Measurement of surface characteristics of Ti6Al4V aerospace engineering components in mass finishing process
•A novel integrated computational approach is introduced for mass finishing process.•High accuracy of proposed model compared to traditional modeling techniques.•Abrasive media type is the most dominant process parameter in finishing process. Mass finishing is a secondary manufacturing process emplo...
Gespeichert in:
Veröffentlicht in: | Measurement : journal of the International Measurement Confederation 2018-02, Vol.115, p.279-287 |
---|---|
Hauptverfasser: | , |
Format: | Artikel |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
container_end_page | 287 |
---|---|
container_issue | |
container_start_page | 279 |
container_title | Measurement : journal of the International Measurement Confederation |
container_volume | 115 |
creator | Vijayaraghavan, V. Castagne, S. |
description | •A novel integrated computational approach is introduced for mass finishing process.•High accuracy of proposed model compared to traditional modeling techniques.•Abrasive media type is the most dominant process parameter in finishing process.
Mass finishing is a secondary manufacturing process employed in aerospace and automotive industries to obtain the required surface finish of engineering parts. The finishing process involves interaction of several input process parameters related to the finishing machine, abrasive media and the parts to be finished. A robust empirical model which can accurately predict the system behavior and capture the science of complex interactions between process variables would provide great insights on mass finishing process. To address this challenge, the authors have proposed a novel integrated data analytics model by combining two powerful evolutionary techniques, Gene Expression Programming and Adaptive Neuro-Fuzzy Inference system. The proposed integrated approach was able to capture the dynamics of mass finishing process more accurately compared to that of other commonly available data analytical models. Tribological analysis of the model showed that an optimal surface finish of mass finished part can be achieved in mass finishing process by regulating the process time and media type. It is anticipated that the proposed model can be useful for determining optimal parameters for achieving desired surface finish without the need to conduct experiments, thereby leading to considerable savings in materials and time. |
doi_str_mv | 10.1016/j.measurement.2017.10.054 |
format | Article |
fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_journals_2062972938</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><els_id>S0263224117306899</els_id><sourcerecordid>2062972938</sourcerecordid><originalsourceid>FETCH-LOGICAL-c349t-ead72a94d767e86c76477629c822715cf7a9a95380290bed511b91bf367f42bf3</originalsourceid><addsrcrecordid>eNqNUFtLwzAUDqLgnP6HiM-tSZomzeMY3mDiyxTfQpaebilrWpNO8N-bMkEffTqH8904H0LXlOSUUHHb5h2YeAjQgR9zRqhM95yU_ATNaCWLjFP2fopmhIkiY4zTc3QRY0sIEYUSM7R__pXjvsFpb4wFbHcmGDtCcHF0Nk7Q2onFnr9hA6GPw0QCv3UeEsdvse27offJJWLncWdixI3zLu4mcAi9hRgv0Vlj9hGufuYcvd7frZeP2erl4Wm5WGW24GrMwNSSGcVrKSRUwkrBpRRM2YoxSUvbSKOMKouKMEU2UJeUbhTdNIWQDWdpztHN0TflfhwgjrrtD8GnSM1IMpJMFVViqSPLpn9igEYPwXUmfGlK9FSubvWfcvVU7gSlcpN2edRCeuPTQdDROvAWahfAjrru3T9cvgHhlYrL</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2062972938</pqid></control><display><type>article</type><title>Measurement of surface characteristics of Ti6Al4V aerospace engineering components in mass finishing process</title><source>ScienceDirect Journals (5 years ago - present)</source><creator>Vijayaraghavan, V. ; Castagne, S.</creator><creatorcontrib>Vijayaraghavan, V. ; Castagne, S.</creatorcontrib><description>•A novel integrated computational approach is introduced for mass finishing process.•High accuracy of proposed model compared to traditional modeling techniques.•Abrasive media type is the most dominant process parameter in finishing process.
