Multi objective prediction and optimization of control parameters in the milling of aluminium hybrid metal matrix composites using ANN and Taguchi -grey relational analysis Article Swipe
S. Ajith Arul Daniel
,
R. Pugazhenthi
,
R. Kumar
,
VijayAnanth Suyamburajan
·
YOU?
·
· 2019
· Open Access
·
· DOI: https://doi.org/10.1016/j.dt.2019.01.001
YOU?
·
· 2019
· Open Access
·
· DOI: https://doi.org/10.1016/j.dt.2019.01.001
This study aims to optimize the input parameters such as mass fraction and particle size of SiC along with depth of cut, feed and cutting speed in the milling of Al5059/SiC/MoS2. The hybrid metal matrix composites are generally fabricated by reinforcing of different sizes (10, 20, 40 μm) of SiC with aluminium at a different levels (5%,10% &15%) whereas the MoS2 addition is fixed as 2%. The effect of each control factor on response variables are analyzed through Taguchi S/N ratio method. Also, the most significant method for prediction of response parameters is satisfied by ANN model than the regression model. Analysis of variance (ANOVA) results envisage that mass fraction of SiC, feed rate is the most domineering factor on response variable. Keywords: Silicon carbide, Temperature, Surface roughness, Cutting forces, Artificial neural network, Grey relational analysis
Related Topics
Concepts
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1016/j.dt.2019.01.001
- OA Status
- diamond
- Cited By
- 123
- References
- 44
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W2909978788
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W2909978788Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.1016/j.dt.2019.01.001Digital Object Identifier
- Title
-
Multi objective prediction and optimization of control parameters in the milling of aluminium hybrid metal matrix composites using ANN and Taguchi -grey relational analysisWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2019Year of publication
- Publication date
-
2019-01-14Full publication date if available
- Authors
-
S. Ajith Arul Daniel, R. Pugazhenthi, R. Kumar, VijayAnanth SuyamburajanList of authors in order
- Landing page
-
https://doi.org/10.1016/j.dt.2019.01.001Publisher landing page
- Open access
-
YesWhether a free full text is available
- OA status
-
diamondOpen access status per OpenAlex
- OA URL
-
https://doi.org/10.1016/j.dt.2019.01.001Direct OA link when available
- Concepts
-
Taguchi methods, Aluminium, Materials science, Grey relational analysis, Mass fraction, Composite material, Matrix (chemical analysis), Orthogonal array, Metal matrix composite, Mathematics, StatisticsTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
123Total citation count in OpenAlex
- Citations by year (recent)
-
2025: 9, 2024: 25, 2023: 21, 2022: 28, 2021: 20Per-year citation counts (last 5 years)
- References (count)
-
44Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
Full payload
| id | https://openalex.org/W2909978788 |
|---|---|
| doi | https://doi.org/10.1016/j.dt.2019.01.001 |
| ids.doi | https://doi.org/10.1016/j.dt.2019.01.001 |
| ids.mag | 2909978788 |
| ids.openalex | https://openalex.org/W2909978788 |
| fwci | 7.74196133 |
| type | article |
| title | Multi objective prediction and optimization of control parameters in the milling of aluminium hybrid metal matrix composites using ANN and Taguchi -grey relational analysis |
| biblio.issue | 4 |
| biblio.volume | 15 |
| biblio.last_page | 556 |
| biblio.first_page | 545 |
| topics[0].id | https://openalex.org/T11451 |
| topics[0].field.id | https://openalex.org/fields/22 |
| topics[0].field.display_name | Engineering |
| topics[0].score | 0.9994999766349792 |
| topics[0].domain.id | https://openalex.org/domains/3 |
| topics[0].domain.display_name | Physical Sciences |
| topics[0].subfield.id | https://openalex.org/subfields/2208 |
| topics[0].subfield.display_name | Electrical and Electronic Engineering |
