Multi-objective optimization of CFRP drilling parameters with a hybrid method integrating the ANN, NSGA-II and fuzzy C-means
A full factorial experiment is performed for the conventional dry drilling of CFRP with spindle speed, feed rate and point angle as drilling parameters, response variables are thrust force and exit-delamination. Artificial neural network (ANN) is developed to express thrust force and delamination fa...
Saved in:
| Published in: | Composite structures Vol. 235; p. 111803 |
|---|---|
| Main Authors: | , |
| Format: | Journal Article |
| Language: | English |
| Published: |
Elsevier Ltd
01.03.2020
|
| Subjects: | |
| ISSN: | 0263-8223, 1879-1085 |
| Online Access: | Get full text |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Abstract | A full factorial experiment is performed for the conventional dry drilling of CFRP with spindle speed, feed rate and point angle as drilling parameters, response variables are thrust force and exit-delamination. Artificial neural network (ANN) is developed to express thrust force and delamination factor as a function of drilling parameters. Multi-objective optimization of drilling parameters is accomplished based on Non-dominated Sorting Genetic Algorithm (NSGA-II) with thrust force, delamination factor and material removal rate as optimization objectives, delamination factor also serves as a constraint. The Pareto front of drilling response variables determined by NSGA-II consists of a large number of non-dominated solutions. In order to facilitate the experimental verification of optimization results, fuzzy C-means clustering algorithm is used to narrow down the solutions on the front to several representative ones. Conformation tests are conducted and results show that the representative solutions can give satisfactory performance with achieving a trade-off among thrust force, exit-delamination and material removal rate. |
|---|---|
| AbstractList | A full factorial experiment is performed for the conventional dry drilling of CFRP with spindle speed, feed rate and point angle as drilling parameters, response variables are thrust force and exit-delamination. Artificial neural network (ANN) is developed to express thrust force and delamination factor as a function of drilling parameters. Multi-objective optimization of drilling parameters is accomplished based on Non-dominated Sorting Genetic Algorithm (NSGA-II) with thrust force, delamination factor and material removal rate as optimization objectives, delamination factor also serves as a constraint. The Pareto front of drilling response variables determined by NSGA-II consists of a large number of non-dominated solutions. In order to facilitate the experimental verification of optimization results, fuzzy C-means clustering algorithm is used to narrow down the solutions on the front to several representative ones. Conformation tests are conducted and results show that the representative solutions can give satisfactory performance with achieving a trade-off among thrust force, exit-delamination and material removal rate. |
| ArticleNumber | 111803 |
| Author | Wang, Qian Jia, Xiaoliang |
| Author_xml | – sequence: 1 givenname: Qian surname: Wang fullname: Wang, Qian email: wq_w@mail.nwpu.edu.cn – sequence: 2 givenname: Xiaoliang surname: Jia fullname: Jia, Xiaoliang email: jiaxl@nwpu.edu.cn |
| BookMark | eNqNkNtKAzEQhoMoWA_vkAdwa5LtbrM3Qi0eClrFw3XIJrPtlN1NSVKlxYd3awXBG70amPn_D-Y7Ivuta4EQylmfM56fL_rGNcsQ_crEvmC86HPOJUv3SI_LYZFwJrN90mMiTxMpRHpIjkJYMMbkgPMe-bhf1RETVy7ARHwD6pYRG9zoiK6lrqLj66dHaj3WNbYzutReNxDBB_qOcU41na9Lj5Z2y7mzFNsIM9-Vu2ycAx1Np2d0-nwzSiYTqltLq9Vms6bjpAHdhhNyUOk6wOn3PCav11cv49vk7uFmMh7dJSblMiaVKGwFeSZKYYZSgBCmACgqkclBPkiZ0CyzUOmsKO3QSJtCkcky1zzl3bVLHJOLHdd4F4KHShmMXx9Gr7FWnKmtS7VQPy7V1qXauewA8hdg6bHRfv2f6uWuCt2DbwheBYPQGrDoO-XKOvwb8glqR5j5 |
| CitedBy_id | crossref_primary_10_1016_j_eswa_2025_126765 crossref_primary_10_1016_j_compositesb_2022_109752 crossref_primary_10_1016_j_engappai_2023_106047 crossref_primary_10_1007_s00170_022_09121_3 crossref_primary_10_1016_j_compositesb_2025_112701 crossref_primary_10_1016_j_compstruct_2021_113764 crossref_primary_10_1007_s00170_024_14317_w crossref_primary_10_1177_09544089241230160 crossref_primary_10_1016_j_compositesb_2021_109034 crossref_primary_10_1016_j_compstruct_2023_116713 crossref_primary_10_1007_s00170_022_10112_7 crossref_primary_10_1007_s40430_022_03806_2 crossref_primary_10_1177_07316844251318852 crossref_primary_10_1007_s10845_023_02315_w crossref_primary_10_3390_ma15030933 crossref_primary_10_1007_s10845_024_02503_2 crossref_primary_10_1177_09544062231207491 crossref_primary_10_1177_16878132251358905 