Loading…
Parametric design optimization of hard turning of AISI 4340 steel (69 HRC)
Continuous research endeavors on hard turning (HT), both on machine tools and cutting tools, have made the previously reported daunting limits easily attainable in the modern scenario. This presents an opportunity for a systematic investigation on finding the current attainable limits of hard turnin...
Saved in:
Published in: | International journal of advanced manufacturing technology 2016-01, Vol.82 (1-4), p.451-462 |
---|---|
Main Authors: | , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
cited_by | cdi_FETCH-LOGICAL-c429t-b955e6ac127d444b62976291bbc0dd1c9c585e8a8f4e5970de8aeee16600921c3 |
---|---|
cites | cdi_FETCH-LOGICAL-c429t-b955e6ac127d444b62976291bbc0dd1c9c585e8a8f4e5970de8aeee16600921c3 |
container_end_page | 462 |
container_issue | 1-4 |
container_start_page | 451 |
container_title | International journal of advanced manufacturing technology |
container_volume | 82 |
creator | Rashid, Waleed Bin Goel, Saurav Davim, J. Paulo Joshi, Shrikrishna N. |
description | Continuous research endeavors on hard turning (HT), both on machine tools and cutting tools, have made the previously reported daunting limits easily attainable in the modern scenario. This presents an opportunity for a systematic investigation on finding the current attainable limits of hard turning using a CNC turret lathe. Accordingly, this study aims to contribute to the existing literature by providing the latest experimental results of hard turning of AISI 4340 steel (69 HRC) using a CBN cutting tool. An orthogonal array was implemented using a set of judiciously chosen cutting parameters. Subsequently, the longitudinal turning trials were carried out in accordance with a well-designed full factorial-based Taguchi matrix. The speculation indeed proved correct as a mirror finished optical quality machined surface (an average surface roughness value of 45 nm) was achieved by the conventional cutting method using a CBN cutting tool. Furthermore, signal to noise (S/N) ratio analysis, analysis of variance (ANOVA), and multiple regression analysis were carried out on the experimental datasets to assert the dominance of each machining variable in dictating the machined surface roughness and to optimize the machining parameters. One of the key findings was that when feed rate during hard turning approaches very low (about 0.02 mm/rev), it could alone be most significant (99.16 %) parameter in influencing the machined surface roughness (Ra). This has, however, also been shown that low feed rate results in high tool wear; so, the selection of machining parameters for carrying out hard turning must be governed by a trade-off between the cost and quality considerations. |
doi_str_mv | 10.1007/s00170-015-7337-2 |
format | article |
fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_journals_2262266601</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2262266601</sourcerecordid><originalsourceid>FETCH-LOGICAL-c429t-b955e6ac127d444b62976291bbc0dd1c9c585e8a8f4e5970de8aeee16600921c3</originalsourceid><addsrcrecordid>eNp1kEtLAzEUhYMoWKs_wF3AjS6iN49JJstSrK0UFB_rkMlkako7U5PpQn-9KSO4Em6494bvnISD0CWFWwqg7hIAVUCAFkRxrgg7QiMqOCc8Xx2jETBZEq5keYrOUlpnWlJZjtDjs4126_sYHK59CqsWd7s-bMO37UOXlwZ_2Fjjfh_b0K4O-2TxusCCC8Cp936Dr6XG85fpzTk6aewm-YvfPkbvs_u36Zwsnx4W08mSOMF0TypdFF5aR5mqhRCVZFrlQ6vKQV1Tp11RFr60ZSN8oRXUefbeUykBNKOOj9HV4LuL3efep96su_y7_KRhTObKJM0UHSgXu5Sib8wuhq2NX4aCOURmhshMzsccIjMsa9igSZltVz7-Of8v-gEA7mtF</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2262266601</pqid></control><display><type>article</type><title>Parametric design optimization of hard turning of AISI 4340 steel (69 HRC)</title><source>Springer Nature</source><creator>Rashid, Waleed Bin ; Goel, Saurav ; Davim, J. Paulo ; Joshi, Shrikrishna N.</creator><creatorcontrib>Rashid, Waleed Bin ; Goel, Saurav ; Davim, J. Paulo ; Joshi, Shrikrishna N.