| topics[0].display_name | Advanced Machining and Optimization Techniques |
| topics[1].id | https://openalex.org/T10188 |
| topics[1].field.id | https://openalex.org/fields/22 |
| topics[1].field.display_name | Engineering |
| topics[1].score | 0.9993000030517578 |
| topics[1].domain.id | https://openalex.org/domains/3 |
| topics[1].domain.display_name | Physical Sciences |
| topics[1].subfield.id | https://openalex.org/subfields/2210 |
| topics[1].subfield.display_name | Mechanical Engineering |
| topics[1].display_name | Advanced machining processes and optimization |
| topics[2].id | https://openalex.org/T10717 |
| topics[2].field.id | https://openalex.org/fields/22 |
| topics[2].field.display_name | Engineering |
| topics[2].score | 0.9990000128746033 |
| topics[2].domain.id | https://openalex.org/domains/3 |
| topics[2].domain.display_name | Physical Sciences |
| topics[2].subfield.id | https://openalex.org/subfields/2210 |
| topics[2].subfield.display_name | Mechanical Engineering |
| topics[2].display_name | Aluminum Alloys Composites Properties |
| is_xpac | False |
| apc_list | |
| apc_paid | |
| concepts[0].id | https://openalex.org/C83469408 |
| concepts[0].level | 2 |
| concepts[0].score | 0.9062471389770508 |
| concepts[0].wikidata | https://www.wikidata.org/wiki/Q2036525 |
| concepts[0].display_name | Taguchi methods |
| concepts[1].id | https://openalex.org/C513153333 |
| concepts[1].level | 2 |
| concepts[1].score | 0.7247129678726196 |
| concepts[1].wikidata | https://www.wikidata.org/wiki/Q663 |
| concepts[1].display_name | Aluminium |
| concepts[2].id | https://openalex.org/C192562407 |
| concepts[2].level | 0 |
| concepts[2].score | 0.684796154499054 |
| concepts[2].wikidata | https://www.wikidata.org/wiki/Q228736 |
| concepts[2].display_name | Materials science |
| concepts[3].id | https://openalex.org/C64734493 |
| concepts[3].level | 2 |
| concepts[3].score | 0.6247615814208984 |
| concepts[3].wikidata | https://www.wikidata.org/wiki/Q5608296 |
| concepts[3].display_name | Grey relational analysis |
| concepts[4].id | https://openalex.org/C116628846 |
| concepts[4].level | 2 |
| concepts[4].score | 0.618652880191803 |
| concepts[4].wikidata | https://www.wikidata.org/wiki/Q899138 |
| concepts[4].display_name | Mass fraction |
| concepts[5].id | https://openalex.org/C159985019 |
| concepts[5].level | 1 |
| concepts[5].score | 0.5416624546051025 |
| concepts[5].wikidata | https://www.wikidata.org/wiki/Q181790 |
| concepts[5].display_name | Composite material |
| concepts[6].id | https://openalex.org/C106487976 |
| concepts[6].level | 2 |
| concepts[6].score | 0.5088603496551514 |
| concepts[6].wikidata | https://www.wikidata.org/wiki/Q685816 |
| concepts[6].display_name | Matrix (chemical analysis) |
| concepts[7].id | https://openalex.org/C42632107 |
| concepts[7].level | 3 |
| concepts[7].score | 0.4975321590900421 |
| concepts[7].wikidata | https://www.wikidata.org/wiki/Q2031860 |
| concepts[7].display_name | Orthogonal array |
| concepts[8].id | https://openalex.org/C2777925586 |
| concepts[8].level | 3 |
| concepts[8].score | 0.457630455493927 |
| concepts[8].wikidata | https://www.wikidata.org/wiki/Q1756475 |
| concepts[8].display_name | Metal matrix composite |
| concepts[9].id | https://openalex.org/C33923547 |
| concepts[9].level | 0 |
| concepts[9].score | 0.21673384308815002 |
| concepts[9].wikidata | https://www.wikidata.org/wiki/Q395 |
| concepts[9].display_name | Mathematics |
| concepts[10].id | https://openalex.org/C105795698 |
| concepts[10].level | 1 |
| concepts[10].score | 0.14222338795661926 |
| concepts[10].wikidata | https://www.wikidata.org/wiki/Q12483 |
| concepts[10].display_name | Statistics |
| keywords[0].id | https://openalex.org/keywords/taguchi-methods |
| keywords[0].score | 0.9062471389770508 |
| keywords[0].display_name | Taguchi methods |