crossref_primary_10_32604_fdmp_2022_019577 crossref_primary_10_1016_j_cie_2022_108022 crossref_primary_10_1016_j_energy_2023_127518 crossref_primary_10_1007_s00170_021_06616_3 crossref_primary_10_1016_j_cie_2024_110207 crossref_primary_10_1007_s11665_021_05807_z crossref_primary_10_1007_s00170_021_07918_2 crossref_primary_10_3390_polym13142246 crossref_primary_10_1002_pc_29193 crossref_primary_10_1007_s12633_021_00977_w crossref_primary_10_1016_j_jclepro_2021_129479 crossref_primary_10_1016_j_jclepro_2021_126153 crossref_primary_10_21062_mft_2024_064 crossref_primary_10_1016_j_jmapro_2022_02_040 crossref_primary_10_1016_j_tws_2025_113721 crossref_primary_10_1088_1742_6596_2484_1_012039 crossref_primary_10_1061_JAEEEZ_ASENG_6092 crossref_primary_10_1016_j_tws_2023_111086 crossref_primary_10_1177_08927057241264803 |
| Cites_doi | 10.1007/s00170-011-3785-5 10.1016/j.compstruct.2016.07.015 10.1016/j.compstruct.2017.12.005 10.1016/j.compositesb.2019.106936 10.1016/j.jmatprotec.2006.04.126 10.1016/j.compositesb.2012.01.007 10.1016/j.jmatprotec.2007.04.121 10.1016/j.measurement.2015.09.015 10.1007/s00158-015-1324-y 10.1016/j.ejor.2010.10.021 10.1016/j.jclepro.2019.04.187 10.1007/s00170-007-0963-6 10.1109/4235.996017 10.1016/j.jmatprotec.2018.06.037 10.1021/jp502557s 10.1007/s00521-014-1721-y 10.1016/j.ijmachtools.2010.06.005 10.1016/j.compositesb.2017.05.039 10.1016/j.matdes.2008.03.014 10.1016/j.compstruct.2018.10.107 10.1016/j.chemolab.2016.09.007 10.1016/S0890-6955(96)00095-8 10.1016/j.jmatprotec.2007.01.016 10.1007/s00170-007-0999-7 10.1016/j.compstruct.2016.03.059 10.1007/s00170-018-1981-2 10.1016/j.measurement.2012.01.008 10.1016/j.compstruct.2016.08.004 10.1016/j.eswa.2017.01.004 10.1016/0377-0427(87)90125-7 10.1016/j.eswa.2019.04.032 10.1016/j.jmatprotec.2018.07.026 10.1016/j.jmatprotec.2007.11.082 10.1007/s13042-017-0668-6 10.1016/j.measurement.2017.07.007 10.1016/j.jmatprotec.2016.10.007 |
| ContentType | Journal Article |
| Copyright | 2019 Elsevier Ltd |
| Copyright_xml | – notice: 2019 Elsevier Ltd |
| DBID | AAYXX CITATION |
| DOI | 10.1016/j.compstruct.2019.111803 |
| DatabaseName | CrossRef |
| DatabaseTitle | CrossRef |
| DatabaseTitleList | |
| DeliveryMethod | fulltext_linktorsrc |
| Discipline | Engineering |
| EISSN | 1879-1085 |
| ExternalDocumentID | 10_1016_j_compstruct_2019_111803 S0263822319330922 |
| GroupedDBID | --K --M .~1 0R~ 1B1 1~. 1~5 4.4 457 4G. 5GY 5VS 6TJ 7-5 71M 8P~ 9JN AABNK AABXZ AACTN AAEDT AAEDW AAEPC AAIAV AAIKJ AAKOC AALRI AAOAW AAQFI AAXUO ABMAC ABXRA ABYKQ ACDAQ ACGFS ACRLP ADBBV ADEZE ADTZH AEBSH AECPX AEKER AENEX AEZYN AFKWA AFRZQ AFTJW AGHFR AGUBO AGYEJ AHHHB AHJVU AIEXJ AIKHN AITUG AJOXV ALMA_UNASSIGNED_HOLDINGS AMFUW AMRAJ AXJTR BJAXD BKOJK BLXMC CS3 DU5 EBS EFJIC EFLBG EO8 EO9 EP2 EP3 FDB FIRID FNPLU FYGXN G-Q GBLVA IHE J1W JJJVA KOM LY7 M24 M41 MAGPM MO0 N9A O-L O9- OAUVE OZT P-8 P-9 P2P PC. Q38 RNS ROL RPZ SDF SDG SES SPC SPCBC SSM SST SSZ T5K XPP ZMT ~02 ~G- 29F 9DU AAQXK AATTM AAXKI AAYWO AAYXX ABFNM ABJNI ABWVN ABXDB ACLOT ACNNM ACRPL ACVFH ADCNI ADIYS ADMUD ADNMO AEIPS AEUPX AFJKZ AFPUW AGQPQ AIGII AIIUN AKBMS AKRWK AKYEP ANKPU APXCP ASPBG AVWKF AZFZN CITATION EFKBS EJD FEDTE FGOYB G-2 HVGLF HZ~ R2- SET SEW SMS WUQ ~HD |
| ID | FETCH-LOGICAL-c318t-f29dfe652b2c782e22c9ee9f258464302a05defa59bd7c8d3e958b6a131430643 |
| ISICitedReferencesCount | 46 |
| ISICitedReferencesURI | http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=000508631700048&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D |
| ISSN | 0263-8223 |
| IngestDate | Sat Nov 29 07:20:27 EST 2025 Tue Nov 18 22:14:44 EST 2025 Fri Feb 23 02:47:42 EST 2024 |
| IsPeerReviewed | true |
| IsScholarly | true |
| Keywords | Fuzzy C-means clustering algorithm Multi-objective optimization Artificial neural network (ANN) Carbon fiber reinforced polymer Non-dominated Sorting Genetic Algorithm (NSGA-II) |
| Language | English |
| LinkModel | OpenURL |
| MergedId | FETCHMERGED-LOGICAL-c318t-f29dfe652b2c782e22c9ee9f258464302a05defa59bd7c8d3e958b6a131430643 |
| ParticipantIDs | crossref_citationtrail_10_1016_j_compstruct_2019_111803 crossref_primary_10_1016_j_compstruct_2019_111803 elsevier_sciencedirect_doi_10_1016_j_compstruct_2019_111803 |
| PublicationCentury | 2000 |
| PublicationDate | 2020-03-01 2020-03-00 |
| PublicationDateYYYYMMDD | 2020-03-01 |
| PublicationDate_xml | – month: 03 year: 2020 text: 2020-03-01 day: 01 |
| PublicationDecade | 2020 |
| PublicationTitle | Composite structures |
| PublicationYear | 2020 |
| Publisher | Elsevier Ltd |
| Publisher_xml | – name: Elsevier Ltd |