</creatorcontrib><description>Continuous research endeavors on hard turning (HT), both on machine tools and cutting tools, have made the previously reported daunting limits easily attainable in the modern scenario. This presents an opportunity for a systematic investigation on finding the current attainable limits of hard turning using a CNC turret lathe. Accordingly, this study aims to contribute to the existing literature by providing the latest experimental results of hard turning of AISI 4340 steel (69 HRC) using a CBN cutting tool. An orthogonal array was implemented using a set of judiciously chosen cutting parameters. Subsequently, the longitudinal turning trials were carried out in accordance with a well-designed full factorial-based Taguchi matrix. The speculation indeed proved correct as a mirror finished optical quality machined surface (an average surface roughness value of 45 nm) was achieved by the conventional cutting method using a CBN cutting tool. Furthermore, signal to noise (S/N) ratio analysis, analysis of variance (ANOVA), and multiple regression analysis were carried out on the experimental datasets to assert the dominance of each machining variable in dictating the machined surface roughness and to optimize the machining parameters. One of the key findings was that when feed rate during hard turning approaches very low (about 0.02 mm/rev), it could alone be most significant (99.16 %) parameter in influencing the machined surface roughness (Ra). This has, however, also been shown that low feed rate results in high tool wear; so, the selection of machining parameters for carrying out hard turning must be governed by a trade-off between the cost and quality considerations.</description><identifier>ISSN: 0268-3768</identifier><identifier>EISSN: 1433-3015</identifier><identifier>DOI: 10.1007/s00170-015-7337-2</identifier><language>eng</language><publisher>London: Springer London</publisher><subject>CAE) and Design ; Computer-Aided Engineering (CAD ; Cutting parameters ; Cutting tools ; Design optimization ; Engineering ; Feed rate ; High strength low alloy steels ; Industrial and Production Engineering ; Machine tools ; Mechanical Engineering ; Media Management ; Multiple regression analysis ; Nickel chromium molybdenum steels ; Numerical controls ; Original Article ; Orthogonal arrays ; Parametric statistics ; Product design ; Surface roughness ; Tool wear ; Turning (machining) ; Turret lathes ; Variance analysis</subject><ispartof>International journal of advanced manufacturing technology, 2016-01, Vol.82 (1-4), p.451-462</ispartof><rights>Springer-Verlag London 2015</rights><rights>The International Journal of Advanced Manufacturing Technology is a copyright of Springer, (2015). All Rights Reserved.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c429t-b955e6ac127d444b62976291bbc0dd1c9c585e8a8f4e5970de8aeee16600921c3</citedby><cites>FETCH-LOGICAL-c429t-b955e6ac127d444b62976291bbc0dd1c9c585e8a8f4e5970de8aeee16600921c3</cites><orcidid>0000-0002-8694-332X</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,27924,27925</link.rule.ids></links><search><creatorcontrib>Rashid, Waleed Bin</creatorcontrib><creatorcontrib>Goel, Saurav</creatorcontrib><creatorcontrib>Davim, J. Paulo</creatorcontrib><creatorcontrib>Joshi, Shrikrishna N.</creatorcontrib><title>Parametric design optimization of hard turning of AISI 4340 steel (69 HRC)</title><title>International journal of advanced manufacturing technology</title><addtitle>Int J Adv Manuf Technol</addtitle><description>Continuous research endeavors on hard turning (HT), both on machine tools and cutting tools, have made the previously reported daunting limits easily attainable in the modern scenario. This presents an opportunity for a systematic investigation on finding the current attainable limits of hard turning using a CNC turret lathe. Accordingly, this study aims to contribute to the existing literature by providing the latest experimental results of hard turning of AISI 4340 steel (69 HRC) using a CBN cutting tool. An orthogonal array was implemented using a set of judiciously chosen cutting parameters. Subsequently, the longitudinal turning trials were carried out in accordance with a well-designed full factorial-based Taguchi matrix. The speculation indeed proved correct as a mirror finished optical quality machined surface (an average surface roughness value of 45 nm) was achieved by the conventional cutting method using a CBN cutting