Mass finishing is a secondary manufacturing process employed in aerospace and automotive industries to obtain the required surface finish of engineering parts. The finishing process involves interaction of several input process parameters related to the finishing machine, abrasive media and the parts to be finished. A robust empirical model which can accurately predict the system behavior and capture the science of complex interactions between process variables would provide great insights on mass finishing process. To address this challenge, the authors have proposed a novel integrated data analytics model by combining two powerful evolutionary techniques, Gene Expression Programming and Adaptive Neuro-Fuzzy Inference system. The proposed integrated approach was able to capture the dynamics of mass finishing process more accurately compared to that of other commonly available data analytical models. Tribological analysis of the model showed that an optimal surface finish of mass finished part can be achieved in mass finishing process by regulating the process time and media type. It is anticipated that the proposed model can be useful for determining optimal parameters for achieving desired surface finish without the need to conduct experiments, thereby leading to considerable savings in materials and time.</description><identifier>ISSN: 0263-2241</identifier><identifier>EISSN: 1873-412X</identifier><identifier>DOI: 10.1016/j.measurement.2017.10.054</identifier><language>eng</language><publisher>London: Elsevier Ltd</publisher><subject>Abrasive finishing ; Abrasive machining ; Adaptive systems ; Aerospace engineering ; Aerospace industry ; Aircraft components ; Analytics ; Artificial neural networks ; Automobile industry ; Automotive engineering ; Automotive parts ; Complex variables ; Data analysis ; Data analytics ; Empirical analysis ; Fuzzy logic ; Fuzzy systems ; Gene expression ; Mass finishing ; Mathematical models ; Optimization ; Process parameters ; Process variables ; Surface finish ; Surface properties ; Titanium base alloys ; Tribology</subject><ispartof>Measurement : journal of the International Measurement Confederation, 2018-02, Vol.115, p.279-287</ispartof><rights>2017 Elsevier Ltd</rights><rights>Copyright Elsevier Science Ltd. Feb 2018</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c349t-ead72a94d767e86c76477629c822715cf7a9a95380290bed511b91bf367f42bf3</citedby><cites>FETCH-LOGICAL-c349t-ead72a94d767e86c76477629c822715cf7a9a95380290bed511b91bf367f42bf3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://dx.doi.org/10.1016/j.measurement.2017.10.054$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>314,780,784,3550,27924,27925,45995</link.rule.ids></links><search><creatorcontrib>Vijayaraghavan, V.</creatorcontrib><creatorcontrib>Castagne, S.</creatorcontrib><title>Measurement of surface characteristics of Ti6Al4V aerospace engineering components in mass finishing process</title><title>Measurement : journal of the International Measurement Confederation</title><description>•A novel integrated computational approach is introduced for mass finishing process.•High accuracy of proposed model compared to traditional modeling techniques.•Abrasive media type is the most dominant process parameter in finishing process.
Mass finishing is a secondary manufacturing process employed in aerospace and automotive industries to obtain the required surface finish of engineering parts. The finishing process involves interaction of several input process parameters related to the finishing machine, abrasive media and the parts to be finished. A robust empirical model which can accurately predict the system behavior and capture the science of complex interactions between process variables would provide great insights on mass finishing process. To address this challenge, the authors have proposed a novel integrated data analytics model by combining two powerful evolutionary techniques, Gene Expression Programming and Adaptive Neuro-Fuzzy Inference system. The proposed integrated approach was able to capture the dynamics of mass finishing process more accurately compared to that of other commonly available data analytical models. Tribological analysis of the model showed that an optimal surface finish of mass finished part can be achieved in mass finishing process by regulating the process time and media type. It is anticipated that the proposed model can be useful for determining optimal parameters for achieving desired surface finish without the need to conduct experiments, thereby leading to considerable savings in materials and time.</description><subject>Abrasive finishing</subject><subject>Abrasive machining</subject><subject>Adaptive systems</subject><subject>Aerospace engineering</subject><subject>Aerospace industry</subject><subject>Aircraft components</subject><subject>Analytics</subject><subject>Artificial neural networks</subject><subject>Automobile industry</subject><subject>Automotive engineering</subject><subject>Automotive parts</subject><subject>Complex variables</subject><subject>Data analysis</subject><subject>Data analytics</subject><subject>Empirical analysis</subject><subject>Fuzzy logic</subject><subject>Fuzzy systems</subject><subject>Gene expression</subject><subject>Mass finishing</subject><subject>Mathematical models</subject><subject>Optimization</subject><subject>Process parameters</subject><subject>Process variables</subject><subject>Surface finish</subject><subject>Surface properties</subject><subject>Titanium base alloys</subject><subject>Tribology</subject><issn>0263-2241</issn><issn>1873-412X</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2018</creationdate><recordtype>article</recordtype><recordid>eNqNUFtLwzAUDqLgnP6HiM-tSZomzeMY3mDiyxTfQpaebilrWpNO8N-bMkEffTqH8904H0LXlOSUUHHb5h2YeAjQgR9zRqhM95yU_ATNaCWLjFP2fopmhIkiY4zTc3QRY0sIEYUSM7R__pXjvsFpb4wFbHcmGDtCcHF0Nk7Q2onFnr9hA6GPw0QCv3UeEsdvse27offJJWLncWdixI3zLu4mcAi9hRgv0Vlj9hGufuYcvd7frZeP2erl4Wm5WGW24GrMwNSSGcVrKSRUwkrBpRRM2YoxSUvbSKOMKouKMEU2UJeUbhTdNIWQDWdpztHN0TflfhwgjrrtD8GnSM1IMpJMFVViqSPLpn9igEYPwXUmfGlK9FSubvWfcvVU7gSlcpN2edRCeuPTQdDROvAWahfAjrru3T9cvgHhlYrL</recordid><startdate>201802</startdate><enddate>201802</enddate><creator>Vijayaraghavan, V.