An investigation of the machinability of PA 6/nano-CaCO3 composite
Nowadays, polymer nanocomposites have attracted manufacturers’ attention because of their good mechanical, thermal, and physical properties. Over the past decade, the requirement of the direct machining of polymer nanocomposites has increased due to the production of most polymer nanocomposites usin...
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| Veröffentlicht in: | International journal of advanced manufacturing technology 2013-10, Vol.68 (9-12), p.2489-2497 |
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| container_title | International journal of advanced manufacturing technology |
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| creator | Farshbaf Zinati, Reza Razfar, Mohammad Reza |
| description | Nowadays, polymer nanocomposites have attracted manufacturers’ attention because of their good mechanical, thermal, and physical properties. Over the past decade, the requirement of the direct machining of polymer nanocomposites has increased due to the production of most polymer nanocomposites using the extrusion method in simple cross-section and the increased demand for personalized products. In this paper, the effect of milling parameters (spindle speed and feed per tooth) and nano-CaCO
3
content on the machinability properties of PA 6/nano-CaCO
3
composites was studied by analyzing variance. Harmony search-based neural network (HSNN) was then utilized to create predictive models of surface roughness and total cutting forces from the experimental data. The results revealed that the nano-CaCO
3
content on PA 6 decreased the cutting forces significantly, but did not have a significant effect on surface roughness. Moreover, the results for modeling total cutting forces and surface roughness showed that HSNN is effective, reliable, and authoritative in modeling the surface roughness formation and total cutting force mechanism for end-milling of PA 6/nano-CaCO
3
composites. |
| doi_str_mv | 10.1007/s00170-013-4875-3 |
| format | Article |
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3
content on the machinability properties of PA 6/nano-CaCO
3
composites was studied by analyzing variance. Harmony search-based neural network (HSNN) was then utilized to create predictive models of surface roughness and total cutting forces from the experimental data. The results revealed that the nano-CaCO
3
content on PA 6 decreased the cutting forces significantly, but did not have a significant effect on surface roughness. Moreover, the results for modeling total cutting forces and surface roughness showed that HSNN is effective, reliable, and authoritative in modeling the surface roughness formation and total cutting force mechanism for end-milling of PA 6/nano-CaCO
3
composites.</description><identifier>ISSN: 0268-3768</identifier><identifier>EISSN: 1433-3015</identifier><identifier>DOI: 10.1007/s00170-013-4875-3</identifier><language>eng</language><publisher>London: Springer London</publisher><subject>CAE) and Design ; Calcium carbonate ; Computer-Aided Engineering (CAD ; Customization ; Cutting force ; End milling ; Engineering ; Extrusion ; Industrial and Production Engineering ; Machinability ; Mechanical Engineering ; Media Management ; Milling (machining) ; Modelling ; Nanocomposites ; Neural networks ; Original Article ; Physical properties ; Polymers ; Surface roughness ; Variance analysis</subject><ispartof>International journal of advanced manufacturing technology, 2013-10, Vol.68 (9-12), p.2489-2497</ispartof><rights>Springer-Verlag London 2013</rights><rights>The International Journal of Advanced Manufacturing Technology is a copyright of Springer, (2013). All Rights Reserved.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c316t-fb725880e3b270940639a6fadfb1199ffb333b37aeb19575ad09f7ba9ffa813e3</citedby><cites>FETCH-LOGICAL-c316t-fb725880e3b270940639a6fadfb1199ffb333b37aeb19575ad09f7ba9ffa813e3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s00170-013-4875-3$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s00170-013-4875-3$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>314,776,780,27901,27902,41464,42533,51294</link.rule.ids></links><search><creatorcontrib>Farshbaf Zinati, Reza</creatorcontrib><creatorcontrib>Razfar, Mohammad Reza</creatorcontrib><title>An investigation of the machinability of PA 6/nano-CaCO3 composite</title><title>International journal of advanced manufacturing technology</title><addtitle>Int J Adv Manuf Technol</addtitle><description>Nowadays, polymer nanocomposites have attracted manufacturers’ attention because of their good mechanical, thermal, and physical properties. Over the past decade, the requirement of the direct machining of polymer nanocomposites has increased due to the production of most polymer nanocomposites using the extrusion method in simple cross-section and the increased demand for personalized products. In this paper, the effect of milling parameters (spindle speed and feed per tooth) and nano-CaCO
3
content on the machinability properties of PA 6/nano-CaCO
3
composites was studied by analyzing variance. Harmony search-based neural network (HSNN) was then utilized to create predictive models of surface roughness and total cutting forces from the experimental data. The results revealed that the nano-CaCO
3