| References | Basheer, Dabade, Joshi, Bhanuprasad, Gadre (b0130) 2008; 197 Kalla, Sheikh-Ahmad, Twomey (b0120) 2010; 50 Umbrello, Ambrogio, Filice, Shivpuri (b0135) 2007; 189 Zhang, Wu, Chen (b0005) 2019; 209 Krishnamoorthy, Boopathy, Palanikumar, Davim (b0040) 2012; 45 Zio, Bazzo (b0190) 2011; 210 Kamaloo, Jabbari, Tooski, Javadi (b0180) 2019; 174 Peng, Li, Zhao, Lv, Tan, Dong (b0170) 2019; 227 Su, Zheng, Sun, Wang, Deng, Qiu (b0065) 2018; 262 Qiu, Li, Niu, Chen, Ouyang, Li (b0025) 2018; 97 Girot, Dau, Gutiérrez-Orrantia (b0090) 2017; 240 Geier, Szalay (b0030) 2017; 110 Peter (b0205) 1987; 20 Tsao, Hocheng (b0035) 2008; 203 Ojo, Ismail, Paggi, Dhakal (b0085) 2017; 124 Davim, Gaitonde, Karnik (b0125) 2008; 205 Guo, Wen, Gao, Bao (b0110) 2011; 226 Abhishek, Datta, Mahapatra (b0045) 2016; 77 Dave, Raval (b0140) 2010; 8 Tang, Yu, Liu, Chen, Huang (b0195) 2019; 130 Tsao (b0015) 2012; 62 Karnik, Gaitonde, Rubio, Correia, Abrão, Davim (b0020) 2008; 29 Tsao (b0075) 2008; 37 Saoudi, Zitoune, Mezlini, Gururaja, Seitier (b0100) 2016; 153 Liu, Mei, Shen, Tu (b0115) 2014; 118 Zhang, Li, Zhang, Yu, Lu (b0200) 2018; 9 Karimi, Heidary, Minak (b0095) 2016; 148 Deb, Pratap, Agarwal, Meyarivan (b0175) 2002; 6 Mu, Su, Chu, Wang (b0185) 2003 Sorrentino, Turchetta, Bellini (b0080) 2018; 186 Zerti, Yallese, Zerti, Nouioua, Khettabi (b0155) 2019 Quiza, Figueira, Davim (b0150) 2008; 37 Chen (b0070) 1997; 37 Wang, Zhao, Wu, Wu (b0160) 2017; 74 Feito, Milani, Muñoz-Sánchez (b0055) 2016; 53 Joshi, Rawat, Balan (b0105) 2018; 262 Sánchez, Ortiz, Sarabia (b0165) 2016; 158 Saoudi, Zitoune, Gururaja, Mezlini, Hajjaji (b0060) 2016; 18 Krishnaraj, Prabukarthi, Ramanathan, Elanghovan, Kumar, Zitoune (b0050) 2012; 43 Kara, Aslantas, Cicek (b0145) 2015; 26 Gaugel, Sripathy, Haeger, Meinhard, Bernthaler, Lissek (b0010) 2016; 155 Karimi (10.1016/j.compstruct.2019.111803_b0095) 2016; 148 Tsao (10.1016/j.compstruct.2019.111803_b0075) 2008; 37 Qiu (10.1016/j.compstruct.2019.111803_b0025) 2018; 97 Sorrentino (10.1016/j.compstruct.2019.111803_b0080) 2018; 186 Davim (10.1016/j.compstruct.2019.111803_b0125) 2008; 205 Peng (10.1016/j.compstruct.2019.111803_b0170) 2019; 227 Zio (10.1016/j.compstruct.2019.111803_b0190) 2011; 210 Tsao (10.1016/j.compstruct.2019.111803_b0015) 2012; 62 Guo (10.1016/j.compstruct.2019.111803_b0110) 2011; 226 Mu (10.1016/j.compstruct.2019.111803_b0185) 2003 Basheer (10.1016/j.compstruct.2019.111803_b0130) 2008; 197 Karnik (10.1016/j.compstruct.2019.111803_b0020) 2008; 29 Kara (10.1016/j.compstruct.2019.111803_b0145) 2015; 26 Wang (10.1016/j.compstruct.2019.111803_b0160) 2017; 74 Gaugel (10.1016/j.compstruct.2019.111803_b0010) 2016; 155 Feito (10.1016/j.compstruct.2019.111803_b0055) 2016; 53 Kalla (10.1016/j.compstruct.2019.111803_b0120) 2010; 50 Liu (10.1016/j.compstruct.2019.111803_b0115) 2014; 118 Umbrello (10.1016/j.compstruct.2019.111803_b0135) 2007; 189 Su (10.1016/j.compstruct.2019.111803_b0065) 2018; 262 Abhishek (10.1016/j.compstruct.2019.111803_b0045) 2016; 77 Krishnaraj (10.1016/j.compstruct.2019.111803_b0050) 2012; 43 Tang (10.1016/j.compstruct.2019.111803_b0195) 2019; 130 Quiza (10.1016/j.compstruct.2019.111803_b0150) 2008; 37 Kamaloo (10.1016/j.compstruct.2019.111803_b0180) 2019; 174 Saoudi (10.1016/j.compstruct.2019.111803_b0100) 2016; 153 Zhang (10.1016/j.compstruct.2019.111803_b0200) 2018; 9 Saoudi (10.1016/j.compstruct.2019.111803_b0060) 2016; 18 Ojo (10.1016/j.compstruct.2019.111803_b0085) 2017; 124 Dave (10.1016/j.compstruct.2019.111803_b0140) 2010; 8 Chen (10.1016/j.compstruct.2019.111803_b0070) 1997; 37 Geier (10.1016/j.compstruct.2019.111803_b0030) 2017; 110 Peter (10.1016/j.compstruct.2019.111803_b0205) 1987; 20 Krishnamoorthy (10.1016/j.compstruct.2019.111803_b0040) 2012; 45 Tsao (10.1016/j.compstruct.2019.111803_b0035) 2008; 203 Zerti (10.1016/j.compstruct.2019.111803_b0155) 2019 Girot (10.1016/j.compstruct.2019.111803_b0090) 2017; 240 Sánchez (10.1016/j.compstruct.2019.111803_b0165) 2016; 158 Deb (10.1016/j.compstruct.2019.111803_b0175) 2002; 6 Zhang (10.1016/j.compstruct.2019.111803_b0005) 2019; 209 Joshi (10.1016/j.compstruct.2019.111803_b0105) 2018; 262 |