tool. Furthermore, signal to noise (S/N) ratio analysis, analysis of variance (ANOVA), and multiple regression analysis were carried out on the experimental datasets to assert the dominance of each machining variable in dictating the machined surface roughness and to optimize the machining parameters. One of the key findings was that when feed rate during hard turning approaches very low (about 0.02 mm/rev), it could alone be most significant (99.16 %) parameter in influencing the machined surface roughness (Ra). This has, however, also been shown that low feed rate results in high tool wear; so, the selection of machining parameters for carrying out hard turning must be governed by a trade-off between the cost and quality considerations.</description><subject>CAE) and Design</subject><subject>Computer-Aided Engineering (CAD</subject><subject>Cutting parameters</subject><subject>Cutting tools</subject><subject>Design optimization</subject><subject>Engineering</subject><subject>Feed rate</subject><subject>High strength low alloy steels</subject><subject>Industrial and Production Engineering</subject><subject>Machine tools</subject><subject>Mechanical Engineering</subject><subject>Media Management</subject><subject>Multiple regression analysis</subject><subject>Nickel chromium molybdenum steels</subject><subject>Numerical controls</subject><subject>Original Article</subject><subject>Orthogonal arrays</subject><subject>Parametric statistics</subject><subject>Product design</subject><subject>Surface roughness</subject><subject>Tool wear</subject><subject>Turning (machining)</subject><subject>Turret lathes</subject><subject>Variance analysis</subject><issn>0268-3768</issn><issn>1433-3015</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2016</creationdate><recordtype>article</recordtype><recordid>eNp1kEtLAzEUhYMoWKs_wF3AjS6iN49JJstSrK0UFB_rkMlkako7U5PpQn-9KSO4Em6494bvnISD0CWFWwqg7hIAVUCAFkRxrgg7QiMqOCc8Xx2jETBZEq5keYrOUlpnWlJZjtDjs4126_sYHK59CqsWd7s-bMO37UOXlwZ_2Fjjfh_b0K4O-2TxusCCC8Cp936Dr6XG85fpzTk6aewm-YvfPkbvs_u36Zwsnx4W08mSOMF0TypdFF5aR5mqhRCVZFrlQ6vKQV1Tp11RFr60ZSN8oRXUefbeUykBNKOOj9HV4LuL3efep96su_y7_KRhTObKJM0UHSgXu5Sib8wuhq2NX4aCOURmhshMzsccIjMsa9igSZltVz7-Of8v-gEA7mtF</recordid><startdate>20160101</startdate><enddate>20160101</enddate><creator>Rashid, Waleed Bin</creator><creator>Goel, Saurav</creator><creator>Davim, J. Paulo</creator><creator>Joshi, Shrikrishna N.</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/0000-0002-8694-332X</orcidid></search><sort><creationdate>20160101</creationdate><title>Parametric design optimization of hard turning of AISI 4340 steel (69 HRC)</title><author>Rashid, Waleed Bin ; Goel, Saurav ; Davim, J. Paulo ; Joshi, Shrikrishna N.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c429t-b955e6ac127d444b62976291bbc0dd1c9c585e8a8f4e5970de8aeee16600921c3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2016</creationdate><topic>CAE) and Design</topic><topic>Computer-Aided Engineering (CAD</topic><topic>Cutting parameters</topic><topic>Cutting tools</topic><topic>Design optimization</topic><topic>Engineering</topic><topic>Feed rate</topic><topic>High strength low alloy steels</topic><topic>Industrial and Production Engineering</topic><topic>Machine tools</topic><topic>Mechanical Engineering</topic><topic>Media Management</topic><topic>Multiple regression analysis</topic><topic>Nickel chromium molybdenum steels</topic><topic>Numerical controls</topic><topic>Original Article</topic><topic>Orthogonal arrays</topic><topic>Parametric statistics</topic><topic>Product design</topic><topic>Surface roughness</topic><topic>Tool wear</topic><topic>Turning (machining)</topic><topic>Turret lathes</topic><topic>Variance analysis</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Rashid, Waleed Bin</creatorcontrib><creatorcontrib>Goel, Saurav</creatorcontrib><creatorcontrib>Davim, J. Paulo</creatorcontrib><creatorcontrib>Joshi, Shrikrishna N.</creatorcontrib><collection>CrossRef</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>Materials Science & Engineering Collection</collection><collection>ProQuest Central</collection><collection>AUTh Library subscriptions: ProQuest Central</collection><collection>Technology Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central</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>Rashid, Waleed Bin</au><au>Goel, Saurav</au><au>Davim, J. Paulo</au><au>Joshi, Shrikrishna N.