| keywords[1].id | https://openalex.org/keywords/aluminium |
| keywords[1].score | 0.7247129678726196 |
| keywords[1].display_name | Aluminium |
| keywords[2].id | https://openalex.org/keywords/materials-science |
| keywords[2].score | 0.684796154499054 |
| keywords[2].display_name | Materials science |
| keywords[3].id | https://openalex.org/keywords/grey-relational-analysis |
| keywords[3].score | 0.6247615814208984 |
| keywords[3].display_name | Grey relational analysis |
| keywords[4].id | https://openalex.org/keywords/mass-fraction |
| keywords[4].score | 0.618652880191803 |
| keywords[4].display_name | Mass fraction |
| keywords[5].id | https://openalex.org/keywords/composite-material |
| keywords[5].score | 0.5416624546051025 |
| keywords[5].display_name | Composite material |
| keywords[6].id | https://openalex.org/keywords/matrix |
| keywords[6].score | 0.5088603496551514 |
| keywords[6].display_name | Matrix (chemical analysis) |
| keywords[7].id | https://openalex.org/keywords/orthogonal-array |
| keywords[7].score | 0.4975321590900421 |
| keywords[7].display_name | Orthogonal array |
| keywords[8].id | https://openalex.org/keywords/metal-matrix-composite |
| keywords[8].score | 0.457630455493927 |
| keywords[8].display_name | Metal matrix composite |
| keywords[9].id | https://openalex.org/keywords/mathematics |
| keywords[9].score | 0.21673384308815002 |
| keywords[9].display_name | Mathematics |
| keywords[10].id | https://openalex.org/keywords/statistics |
| keywords[10].score | 0.14222338795661926 |
| keywords[10].display_name | Statistics |
| language | en |
| locations[0].id | doi:10.1016/j.dt.2019.01.001 |
| locations[0].is_oa | True |
| locations[0].source.id | https://openalex.org/S2736621015 |
| locations[0].source.issn | 2096-3459, 2214-9147 |
| locations[0].source.type | journal |
| locations[0].source.is_oa | True |
| locations[0].source.issn_l | 2096-3459 |
| locations[0].source.is_core | True |
| locations[0].source.is_in_doaj | True |
| locations[0].source.display_name | Defence Technology |
| locations[0].source.host_organization | https://openalex.org/P4310320990 |
| locations[0].source.host_organization_name | Elsevier BV |
| locations[0].source.host_organization_lineage | https://openalex.org/P4310320990 |
| locations[0].source.host_organization_lineage_names | Elsevier BV |
| locations[0].license | cc-by-nc-nd |
| locations[0].pdf_url | |
| locations[0].version | publishedVersion |
| locations[0].raw_type | journal-article |
| locations[0].license_id | https://openalex.org/licenses/cc-by-nc-nd |
| locations[0].is_accepted | True |
| locations[0].is_published | True |
| locations[0].raw_source_name | Defence Technology |
| locations[0].landing_page_url | https://doi.org/10.1016/j.dt.2019.01.001 |
| locations[1].id | pmh:oai:doaj.org/article:96031dfac29c46ea8c73da908902b7f3 |
| locations[1].is_oa | False |
| locations[1].source.id | https://openalex.org/S4306401280 |
| locations[1].source.issn | |
| locations[1].source.type | repository |
| locations[1].source.is_oa | False |
| locations[1].source.issn_l | |
| locations[1].source.is_core | False |
| locations[1].source.is_in_doaj | False |
| locations[1].source.display_name | DOAJ (DOAJ: Directory of Open Access Journals) |
| locations[1].source.host_organization | |
| locations[1].source.host_organization_name | |
| locations[1].license | |
| locations[1].pdf_url | |
| locations[1].version | submittedVersion |
| locations[1].raw_type | article |
| locations[1].license_id | |
| locations[1].is_accepted | False |
| locations[1].is_published | False |
| locations[1].raw_source_name | Defence Technology, Vol 15, Iss 4, Pp 545-556 (2019) |
| locations[1].landing_page_url | https://doaj.org/article/96031dfac29c46ea8c73da908902b7f3 |
| indexed_in | crossref, doaj |
| authorships[0].author.id | https://openalex.org/A5003263021 |
| authorships[0].author.orcid | |