</creator><creator>Castagne, S.</creator><general>Elsevier Ltd</general><general>Elsevier Science Ltd</general><scope>AAYXX</scope><scope>CITATION</scope></search><sort><creationdate>201802</creationdate><title>Measurement of surface characteristics of Ti6Al4V aerospace engineering components in mass finishing process</title><author>Vijayaraghavan, V. ; Castagne, S.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c349t-ead72a94d767e86c76477629c822715cf7a9a95380290bed511b91bf367f42bf3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2018</creationdate><topic>Abrasive finishing</topic><topic>Abrasive machining</topic><topic>Adaptive systems</topic><topic>Aerospace engineering</topic><topic>Aerospace industry</topic><topic>Aircraft components</topic><topic>Analytics</topic><topic>Artificial neural networks</topic><topic>Automobile industry</topic><topic>Automotive engineering</topic><topic>Automotive parts</topic><topic>Complex variables</topic><topic>Data analysis</topic><topic>Data analytics</topic><topic>Empirical analysis</topic><topic>Fuzzy logic</topic><topic>Fuzzy systems</topic><topic>Gene expression</topic><topic>Mass finishing</topic><topic>Mathematical models</topic><topic>Optimization</topic><topic>Process parameters</topic><topic>Process variables</topic><topic>Surface finish</topic><topic>Surface properties</topic><topic>Titanium base alloys</topic><topic>Tribology</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Vijayaraghavan, V.</creatorcontrib><creatorcontrib>Castagne, S.</creatorcontrib><collection>CrossRef</collection><jtitle>Measurement : journal of the International Measurement Confederation</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Vijayaraghavan, V.</au><au>Castagne, S.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Measurement of surface characteristics of Ti6Al4V aerospace engineering components in mass finishing process</atitle><jtitle>Measurement : journal of the International Measurement Confederation</jtitle><date>2018-02</date><risdate>2018</risdate><volume>115</volume><spage>279</spage><epage>287</epage><pages>279-287</pages><issn>0263-2241</issn><eissn>1873-412X</eissn><abstract>•A novel integrated computational approach is introduced for mass finishing process.•High accuracy of proposed model compared to traditional modeling techniques.•Abrasive media type is the most dominant process parameter in finishing process.
Mass finishing is a secondary manufacturing process employed in aerospace and automotive industries to obtain the required surface finish of engineering parts. The finishing process involves interaction of several input process parameters related to the finishing machine, abrasive media and the parts to be finished. A robust empirical model which can accurately predict the system behavior and capture the science of complex interactions between process variables would provide great insights on mass finishing process. To address this challenge, the authors have proposed a novel integrated data analytics model by combining two powerful evolutionary techniques, Gene Expression Programming and Adaptive Neuro-Fuzzy Inference system. The proposed integrated approach was able to capture the dynamics of mass finishing process more accurately compared to that of other commonly available data analytical models. Tribological analysis of the model showed that an optimal surface finish of mass finished part can be achieved in mass finishing process by regulating the process time and media type. It is anticipated that the proposed model can be useful for determining optimal parameters for achieving desired surface finish without the need to conduct experiments, thereby leading to considerable savings in materials and time.</abstract><cop>London</cop><pub>Elsevier Ltd</pub><doi>10.1016/j.measurement.2017.10.054</doi><tpages>9</tpages></addata></record> |
fulltext | fulltext |
identifier | ISSN: 0263-2241 |
ispartof | Measurement : journal of the International Measurement Confederation, 2018-02, Vol.115, p.279-287 |
issn | 0263-2241 1873-412X |
language | eng |
recordid | cdi_proquest_journals_2062972938 |
source | ScienceDirect Journals (5 years ago - present) |
subjects | Abrasive finishing Abrasive machining Adaptive systems Aerospace engineering Aerospace industry Aircraft components Analytics Artificial neural networks Automobile industry Automotive engineering Automotive parts Complex variables Data analysis Data analytics Empirical analysis Fuzzy logic Fuzzy systems Gene expression Mass finishing Mathematical models Optimization Process parameters Process variables Surface finish Surface properties Titanium base alloys Tribology |
title | Measurement of surface characteristics of Ti6Al4V aerospace engineering components in mass finishing process |
url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-08T03%3A19%3A10IST&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=Measurement%20of%20surface%20characteristics%20of%20Ti6Al4V%20aerospace%20engineering%20components%20in%20mass%20finishing%20process&rft.jtitle=Measurement%20:%20journal%20of%20the%20International%20Measurement%20Confederation&rft.au=Vijayaraghavan,%20V.&rft.date=2018-02&rft.volume=115&rft.spage=279&rft.epage=287&rft.pages=279-287&rft.issn=0263-2241&rft.eissn=1873-412X&rft_id=info:doi/10.1016/j.measurement.2017.10.054&rft_dat=%3Cproquest_cross%3E2062972938%3C/proquest_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2062972938&rft_id=info:pmid/&rft_els_id=S0263224117306899&rfr_iscdi=true |