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Parametric design optimization of hard turning of AISI 4340 steel (69 HRC)</atitle><jtitle>International journal of advanced manufacturing technology</jtitle><stitle>Int J Adv Manuf Technol</stitle><date>2016-01-01</date><risdate>2016</risdate><volume>82</volume><issue>1-4</issue><spage>451</spage><epage>462</epage><pages>451-462</pages><issn>0268-3768</issn><eissn>1433-3015</eissn><abstract>Continuous research endeavors on hard turning (HT), both on machine tools and cutting tools, have made the previously reported daunting limits easily attainable in the modern scenario. This presents an opportunity for a systematic investigation on finding the current attainable limits of hard turning using a CNC turret lathe. Accordingly, this study aims to contribute to the existing literature by providing the latest experimental results of hard turning of AISI 4340 steel (69 HRC) using a CBN cutting tool. An orthogonal array was implemented using a set of judiciously chosen cutting parameters. Subsequently, the longitudinal turning trials were carried out in accordance with a well-designed full factorial-based Taguchi matrix. The speculation indeed proved correct as a mirror finished optical quality machined surface (an average surface roughness value of 45 nm) was achieved by the conventional cutting method using a CBN cutting tool. Furthermore, signal to noise (S/N) ratio analysis, analysis of variance (ANOVA), and multiple regression analysis were carried out on the experimental datasets to assert the dominance of each machining variable in dictating the machined surface roughness and to optimize the machining parameters. One of the key findings was that when feed rate during hard turning approaches very low (about 0.02 mm/rev), it could alone be most significant (99.16 %) parameter in influencing the machined surface roughness (Ra). This has, however, also been shown that low feed rate results in high tool wear; so, the selection of machining parameters for carrying out hard turning must be governed by a trade-off between the cost and quality considerations.</abstract><cop>London</cop><pub>Springer London</pub><doi>10.1007/s00170-015-7337-2</doi><tpages>12</tpages><orcidid>https://orcid.org/0000-0002-8694-332X</orcidid><oa>free_for_read</oa></addata></record> |
fulltext | fulltext |
identifier | ISSN: 0268-3768 |
ispartof | International journal of advanced manufacturing technology, 2016-01, Vol.82 (1-4), p.451-462 |
issn | 0268-3768 1433-3015 |
language | eng |
recordid | cdi_proquest_journals_2262266601 |
source | Springer Nature |
subjects | CAE) and Design Computer-Aided Engineering (CAD Cutting parameters Cutting tools Design optimization Engineering Feed rate High strength low alloy steels Industrial and Production Engineering Machine tools Mechanical Engineering Media Management Multiple regression analysis Nickel chromium molybdenum steels Numerical controls Original Article Orthogonal arrays Parametric statistics Product design Surface roughness Tool wear Turning (machining) Turret lathes Variance analysis |
title | Parametric design optimization of hard turning of AISI 4340 steel (69 HRC) |
url | http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-30T02%3A34%3A54IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Parametric%20design%20optimization%20of%20hard%20turning%20of%20AISI%204340%20steel%20(69%20HRC)&rft.jtitle=International%20journal%20of%20advanced%20manufacturing%20technology&rft.au=Rashid,%20Waleed%20Bin&rft.date=2016-01-01&rft.volume=82&rft.issue=1-4&rft.spage=451&rft.epage=462&rft.pages=451-462&rft.issn=0268-3768&rft.eissn=1433-3015&rft_id=info:doi/10.1007/s00170-015-7337-2&rft_dat=%3Cproquest_cross%3E2262266601%3C/proquest_cross%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-c429t-b955e6ac127d444b62976291bbc0dd1c9c585e8a8f4e5970de8aeee16600921c3%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_pqid=2262266601&rft_id=info:pmid/&rfr_iscdi=true |