| authorships[0].author.display_name | S. Ajith Arul Daniel |
| authorships[0].countries | IN |
| authorships[0].affiliations[0].institution_ids | https://openalex.org/I138876546 |
| authorships[0].affiliations[0].raw_affiliation_string | Department of Mechanical Engineering, Vels Institute of Science, Technology and Advanced Studies, Chennai, Tamilnadu, 600117, India |
| authorships[0].institutions[0].id | https://openalex.org/I138876546 |
| authorships[0].institutions[0].ror | https://ror.org/00tscx035 |
| authorships[0].institutions[0].type | education |
| authorships[0].institutions[0].lineage | https://openalex.org/I138876546 |
| authorships[0].institutions[0].country_code | IN |
| authorships[0].institutions[0].display_name | Vels University |
| authorships[0].author_position | first |
| authorships[0].raw_author_name | S. Ajith Arul Daniel |
| authorships[0].is_corresponding | False |
| authorships[0].raw_affiliation_strings | Department of Mechanical Engineering, Vels Institute of Science, Technology and Advanced Studies, Chennai, Tamilnadu, 600117, India |
| authorships[1].author.id | https://openalex.org/A5084973555 |
| authorships[1].author.orcid | |
| authorships[1].author.display_name | R. Pugazhenthi |
| authorships[1].countries | IN |
| authorships[1].affiliations[0].institution_ids | https://openalex.org/I138876546 |
| authorships[1].affiliations[0].raw_affiliation_string | Department of Mechanical Engineering, Vels Institute of Science, Technology and Advanced Studies, Chennai, Tamilnadu, 600117, India |
| authorships[1].institutions[0].id | https://openalex.org/I138876546 |
| authorships[1].institutions[0].ror | https://ror.org/00tscx035 |
| authorships[1].institutions[0].type | education |
| authorships[1].institutions[0].lineage | https://openalex.org/I138876546 |
| authorships[1].institutions[0].country_code | IN |
| authorships[1].institutions[0].display_name | Vels University |
| authorships[1].author_position | middle |
| authorships[1].raw_author_name | R. Pugazhenthi |
| authorships[1].is_corresponding | False |
| authorships[1].raw_affiliation_strings | Department of Mechanical Engineering, Vels Institute of Science, Technology and Advanced Studies, Chennai, Tamilnadu, 600117, India |
| authorships[2].author.id | https://openalex.org/A5101477525 |
| authorships[2].author.orcid | https://orcid.org/0000-0002-7910-9142 |
| authorships[2].author.display_name | R. Kumar |
| authorships[2].countries | IN |
| authorships[2].affiliations[0].institution_ids | https://openalex.org/I138876546 |
| authorships[2].affiliations[0].raw_affiliation_string | Department of Mechanical Engineering, Vels Institute of Science, Technology and Advanced Studies, Chennai, Tamilnadu, 600117, India |
| authorships[2].institutions[0].id | https://openalex.org/I138876546 |
| authorships[2].institutions[0].ror | https://ror.org/00tscx035 |
| authorships[2].institutions[0].type | education |
| authorships[2].institutions[0].lineage | https://openalex.org/I138876546 |
| authorships[2].institutions[0].country_code | IN |
| authorships[2].institutions[0].display_name | Vels University |
| authorships[2].author_position | middle |
| authorships[2].raw_author_name | R. Kumar |
| authorships[2].is_corresponding | True |
| authorships[2].raw_affiliation_strings | Department of Mechanical Engineering, Vels Institute of Science, Technology and Advanced Studies, Chennai, Tamilnadu, 600117, India |
| authorships[3].author.id | https://openalex.org/A5000542683 |
| authorships[3].author.orcid | https://orcid.org/0000-0003-3883-5938 |
| authorships[3].author.display_name | VijayAnanth Suyamburajan |
| authorships[3].countries | IN |
| authorships[3].affiliations[0].institution_ids | https://openalex.org/I138876546 |
| authorships[3].affiliations[0].raw_affiliation_string | Department of Mechanical Engineering, Vels Institute of Science, Technology and Advanced Studies, Chennai, Tamilnadu, 600117, India |