| References_xml | – volume: 37 start-page: 23 year: 2008 end-page: 28 ident: b0075 article-title: Thrust force and delamination of core-saw drill during drilling of carbon fiber reinforced plastics (CFRP) publication-title: Int J Adv Manuf Technol – volume: 118 start-page: 10686 year: 2014 end-page: 10693 ident: b0115 article-title: Nonoxidative conversion of methane in a dielectric barrier discharge reactor: prediction of reaction performance based on neural network model publication-title: J Phys Chem C – volume: 174 year: 2019 ident: b0180 article-title: Optimization of thickness and delamination growth in composite laminates under multi-axial fatigue loading using NSGA-II publication-title: Compos Part B-Eng – volume: 130 start-page: 265 year: 2019 end-page: 275 ident: b0195 article-title: A hierarchical prediction model for lane-changes based on combination of fuzzy C-means and adaptive neural network publication-title: Expert Syst Appl – volume: 62 start-page: 241 year: 2012 end-page: 247 ident: b0015 article-title: Evaluation of the drilling-induced delamination of compound core-special drills using response surface methodology based on the Taguchi method publication-title: Int J Adv Manuf Technol – volume: 8 start-page: 198 year: 2010 ident: b0140 article-title: Modelling of cutting forces as a function of cutting parameters in milling process using regression analysis and artificial neural network publication-title: Int J Mach Mach Mater – volume: 77 start-page: 222 year: 2016 end-page: 239 ident: b0045 article-title: Multi-objective optimization in drilling of CFRP (polyester) composites: application of a fuzzy embedded harmony search (HS) algorithm publication-title: Measurement – volume: 205 start-page: 16 year: 2008 end-page: 23 ident: b0125 article-title: Investigations into the effect of cutting conditions on surface roughness in turning of free machining steel by ANN models publication-title: J Mater Process Technol – volume: 6 start-page: 182 year: 2002 end-page: 197 ident: b0175 article-title: A fast and elitist multiobjective genetic algorithm: NSGA-II publication-title: IEEE Trans Evol Comp – volume: 189 start-page: 143 year: 2007 end-page: 152 ident: b0135 article-title: An ANN approach for predicting subsurface residual stresses and the desired cutting conditions during hard turning publication-title: J Mater Process Technol – volume: 37 start-page: 641 year: 2008 end-page: 648 ident: b0150 article-title: Comparing statistical models and artificial neural networks on predicting the tool wear in hard machining D2 AISI steel publication-title: Int J Adv Manuf Technol – volume: 97 start-page: 857 year: 2018 end-page: 865 ident: b0025 article-title: Influence of machining parameters and tool structure on cutting force and hole wall damage in drilling CFRP with stepped drills publication-title: Int J Adv Manuf Technol – start-page: 914 year: 2003 end-page: 920 ident: b0185 article-title: An efficient evolutionary multi-objective optimization algorithm publication-title: Proceedings of the IEEE Congress on Evolutionary Computation – volume: 240 start-page: 332 year: 2017 end-page: 343 ident: b0090 article-title: New analytical model for delamination of CFRP during drilling publication-title: J Mater Process Technol – volume: 262 start-page: 157 year: 2018 end-page: 167 ident: b0065 article-title: Novel drill bit based on the step-control scheme for reducing the CFRP delamination publication-title: J Mater Process Technol – volume: 18 start-page: 77 year: 2016 end-page: 98 ident: b0060 article-title: Prediction of critical thrust force for exit-ply delamination during drilling composite laminates: thermo-mechanical analysis publication-title: Int J Mach Mach Mater – volume: 20 start-page: 53 year: 1987 end-page: 65 ident: b0205 article-title: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis publication-title: J Comput Appl Math – volume: 26 start-page: 237 year: 2015 end-page: 250 ident: b0145 article-title: ANN and multiple regression method-based modeling of cuttingforces in orthogonal machining of AISI 316L stainless steel publication-title: Neural Comput Appl – start-page: 1989 year: 2019 end-page: 1996 ident: b0155 article-title: Prediction of machining performance using RSM and ANN models in hard turning of martensitic stainless steel AISI 420 publication-title: ARCHIVE P I Mech Part C: J Mech Eng Sci – volume: 226 start-page: 28 year: 2011 end-page: 42 ident: b0110 article-title: Prediction of the cutting forces generated in the drilling of carbon-fibre-reinforced plastic composites using a twist drill publication-title: P I Mech Eng B-J Eng – volume: 74 start-page: 96 year: 2017 end-page: 104 ident: b0160 article-title: Multi-objective optimization: a method for selecting the optimal solution from Pareto non-inferior solutions publication-title: Expert Syst Appl – volume: 197 start-page: 439 year: 2008 end-page: 444 ident: b0130 article-title: Modeling of surface roughness in precision machining of metal matrix composites using ANN publication-title: J Mater Process Technol – volume: 43 start-page: 1791 year: 2012 end-page: 1799 ident: b0050 article-title: Optimization of machining parameters at high speed drilling of carbon fiber reinforced plastic (CFRP) laminates publication-title: Compos PartB-Eng – volume: 148 start-page: 19 year: 2016 end-page: 26 ident: b0095 article-title: Critical thrust and feed prediction models in drilling of composite laminates publication-title: Compos Struct – volume: 227 start-page: 58 year: 2019 end-page: 69 ident: b0170 article-title: Towards energy and material efficient laser cladding process: modeling and optimization using a hybrid TS-GEP algorithm and the NSGA-II publication-title: J Clean Prod – volume: 50 start-page: 882 year: 2010 end-page: 891 ident: b0120 article-title: Prediction of cutting forces in helical end milling fiber reinforced polymers publication-title: Int J MachTools Manuf – volume: 155 start-page: 173 year: 2016 end-page: 183 ident: b0010 article-title: A comparative study on tool wear and laminate damage in drilling of carbon-fiber reinforced polymers (CFRP) publication-title: Compos Struct – volume: 203 start-page: 342 year: 2008 end-page: 348 ident: b0035 article-title: Evaluation of thrust force and surface roughness in drilling composite material using Taguchi analysis and neural network publication-title: J Mater Process Technol – volume: 262 start-page: 521 year: 2018 end-page: 531 ident: b0105 article-title: A novel approach to predict the delamination factor for dry and cryogenic drilling of CFRP publication-title: J Mater Process Technol – volume: 209 start-page: 337 year: 2019 end-page: 348 ident: b0005 article-title: A theoretical model for predicting the CFRP drilling-countersinking thrust force of stacks publication-title: Compo Struct – volume: 153 start-page: 886 year: 2016 end-page: 894 ident: b0100 article-title: Critical thrust force predictions during drilling: analytical modeling and X-ray tomography quantification publication-title: Compos Struct – volume: 210 start-page: 624 year: 2011 end-page: 634 ident: b0190 article-title: A clustering procedure for reducing the number of representative solutions in the Pareto Front of multiobjective optimization problems publication-title: Eur J Oper Res – volume: 45 start-page: 1286 year: 2012 end-page: 1296 ident: b0040 article-title: Application of grey fuzzy logic for the optimization of drilling parameters for CFRP composites with multiple performance characteristics publication-title: Measurement – volume: 37 start-page: 1097 year: 1997 end-page: 1108 ident: b0070 article-title: Some experimental investigations in the drilling of carbon fiber-reinforced plastic (CFRP) composite laminates publication-title: Int J Mach Tools Manuf – volume: 29 start-page: 1768 year: 2008 end-page: 1776 ident: b0020 article-title: Delamination analysis in high speed drilling of carbon fiber reinforced plastics (CFRP) using artificial neural network model publication-title: Mater Des – volume: 186 start-page: 154 year: 2018 end-page: 164 ident: b0080 article-title: A new method to reduce delaminations during drilling of FRP laminates by feed rate control publication-title: Compos Struct – volume: 124 start-page: 207 year: 2017 end-page: 217 ident: b0085 article-title: A new analytical critical thrust force model for delamination analysis of laminated composites during drilling operation publication-title: Compos Part B-Eng – volume: 9 start-page: 1609 year: 2018 end-page: 1621 ident: b0200 article-title: Fuzzy c-means clustering-based mating restriction for multiobjective optimization publication-title: Int J Mach Learn Cyber – volume: 110 start-page: 319 year: 2017 end-page: 334 ident: b0030 article-title: Optimisation of process parameters for the orbital and conventional drilling of uni-directional carbon fibre-reinforced polymers (UD-CFRP) publication-title: Measurement – volume: 53 start-page: 239 year: 2016 end-page: 251 ident: b0055 article-title: Drilling optimization of woven CFRP laminates under different tool wear conditions: a multi-objective design of experiments approach publication-title: Struct Multidisc Optim – volume: 158 start-page: 210 year: 2016 end-page: 217 ident: b0165 article-title: A useful tool for computation and interpretation of trading-off solutions through Pareto front in the field of experimental designs for mixtures publication-title: Chemom Intell Lab Syst – volume: 62 start-page: 241 issue: 1–4 year: 2012 ident: 10.1016/j.compstruct.2019.111803_b0015 article-title: Evaluation of the drilling-induced delamination of compound core-special drills using response surface methodology based on the Taguchi method publication-title: Int J Adv Manuf Technol doi: 10.1007/s00170-011-3785-5 – volume: 153 start-page: 886 year: 2016 ident: 10.1016/j.compstruct.2019.111803_b0100 article-title: Critical thrust force predictions during