | The current work examines the performance of Minimum Quantity Lubrication when turning of EN-GJL-250 cast iron compared to dry and wet cooling methods. The Taguchi design L
36
has been chosen for the planification of experimentation. Then, ANOVA has been established after data acquisition in order to define the effect of cutting conditions such as the used inserts, cutting depth, feed rate and cutting speed on the studied factors. Furthermore, the surface roughness has been deeply studied using 3D roughness topography to evaluate the MQL effect. Finally, the approach ANN-MOALO was found to be helpful for future industrial applications for predicting part quality and power consumption with accurate results and optimizing cutting parameters that helps to achieve the best production control. |
| doi_str_mv | 10.1007/s00170-021-07759-z |
| format | Article |
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36
has been chosen for the planification of experimentation. Then, ANOVA has been established after data acquisition in order to define the effect of cutting conditions such as the used inserts, cutting depth, feed rate and cutting speed on the studied factors. Furthermore, the surface roughness has been deeply studied using 3D roughness topography to evaluate the MQL effect. Finally, the approach ANN-MOALO was found to be helpful for future industrial applications for predicting part quality and power consumption with accurate results and optimizing cutting parameters that helps to achieve the best production control.</description><identifier>ISSN: 0268-3768</identifier><identifier>EISSN: 1433-3015</identifier><identifier>DOI: 10.1007/s00170-021-07759-z</identifier><language>eng</language><publisher>London: Springer London</publisher><subject>Advanced manufacturing technologies ; CAE) and Design ; Cast iron ; Computer-Aided Engineering (CAD ; Cooling ; Cost control ; Cutting parameters ; Cutting speed ; Cutting tools ; Design of experiments ; Efficiency ; Engineering ; Experimentation ; Feed rate ; Graphite ; Industrial and Production Engineering ; Industrial applications ; Inserts ; Lubricants & lubrication ; Machinability ; Manufacturing ; Mechanical Engineering ; Media Management ; Optimization ; Original Article ; Power consumption ; Production controls ; Productivity ; Surface roughness ; Taguchi methods ; Turning (machining)</subject><ispartof>International journal of advanced manufacturing technology, 2021-11, Vol.117 (3-4), p.1179-1192</ispartof><rights>The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2021</rights><rights>The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2021.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c319t-a1274b211c38920de737b890ac66e747348c91e0a84cc917f78366d4a053519a3</citedby><cites>FETCH-LOGICAL-c319t-a1274b211c38920de737b890ac66e747348c91e0a84cc917f78366d4a053519a3</cites><orcidid>0000-0002-5723-3863</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s00170-021-07759-z$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s00170-021-07759-z$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>314,780,784,27924,27925,41488,42557,51319</link.rule.ids></links><search><creatorcontrib>Laouissi, Aissa</creatorcontrib><creatorcontrib>Nouioua, Mourad</creatorcontrib><creatorcontrib>Yallese, Mohamed Athmane</creatorcontrib><creatorcontrib>Abderazek, Hammoudi</creatorcontrib><creatorcontrib>Maouche, Hichem</creatorcontrib><creatorcontrib>Bouhalais, Mohamed Lamine</creatorcontrib><title>Machinability study and ANN-MOALO-based multi-response optimization during Eco-Friendly machining of EN-GJL-250 cast iron</title><title>International journal of advanced manufacturing technology</title><addtitle>Int J Adv Manuf Technol</addtitle><description>The current work examines the performance of Minimum Quantity Lubrication when turning of EN-GJL-250 cast iron compared to dry and wet cooling methods. The Taguchi design L
36
has been chosen for the planification of experimentation. Then, ANOVA has been established after data acquisition in order to define the effect of cutting conditions such as the used inserts, cutting depth, feed rate and cutting speed on the studied factors. Furthermore, the surface roughness has been deeply studied using 3D roughness topography to evaluate the MQL effect. Finally, the approach ANN-MOALO was found to be helpful for future industrial applications for predicting part quality and power consumption with accurate results and optimizing cutting parameters that helps to achieve the best production control.</description><subject>Advanced manufacturing technologies</subject><subject>CAE) and Design</subject><subject>Cast iron</subject><subject>Computer-Aided Engineering (CAD</subject><subject>Cooling</subject><subject>Cost control</subject><subject>Cutting parameters</subject><subject>Cutting speed</subject><subject>Cutting tools</subject><subject>Design of experiments</subject><subject>Efficiency</subject><subject>Engineering</subject><subject>Experimentation</subject><subject>Feed rate</subject><subject>Graphite</subject><subject>Industrial and Production Engineering</subject><subject>Industrial applications</subject><subject>Inserts</subject><subject>Lubricants & lubrication</subject><subject>Machinability</subject><subject>Manufacturing</subject><subject>Mechanical Engineering</subject><subject>Media Management</subject><subject>Optimization</subject><subject>Original Article</subject><subject>Power consumption</subject><subject>Production controls</subject><subject>Productivity</subject><subject>Surface roughness</subject><subject>Taguchi methods</subject><subject>Turning (machining)</subject><issn>0268-3768</issn><issn>1433-3015</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>AFKRA</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><recordid>eNp9kMtOwzAQRS0EEqXwA6wssTaM48R2llXV8lAfG1hbjuOAqzQOdrJIv560RWLHakajc-9IB6F7Co8UQDxFACqAQEIJCJHl5HCBJjRljDCg2SWaQMIlYYLLa3QT427EOeVygoa1Nl-u0YWrXTfg2PXlgHVT4tlmQ9bb2WpLCh1tifd93TkSbGx9Ey32bef27qA75xtc9sE1n3hhPFkGZ5uyHvD-1Hs8-wovNuT5bUWSDLDRscMu-OYWXVW6jvbud07Rx3LxPn8hq-3z63y2IobRvCOaJiItEkoNk3kCpRVMFDIHbTi3IhUslSanFrRMzbiISkjGeZlqyFhGc82m6OHc2wb_3dvYqZ3vQzO-VEkmKQXOMj5SyZkywccYbKXa4PY6DIqCOipWZ8VqVKxOitVhDLFzKLZHATb8Vf-T-gFzRH3d</recordid><startdate>20211101</startdate><enddate>20211101</enddate><creator>Laouissi, Aissa</creator><creator>Nouioua, Mourad</creator><creator>Yallese, Mohamed Athmane</creator><creator>Abderazek, Hammoudi</creator><creator>Maouche, Hichem</creator><creator>Bouhalais, Mohamed Lamine</creator><general>Springer London</general><general>Springer Nature B.V</general><scope>AAYXX</scope><scope>CITATION</scope><scope>8FE</scope><scope>8FG</scope><scope>ABJCF</scope><scope>AFKRA</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>HCIFZ</scope><scope>L6V</scope><scope>M7S</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>PTHSS</scope><orcidid>https://orcid.org/0000-0002-5723-3863</orcidid></search><sort><creationdate>20211101</creationdate><title>Machinability study and ANN-MOALO-based multi-response optimization during Eco-Friendly machining of EN-GJL-250 cast iron</title><author>Laouissi, Aissa ; Nouioua, Mourad ; Yallese, Mohamed Athmane ; Abderazek, Hammoudi ; Maouche, Hichem ; Bouhalais, Mohamed Lamine</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c319t-a1274b211c38920de737b890ac66e747348c91e0a84cc917f78366d4a053519a3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Advanced manufacturing technologies</topic><topic>CAE) and Design</topic><topic>Cast iron</topic><topic>Computer-Aided Engineering (CAD</topic><topic>Cooling</topic><topic>Cost control</topic><topic>Cutting parameters</topic><topic>Cutting speed</topic><topic>Cutting tools</topic><topic>Design of experiments</topic><topic>Efficiency</topic><topic>Engineering</topic><topic>Experimentation</topic><topic>Feed rate</topic><topic>Graphite</topic><topic>Industrial and Production Engineering</topic><topic>Industrial applications</topic><topic>Inserts</topic><topic>Lubricants & lubrication</topic><topic>Machinability</topic><topic>Manufacturing</topic><topic>Mechanical Engineering</topic><topic>Media Management</topic><topic>Optimization</topic><topic>Original Article</topic><topic>Power consumption</topic><topic>Production controls</topic><topic>Productivity</topic><topic>Surface roughness</topic><topic>Taguchi methods</topic><topic>Turning (machining)</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Laouissi, Aissa</creatorcontrib><creatorcontrib>Nouioua, Mourad</creatorcontrib><creatorcontrib>Yallese, Mohamed Athmane</creatorcontrib><creatorcontrib>Abderazek, Hammoudi</creatorcontrib><creatorcontrib>Maouche, Hichem</creatorcontrib><creatorcontrib>Bouhalais, Mohamed Lamine</creatorcontrib><collection>CrossRef</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>Materials Science & Engineering Collection</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Engineering Collection</collection><collection>Engineering Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>Engineering Collection</collection><jtitle>International journal of advanced manufacturing technology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Laouissi, Aissa</au><au>Nouioua, Mourad</au><au>Yallese, Mohamed Athmane</au><au>Abderazek, Hammoudi</au><au>Maouche, Hichem</au><au>Bouhalais, Mohamed Lamine</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Machinability study and ANN-MOALO-based multi-response optimization during Eco-Friendly machining of EN-GJL-250 cast iron</atitle><jtitle>International journal of advanced manufacturing technology</jtitle><stitle>Int J Adv Manuf Technol</stitle><date>2021-11-01</date><risdate>2021</risdate><volume>117</volume><issue>3-4</issue><spage>1179</spage><epage>1192</epage><pages>1179-1192</pages><issn>0268-3768</issn><eissn>1433-3015</eissn><abstract>The current work examines the performance of Minimum Quantity Lubrication when turning of EN-GJL-250 cast iron compared to dry and wet cooling methods. The Taguchi design L
36
has been chosen for the planification of experimentation. Then, ANOVA has been established after data acquisition in order to define the effect of cutting conditions such as the used inserts, cutting depth, feed rate and cutting speed on the studied factors. Furthermore, the surface roughness has been deeply studied using 3D roughness topography to evaluate the MQL effect. Finally, the approach ANN-MOALO was found to be helpful for future industrial applications for predicting part quality and power consumption with accurate results and optimizing cutting parameters that helps to achieve the best production control.</abstract><cop>London</cop><pub>Springer London</pub><doi>10.1007/s00170-021-07759-z</doi><tpages>14</tpages><orcidid>https://orcid.org/0000-0002-5723-3863</orcidid></addata></record> |
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| subjects | Advanced manufacturing technologies CAE) and Design Cast iron Computer-Aided Engineering (CAD Cooling Cost control Cutting parameters Cutting speed Cutting tools Design of experiments Efficiency Engineering Experimentation Feed rate Graphite Industrial and Production Engineering Industrial applications Inserts Lubricants & lubrication Machinability Manufacturing Mechanical Engineering Media Management Optimization Original Article Power consumption Production controls Productivity Surface roughness Taguchi methods Turning (machining) |
| title | Machinability study and ANN-MOALO-based multi-response optimization during Eco-Friendly machining of EN-GJL-250 cast iron |
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