| authorships[3].institutions[0].id | https://openalex.org/I138876546 |
| authorships[3].institutions[0].ror | https://ror.org/00tscx035 |
| authorships[3].institutions[0].type | education |
| authorships[3].institutions[0].lineage | https://openalex.org/I138876546 |
| authorships[3].institutions[0].country_code | IN |
| authorships[3].institutions[0].display_name | Vels University |
| authorships[3].author_position | last |
| authorships[3].raw_author_name | S. Vijayananth |
| authorships[3].is_corresponding | False |
| authorships[3].raw_affiliation_strings | Department of Mechanical Engineering, Vels Institute of Science, Technology and Advanced Studies, Chennai, Tamilnadu, 600117, India |
| has_content.pdf | False |
| has_content.grobid_xml | False |
| is_paratext | False |
| open_access.is_oa | True |
| open_access.oa_url | https://doi.org/10.1016/j.dt.2019.01.001 |
| open_access.oa_status | diamond |
| open_access.any_repository_has_fulltext | False |
| created_date | 2025-10-10T00:00:00 |
| display_name | Multi objective prediction and optimization of control parameters in the milling of aluminium hybrid metal matrix composites using ANN and Taguchi -grey relational analysis |
| has_fulltext | False |
| is_retracted | False |
| updated_date | 2025-11-06T03:46:38.306776 |
| primary_topic.id | https://openalex.org/T11451 |
| primary_topic.field.id | https://openalex.org/fields/22 |
| primary_topic.field.display_name | Engineering |
| primary_topic.score | 0.9994999766349792 |
| primary_topic.domain.id | https://openalex.org/domains/3 |
| primary_topic.domain.display_name | Physical Sciences |
| primary_topic.subfield.id | https://openalex.org/subfields/2208 |
| primary_topic.subfield.display_name | Electrical and Electronic Engineering |
| primary_topic.display_name | Advanced Machining and Optimization Techniques |
| related_works | https://openalex.org/W3089885773, https://openalex.org/W2072844563, https://openalex.org/W3043200669, https://openalex.org/W2611443241, https://openalex.org/W2036395833, https://openalex.org/W2798254176, https://openalex.org/W3009898605, https://openalex.org/W2901256284, https://openalex.org/W3171345323, https://openalex.org/W3193005141 |
| cited_by_count | 123 |
| counts_by_year[0].year | 2025 |
| counts_by_year[0].cited_by_count | 9 |
| counts_by_year[1].year | 2024 |
| counts_by_year[1].cited_by_count | 25 |
| counts_by_year[2].year | 2023 |
| counts_by_year[2].cited_by_count | 21 |
| counts_by_year[3].year | 2022 |
| counts_by_year[3].cited_by_count | 28 |
| counts_by_year[4].year | 2021 |
| counts_by_year[4].cited_by_count | 20 |
| counts_by_year[5].year | 2020 |
| counts_by_year[5].cited_by_count | 17 |
| counts_by_year[6].year | 2019 |
| counts_by_year[6].cited_by_count | 3 |
| locations_count | 2 |
| best_oa_location.id | doi:10.1016/j.dt.2019.01.001 |
| best_oa_location.is_oa | True |
| best_oa_location.source.id | https://openalex.org/S2736621015 |
| best_oa_location.source.issn | 2096-3459, 2214-9147 |
| best_oa_location.source.type | journal |
| best_oa_location.source.is_oa | True |
| best_oa_location.source.issn_l | 2096-3459 |
| best_oa_location.source.is_core | True |
| best_oa_location.source.is_in_doaj | True |
| best_oa_location.source.display_name | Defence Technology |
| best_oa_location.source.host_organization | https://openalex.org/P4310320990 |
| best_oa_location.source.host_organization_name | Elsevier BV |
| best_oa_location.source.host_organization_lineage | https://openalex.org/P4310320990 |
| best_oa_location.source.host_organization_lineage_names | Elsevier BV |
| best_oa_location.license | cc-by-nc-nd |
| best_oa_location.pdf_url | |
| best_oa_location.version | publishedVersion |
| best_oa_location.raw_type | journal-article |
| best_oa_location.license_id | https://openalex.org/licenses/cc-by-nc-nd |