drilling: analytical modeling and X-ray tomography quantification publication-title: Compos Struct doi: 10.1016/j.compstruct.2016.07.015 – volume: 186 start-page: 154 year: 2018 ident: 10.1016/j.compstruct.2019.111803_b0080 article-title: A new method to reduce delaminations during drilling of FRP laminates by feed rate control publication-title: Compos Struct doi: 10.1016/j.compstruct.2017.12.005 – volume: 174 year: 2019 ident: 10.1016/j.compstruct.2019.111803_b0180 article-title: Optimization of thickness and delamination growth in composite laminates under multi-axial fatigue loading using NSGA-II publication-title: Compos Part B-Eng doi: 10.1016/j.compositesb.2019.106936 – volume: 203 start-page: 342 year: 2008 ident: 10.1016/j.compstruct.2019.111803_b0035 article-title: Evaluation of thrust force and surface roughness in drilling composite material using Taguchi analysis and neural network publication-title: J Mater Process Technol doi: 10.1016/j.jmatprotec.2006.04.126 – volume: 43 start-page: 1791 year: 2012 ident: 10.1016/j.compstruct.2019.111803_b0050 article-title: Optimization of machining parameters at high speed drilling of carbon fiber reinforced plastic (CFRP) laminates publication-title: Compos PartB-Eng doi: 10.1016/j.compositesb.2012.01.007 – volume: 197 start-page: 439 year: 2008 ident: 10.1016/j.compstruct.2019.111803_b0130 article-title: Modeling of surface roughness in precision machining of metal matrix composites using ANN publication-title: J Mater Process Technol doi: 10.1016/j.jmatprotec.2007.04.121 – volume: 77 start-page: 222 year: 2016 ident: 10.1016/j.compstruct.2019.111803_b0045 article-title: Multi-objective optimization in drilling of CFRP (polyester) composites: application of a fuzzy embedded harmony search (HS) algorithm publication-title: Measurement doi: 10.1016/j.measurement.2015.09.015 – volume: 53 start-page: 239 issue: 2 year: 2016 ident: 10.1016/j.compstruct.2019.111803_b0055 article-title: Drilling optimization of woven CFRP laminates under different tool wear conditions: a multi-objective design of experiments approach publication-title: Struct Multidisc Optim doi: 10.1007/s00158-015-1324-y – volume: 226 start-page: 28 issue: 1 year: 2011 ident: 10.1016/j.compstruct.2019.111803_b0110 article-title: Prediction of the cutting forces generated in the drilling of carbon-fibre-reinforced plastic composites using a twist drill publication-title: P I Mech Eng B-J Eng – volume: 210 start-page: 624 issue: 3 year: 2011 ident: 10.1016/j.compstruct.2019.111803_b0190 article-title: A clustering procedure for reducing the number of representative solutions in the Pareto Front of multiobjective optimization problems publication-title: Eur J Oper Res doi: 10.1016/j.ejor.2010.10.021 – volume: 227 start-page: 58 year: 2019 ident: 10.1016/j.compstruct.2019.111803_b0170 article-title: Towards energy and material efficient laser cladding process: modeling and optimization using a hybrid TS-GEP algorithm and the NSGA-II publication-title: J Clean Prod doi: 10.1016/j.jclepro.2019.04.187 – volume: 18 start-page: 77 issue: 1–2 year: 2016 ident: 10.1016/j.compstruct.2019.111803_b0060 article-title: Prediction of critical thrust force for exit-ply delamination during drilling composite laminates: thermo-mechanical analysis publication-title: Int J Mach Mach Mater – start-page: 1989 issue: 203-210 year: 2019 ident: 10.1016/j.compstruct.2019.111803_b0155 article-title: Prediction of machining performance using RSM and ANN models in hard turning of martensitic stainless steel AISI 420 publication-title: ARCHIVE P I Mech Part C: J Mech Eng Sci – volume: 37 start-page: 23 issue: 1–2 year: 2008 ident: 10.1016/j.compstruct.2019.111803_b0075 article-title: Thrust force and delamination of core-saw drill during drilling of carbon fiber reinforced plastics (CFRP) publication-title: Int J Adv Manuf Technol doi: 10.1007/s00170-007-0963-6 – volume: 6 start-page: 182 issue: 2 year: 2002 ident: 10.1016/j.compstruct.2019.111803_b0175 article-title: A fast and elitist multiobjective genetic algorithm: NSGA-II publication-title: IEEE Trans Evol Comp doi: 10.1109/4235.996017 – volume: 262 start-page: 157 year: 2018 ident: 10.1016/j.compstruct.2019.111803_b0065 article-title: Novel drill bit based on the step-control scheme for reducing the CFRP delamination publication-title: J Mater Process Technol doi: 10.1016/j.jmatprotec.2018.06.037 – volume: 118 start-page: 10686 issue: 20 year: 2014 ident: 10.1016/j.compstruct.2019.111803_b0115 article-title: Nonoxidative conversion of methane in a dielectric barrier discharge reactor: prediction of reaction performance based on neural network model