content on PA 6 decreased the cutting forces significantly, but did not have a significant effect on surface roughness. Moreover, the results for modeling total cutting forces and surface roughness showed that HSNN is effective, reliable, and authoritative in modeling the surface roughness formation and total cutting force mechanism for end-milling of PA 6/nano-CaCO
3
composites.</description><subject>CAE) and Design</subject><subject>Calcium carbonate</subject><subject>Computer-Aided Engineering (CAD</subject><subject>Customization</subject><subject>Cutting force</subject><subject>End milling</subject><subject>Engineering</subject><subject>Extrusion</subject><subject>Industrial and Production Engineering</subject><subject>Machinability</subject><subject>Mechanical Engineering</subject><subject>Media Management</subject><subject>Milling (machining)</subject><subject>Modelling</subject><subject>Nanocomposites</subject><subject>Neural networks</subject><subject>Original Article</subject><subject>Physical properties</subject><subject>Polymers</subject><subject>Surface roughness</subject><subject>Variance analysis</subject><issn>0268-3768</issn><issn>1433-3015</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2013</creationdate><recordtype>article</recordtype><sourceid>BENPR</sourceid><recordid>eNp1kE1LAzEQhoMoWKs_wNuC59gks5tkj3XxCwr1oOeQbJM2pU1qshX896as4MnTwMzzzgwPQreU3FNCxCwTQgXBhAKupWgwnKEJrQEwENqcowlhXGIQXF6iq5y3heaUywl6mIfKhy-bB7_Wg4-hiq4aNrba637jgzZ-54fvU_NtXvFZ0CHiTndLqPq4P8TsB3uNLpzeZXvzW6fo4-nxvXvBi-Xzazdf4B4oH7AzgjVSEguGCdLWhEOrudMrZyhtW-cMABgQ2hraNqLRK9I6YXSZaEnBwhTdjXsPKX4ey8dqG48plJOKMc6Ag2R1oehI9SnmnKxTh-T3On0rStRJlRpVqaJKnVQpKBk2ZnJhw9qmv83_h34AgLlqKA</recordid><startdate>20131001</startdate><enddate>20131001</enddate><creator>Farshbaf Zinati, Reza</creator><creator>Razfar, Mohammad Reza</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></search><sort><creationdate>20131001</creationdate><title>An investigation of the machinability of PA 6/nano-CaCO3 composite</title><author>Farshbaf Zinati, Reza ; Razfar, Mohammad Reza</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c316t-fb725880e3b270940639a6fadfb1199ffb333b37aeb19575ad09f7ba9ffa813e3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2013</creationdate><topic>CAE) and Design</topic><topic>Calcium carbonate</topic><topic>Computer-Aided Engineering (CAD</topic><topic>Customization</topic><topic>Cutting force</topic><topic>End milling</topic><topic>Engineering</topic><topic>Extrusion</topic><topic>Industrial and Production Engineering</topic><topic>Machinability</topic><topic>Mechanical Engineering</topic><topic>Media Management</topic><topic>Milling (machining)</topic><topic>Modelling</topic><topic>Nanocomposites</topic><topic>Neural networks</topic><topic>Original Article</topic><topic>Physical properties</topic><topic>Polymers</topic><topic>Surface roughness</topic><topic>Variance analysis</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Farshbaf Zinati, Reza</creatorcontrib><creatorcontrib>Razfar, Mohammad Reza</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>Farshbaf Zinati, Reza</au><au>Razfar, Mohammad Reza</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>An investigation of the machinability of PA 6/nano-CaCO3 composite</atitle><jtitle>International journal of advanced manufacturing technology</jtitle><stitle>Int J Adv Manuf Technol</stitle><date>2013-10-01</date><risdate>2013</risdate><volume>68</volume><issue>9-12</issue><spage>2489</spage><epage>2497</epage><pages>2489-2497</pages><issn>0268-3768</issn><eissn>1433-3015</eissn><abstract>Nowadays, polymer nanocomposites have attracted manufacturers’ attention because of their good mechanical, thermal, and physical properties. Over the past decade, the requirement of the direct machining of polymer nanocomposites has increased due to the production of most polymer nanocomposites using the extrusion method in simple cross-section and the increased demand for personalized products. In this paper, the effect of milling parameters (spindle speed and feed per tooth) and nano-CaCO
3
content on the machinability properties of PA 6/nano-CaCO
3
composites was studied by analyzing variance. Harmony search-based neural network (HSNN) was then utilized to create predictive models of surface roughness and total cutting forces from the experimental data. The results revealed that the nano-CaCO
3
content on PA 6 decreased the cutting forces significantly, but did not have a significant effect on surface roughness. Moreover, the results for modeling total cutting forces and surface roughness showed that HSNN is effective, reliable, and authoritative in modeling the surface roughness formation and total cutting force mechanism for end-milling of PA 6/nano-CaCO
3
composites.</abstract><cop>London</cop><pub>Springer London</pub><doi>10.1007/s00170-013-4875-3</doi><tpages>9</tpages></addata></record> |
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| ispartof | International journal of advanced manufacturing technology, 2013-10, Vol.68 (9-12), p.2489-2497 |
| issn | 0268-3768 1433-3015 |
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| subjects | CAE) and Design Calcium carbonate Computer-Aided Engineering (CAD Customization Cutting force End milling Engineering Extrusion Industrial and Production Engineering Machinability Mechanical Engineering Media Management Milling (machining) Modelling Nanocomposites Neural networks Original Article Physical properties Polymers Surface roughness Variance analysis |
| title | An investigation of the machinability of PA 6/nano-CaCO3 composite |
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