| best_oa_location.is_accepted | True |
| best_oa_location.is_published | True |
| best_oa_location.raw_source_name | Defence Technology |
| best_oa_location.landing_page_url | https://doi.org/10.1016/j.dt.2019.01.001 |
| primary_location.id | doi:10.1016/j.dt.2019.01.001 |
| primary_location.is_oa | True |
| primary_location.source.id | https://openalex.org/S2736621015 |
| primary_location.source.issn | 2096-3459, 2214-9147 |
| primary_location.source.type | journal |
| primary_location.source.is_oa | True |
| primary_location.source.issn_l | 2096-3459 |
| primary_location.source.is_core | True |
| primary_location.source.is_in_doaj | True |
| primary_location.source.display_name | Defence Technology |
| primary_location.source.host_organization | https://openalex.org/P4310320990 |
| primary_location.source.host_organization_name | Elsevier BV |
| primary_location.source.host_organization_lineage | https://openalex.org/P4310320990 |
| primary_location.source.host_organization_lineage_names | Elsevier BV |
| primary_location.license | cc-by-nc-nd |
| primary_location.pdf_url | |
| primary_location.version | publishedVersion |
| primary_location.raw_type | journal-article |
| primary_location.license_id | https://openalex.org/licenses/cc-by-nc-nd |
| primary_location.is_accepted | True |
| primary_location.is_published | True |
| primary_location.raw_source_name | Defence Technology |
| primary_location.landing_page_url | https://doi.org/10.1016/j.dt.2019.01.001 |
| publication_date | 2019-01-14 |
| publication_year | 2019 |
| referenced_works | https://openalex.org/W2013377846, https://openalex.org/W2042055770, https://openalex.org/W2013777644, https://openalex.org/W2003870912, https://openalex.org/W2005585791, https://openalex.org/W2071577452, https://openalex.org/W6844030724, https://openalex.org/W2025973944, https://openalex.org/W2260439501, https://openalex.org/W6675535115, https://openalex.org/W2029011826, https://openalex.org/W2013783199, https://openalex.org/W2153467000, https://openalex.org/W2806112502, https://openalex.org/W6644469231, https://openalex.org/W2041295062, https://openalex.org/W2011404443, https://openalex.org/W2030304724, https://openalex.org/W2612689053, https://openalex.org/W6983607025, https://openalex.org/W2795357276, https://openalex.org/W2148303695, https://openalex.org/W2082318215, https://openalex.org/W2048858233, https://openalex.org/W2758909008, https://openalex.org/W263293068, https://openalex.org/W2059512033, https://openalex.org/W2163831974, https://openalex.org/W2263867451, https://openalex.org/W6695319244, https://openalex.org/W6728840421, https://openalex.org/W1967896897, https://openalex.org/W3098189211, https://openalex.org/W1581808154, https://openalex.org/W3143590765, https://openalex.org/W4298282998, https://openalex.org/W4285719527, https://openalex.org/W2085440494, https://openalex.org/W2105043403, https://openalex.org/W2970815070, https://openalex.org/W1977408846, https://openalex.org/W2341933480, https://openalex.org/W2278076336, https://openalex.org/W2533791227 |
| referenced_works_count | 44 |
| abstract_inverted_index.a | 53 |
| abstract_inverted_index.40 | 46 |
| abstract_inverted_index.as | 9, 64 |
| abstract_inverted_index.at | 52 |
| abstract_inverted_index.by | 39, 94 |
| abstract_inverted_index.in | 26 |
| abstract_inverted_index.is | 62, 92, 114 |
| abstract_inverted_index.of | 15, 20, 29, 41, 48, 68, 89, 102, 110 |
| abstract_inverted_index.on | 72, 119 |
| abstract_inverted_index.to | 3 |
| abstract_inverted_index.2%. | 65 |
| abstract_inverted_index.20, | 45 |
| abstract_inverted_index.ANN | 95 |
| abstract_inverted_index.S/N | 79 |
| abstract_inverted_index.SiC | 16, 49 |
| abstract_inverted_index.The | 31, 66 |
| abstract_inverted_index.and | 12, 23 |
| abstract_inverted_index.are | 36, 75 |
| abstract_inverted_index.for | 87 |
| abstract_inverted_index.the | 5, 27, 59, 83, 98, 115 |