publication-title: J Phys Chem C doi: 10.1021/jp502557s – volume: 26 start-page: 237 year: 2015 ident: 10.1016/j.compstruct.2019.111803_b0145 article-title: ANN and multiple regression method-based modeling of cuttingforces in orthogonal machining of AISI 316L stainless steel publication-title: Neural Comput Appl doi: 10.1007/s00521-014-1721-y – volume: 50 start-page: 882 issue: 10 year: 2010 ident: 10.1016/j.compstruct.2019.111803_b0120 article-title: Prediction of cutting forces in helical end milling fiber reinforced polymers publication-title: Int J MachTools Manuf doi: 10.1016/j.ijmachtools.2010.06.005 – volume: 8 start-page: 198 issue: 1/2 year: 2010 ident: 10.1016/j.compstruct.2019.111803_b0140 article-title: Modelling of cutting forces as a function of cutting parameters in milling process using regression analysis and artificial neural network publication-title: Int J Mach Mach Mater – volume: 124 start-page: 207 year: 2017 ident: 10.1016/j.compstruct.2019.111803_b0085 article-title: A new analytical critical thrust force model for delamination analysis of laminated composites during drilling operation publication-title: Compos Part B-Eng doi: 10.1016/j.compositesb.2017.05.039 – volume: 29 start-page: 1768 year: 2008 ident: 10.1016/j.compstruct.2019.111803_b0020 article-title: Delamination analysis in high speed drilling of carbon fiber reinforced plastics (CFRP) using artificial neural network model publication-title: Mater Des doi: 10.1016/j.matdes.2008.03.014 – volume: 209 start-page: 337 year: 2019 ident: 10.1016/j.compstruct.2019.111803_b0005 article-title: A theoretical model for predicting the CFRP drilling-countersinking thrust force of stacks publication-title: Compo Struct doi: 10.1016/j.compstruct.2018.10.107 – volume: 158 start-page: 210 year: 2016 ident: 10.1016/j.compstruct.2019.111803_b0165 article-title: A useful tool for computation and interpretation of trading-off solutions through Pareto front in the field of experimental designs for mixtures publication-title: Chemom Intell Lab Syst doi: 10.1016/j.chemolab.2016.09.007 – volume: 37 start-page: 1097 issue: 8 year: 1997 ident: 10.1016/j.compstruct.2019.111803_b0070 article-title: Some experimental investigations in the drilling of carbon fiber-reinforced plastic (CFRP) composite laminates publication-title: Int J Mach Tools Manuf doi: 10.1016/S0890-6955(96)00095-8 – volume: 189 start-page: 143 year: 2007 ident: 10.1016/j.compstruct.2019.111803_b0135 article-title: An ANN approach for predicting subsurface residual stresses and the desired cutting conditions during hard turning publication-title: J Mater Process Technol doi: 10.1016/j.jmatprotec.2007.01.016 – volume: 37 start-page: 641 year: 2008 ident: 10.1016/j.compstruct.2019.111803_b0150 article-title: Comparing statistical models and artificial neural networks on predicting the tool wear in hard machining D2 AISI steel publication-title: Int J Adv Manuf Technol doi: 10.1007/s00170-007-0999-7 – volume: 148 start-page: 19 year: 2016 ident: 10.1016/j.compstruct.2019.111803_b0095 article-title: Critical thrust and feed prediction models in drilling of composite laminates publication-title: Compos Struct doi: 10.1016/j.compstruct.2016.03.059 – volume: 97 start-page: 857 year: 2018 ident: 10.1016/j.compstruct.2019.111803_b0025 article-title: Influence of machining parameters and tool structure on cutting force and hole wall damage in drilling CFRP with stepped drills publication-title: Int J Adv Manuf Technol doi: 10.1007/s00170-018-1981-2 – volume: 45 start-page: 1286 issue: 5 year: 2012 ident: 10.1016/j.compstruct.2019.111803_b0040 article-title: Application of grey fuzzy logic for the optimization of drilling parameters for CFRP composites with multiple performance characteristics publication-title: Measurement doi: 10.1016/j.measurement.2012.01.008 – volume: 155 start-page: 173 year: 2016 ident: 10.1016/j.compstruct.2019.111803_b0010 article-title: A comparative study on tool wear and laminate damage in drilling of carbon-fiber reinforced polymers (CFRP) publication-title: Compos Struct doi: 10.1016/j.compstruct.2016.08.004 – volume: 74 start-page: 96 year: 2017 ident: 10.1016/j.compstruct.2019.111803_b0160 article-title: Multi-objective optimization: a method for selecting the optimal solution from Pareto non-inferior solutions publication-title: Expert Syst Appl doi: 10.1016/j.eswa.2017.01.004 – volume: 20 start-page: 53 year: 1987 ident: 10.1016/j.compstruct.2019.111803_b0205 article-title: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis publication-title: J Comput Appl Math doi: 10.1016/0377-0427(87)90125-7 – volume: 130 start-page: 265 year: 2019 ident: 