| abstract_inverted_index.(10, | 44 |
| abstract_inverted_index.Grey | 133 |
| abstract_inverted_index.MoS2 | 60 |
| abstract_inverted_index.SiC, | 111 |
| abstract_inverted_index.This | 0 |
| abstract_inverted_index.aims | 2 |
| abstract_inverted_index.cut, | 21 |
| abstract_inverted_index.each | 69 |
| abstract_inverted_index.feed | 22, 112 |
| abstract_inverted_index.mass | 10, 108 |
| abstract_inverted_index.most | 84, 116 |
| abstract_inverted_index.rate | 113 |
| abstract_inverted_index.size | 14 |
| abstract_inverted_index.such | 8 |
| abstract_inverted_index.than | 97 |
| abstract_inverted_index.that | 107 |
| abstract_inverted_index.with | 18, 50 |
| abstract_inverted_index.μm) | 47 |
| abstract_inverted_index.&15%) | 57 |
| abstract_inverted_index.Also, | 82 |
| abstract_inverted_index.along | 17 |
| abstract_inverted_index.depth | 19 |
| abstract_inverted_index.fixed | 63 |
| abstract_inverted_index.input | 6 |
| abstract_inverted_index.metal | 33 |
| abstract_inverted_index.model | 96 |
| abstract_inverted_index.ratio | 80 |
| abstract_inverted_index.sizes | 43 |
| abstract_inverted_index.speed | 25 |
| abstract_inverted_index.study | 1 |
| abstract_inverted_index.effect | 67 |
| abstract_inverted_index.factor | 71, 118 |
| abstract_inverted_index.hybrid | 32 |
| abstract_inverted_index.levels | 55 |
| abstract_inverted_index.matrix | 34 |
| abstract_inverted_index.method | 86 |
| abstract_inverted_index.model. | 100 |
| abstract_inverted_index.neural | 131 |
| abstract_inverted_index.(5%,10% | 56 |
| abstract_inverted_index.(ANOVA) | 104 |
| abstract_inverted_index.Cutting | 128 |
| abstract_inverted_index.Silicon | 123 |
| abstract_inverted_index.Surface | 126 |
| abstract_inverted_index.Taguchi | 78 |
| abstract_inverted_index.control | 70 |
| abstract_inverted_index.cutting | 24 |
| abstract_inverted_index.forces, | 129 |
| abstract_inverted_index.method. | 81 |
| abstract_inverted_index.milling | 28 |
| abstract_inverted_index.results | 105 |
| abstract_inverted_index.through | 77 |
| abstract_inverted_index.whereas | 58 |
| abstract_inverted_index.Analysis | 101 |
| abstract_inverted_index.addition | 61 |
| abstract_inverted_index.analysis | 135 |
| abstract_inverted_index.analyzed | 76 |
| abstract_inverted_index.carbide, | 124 |
| abstract_inverted_index.envisage | 106 |
| abstract_inverted_index.fraction | 11, 109 |
| abstract_inverted_index.network, | 132 |
| abstract_inverted_index.optimize | 4 |
| abstract_inverted_index.particle | 13 |
| abstract_inverted_index.response | 73, 90, 120 |
| abstract_inverted_index.variance | 103 |
| abstract_inverted_index.Keywords: | 122 |
| abstract_inverted_index.aluminium | 51 |
| abstract_inverted_index.different | 42, 54 |
| abstract_inverted_index.generally | 37 |
| abstract_inverted_index.satisfied | 93 |
| abstract_inverted_index.variable. | 121 |
| abstract_inverted_index.variables | 74 |
| abstract_inverted_index.Artificial | 130 |
| abstract_inverted_index.composites | 35 |
| abstract_inverted_index.fabricated | 38 |
| abstract_inverted_index.parameters | 7, 91 |
| abstract_inverted_index.prediction | 88 |
| abstract_inverted_index.regression | 99 |
| abstract_inverted_index.relational | 134 |
| abstract_inverted_index.roughness, | 127 |
| abstract_inverted_index.domineering | 117 |
| abstract_inverted_index.reinforcing | 40 |
| abstract_inverted_index.significant | 85 |
| abstract_inverted_index.Temperature, | 125 |
| abstract_inverted_index.Al5059/SiC/MoS2. | 30 |
| cited_by_percentile_year.max | 100 |
| cited_by_percentile_year.min | 96 |
| corresponding_author_ids | https://openalex.org/A5101477525 |
| countries_distinct_count | 1 |
| institutions_distinct_count | 4 |
| corresponding_institution_ids | https://openalex.org/I138876546 |
| citation_normalized_percentile.value | 0.98119157 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | True |