10.1016/j.compstruct.2019.111803_b0195 article-title: A hierarchical prediction model for lane-changes based on combination of fuzzy C-means and adaptive neural network publication-title: Expert Syst Appl doi: 10.1016/j.eswa.2019.04.032 – volume: 262 start-page: 521 year: 2018 ident: 10.1016/j.compstruct.2019.111803_b0105 article-title: A novel approach to predict the delamination factor for dry and cryogenic drilling of CFRP publication-title: J Mater Process Technol doi: 10.1016/j.jmatprotec.2018.07.026 – volume: 205 start-page: 16 year: 2008 ident: 10.1016/j.compstruct.2019.111803_b0125 article-title: Investigations into the effect of cutting conditions on surface roughness in turning of free machining steel by ANN models publication-title: J Mater Process Technol doi: 10.1016/j.jmatprotec.2007.11.082 – volume: 9 start-page: 1609 issue: 10 year: 2018 ident: 10.1016/j.compstruct.2019.111803_b0200 article-title: Fuzzy c-means clustering-based mating restriction for multiobjective optimization publication-title: Int J Mach Learn Cyber doi: 10.1007/s13042-017-0668-6 – volume: 110 start-page: 319 year: 2017 ident: 10.1016/j.compstruct.2019.111803_b0030 article-title: Optimisation of process parameters for the orbital and conventional drilling of uni-directional carbon fibre-reinforced polymers (UD-CFRP) publication-title: Measurement doi: 10.1016/j.measurement.2017.07.007 – start-page: 914 year: 2003 ident: 10.1016/j.compstruct.2019.111803_b0185 article-title: An efficient evolutionary multi-objective optimization algorithm – volume: 240 start-page: 332 year: 2017 ident: 10.1016/j.compstruct.2019.111803_b0090 article-title: New analytical model for delamination of CFRP during drilling publication-title: J Mater Process Technol doi: 10.1016/j.jmatprotec.2016.10.007 |
| SSID | ssj0008411 |
| Score | 2.4819198 |
| Snippet | A full factorial experiment is performed for the conventional dry drilling of CFRP with spindle speed, feed rate and point angle as drilling parameters,... |
| SourceID | crossref elsevier |
| SourceType | Enrichment Source Index Database Publisher |
| StartPage | 111803 |
| SubjectTerms | Artificial neural network (ANN) Carbon fiber reinforced polymer Fuzzy C-means clustering algorithm Multi-objective optimization Non-dominated Sorting Genetic Algorithm (NSGA-II) |
| Title | Multi-objective optimization of CFRP drilling parameters with a hybrid method integrating the ANN, NSGA-II and fuzzy C-means |
| URI | https://dx.doi.org/10.1016/j.compstruct.2019.111803 |
| Volume | 235 |
| WOSCitedRecordID | wos000508631700048&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D |
| hasFullText | 1 |
| inHoldings | 1 |
| isFullTextHit | |
| isPrint | |
| journalDatabaseRights | – providerCode: PRVESC databaseName: Elsevier SD Freedom Collection Journals 2021 customDbUrl: eissn: 1879-1085 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0008411 issn: 0263-8223 databaseCode: AIEXJ dateStart: 19950101 isFulltext: true titleUrlDefault: https://www.sciencedirect.com providerName: Elsevier |
| link | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwtV1bb9MwFLbQxgM8IK5i3OQH3oql1IkTWzxVaINOqBpsiL5F8SWsFU2qdkNj4sdzTuxcBJMYQrxEVVTXUb-vx8en3_lMyMsy1ZE0WcZg_1OwRKsx07GImUjRa50nQnuf2ffZbCbnc3UUZGPb5jiBrKrkxYVa_1eo4R6Aja2zfwF396FwA14D6HAF2OF6LeCbllpW66UPZaMagsIqdFs24ouDj0cju1l4M260_l6hJKZtcxudfscmrnC0dGcn0XZVTWaNLmB2_HbCptPmr4fy_PISAgtbuSKU_lrnA4g1qAlDE1t0qT3f9ILFz6FO_WFAz0Mv3J0vihqLL1-GFQnYfnaSLF8ma1tlel3StnF4jRlkIz6aOR9tZaYYtj8MwzH39iW_hXZfZVgiMmv_1CjMUxjzZRT3y1knMjzGKXHGMRZtFIeFepdnQkHs251M9-eH3Yotk-ac5u4Rg-LL6wCvnu_qNGaQmpzcJXfCnoJOPBfukRuuuk9uD5wmH5Afv7CCDllB65IiK2jLCtqzgiIraEE9K6hnBR2wggIrKLDiFQ2coMAJ2nCCBk48JJ8O9k_evGPh4A1mIMSfsZIrW7pUcM0NZJCOc6OcUyXHbDWJI15EwrqyEErbzEgbOyWkTotxDNk35riPyE5VV-4xodxYodGm0sU2cVEsnYUU0lg0YEit0Xska7_H3ARXejwc5Wveyg-XeY9AjgjkHoE9Mu5Grr0zyzXGvG6hykOG6TPHHFj2x9FP_mn0U3Kr_7E8IzvwBvec3DTfzhbbzYtAyZ-q6ac- |
| linkProvider | Elsevier |
| openUrl | ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=Multi-objective+optimization+of+CFRP+drilling+parameters+with+a+hybrid+method+integrating+the+ANN%2C+NSGA-II+and+fuzzy+C-means&rft.jtitle=Composite+structures&rft.au=Wang%2C+Qian&rft.au=Jia%2C+Xiaoliang&rft.date=2020-03-01&rft.pub=Elsevier+Ltd&rft.issn=0263-8223&rft.eissn=1879-1085&rft.volume=235&rft_id=info:doi/10.1016%2Fj.compstruct.2019.111803&rft.externalDocID=S0263822319330922 |
| thumbnail_l | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=0263-8223&client=summon |
| thumbnail_m | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=0263-8223&client=summon |
| thumbnail_s | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=0263-8223&client=summon |