Predicting the solidification time of low pressure die castings using geometric feature-based machine learning metamodels Article Swipe

View

Tobias Rosnitschek , Maximilian Erber , Bettina Alber-Laukant , Christoph Hartmann , Wolfram Volk , Frank Rieg , Stephan Tremmel ·

YOU? · · 2023 · Open Access · · DOI: https://doi.org/10.1016/j.procir.2023.06.189

Casting process simulations are commonly used to predict and avoid defect formation. Their integration into structural optimization can enable automated structure- and process-optimized castings. Nevertheless, these simulations are time-consuming and computationally expensive. Therefore, this paper used graph theory and skeletonization techniques to extract geometric features from arbitrary 3D geometries and transferred them to machine learning-metamodels. This method can replace casting process simulation for the prediction of directional solidification in low-pressure die casting. Automated machine learning and hyperparameter optimization were used to systemize the search for well-suited neural network architectures. Two examples were used to train the metamodels, which are subsequently evaluated by a further test example, unknown to the training data and compared to the simulation results. The results showed an accuracy on unknown geometries over 60 % and thus emphasized that neural network metamodels are capable of replacing time-consuming casting process simulation for specific objectives.

Related Topics

Process (Computing)

Artificial Intelligence

Die (Integrated Circuit)

Engineering

Algorithm

Mechanical Engineering

Materials Science

Composite Material

Philosophy

Concepts

Artificial neural network Hyperparameter Process (computing) Artificial intelligence Computer science Machine learning Die casting Feature (linguistics) Casting Die (integrated circuit) Engineering Algorithm Mechanical engineering Materials science Operating system Composite material Philosophy Linguistics

Metadata

Type: article
Language: en
Landing Page: https://doi.org/10.1016/j.procir.2023.06.189
OA Status: diamond
Cited By: 3
References: 37
Related Works: 10
OpenAlex ID: https://openalex.org/W4384788748

All OpenAlex metadata

Raw OpenAlex JSON

OpenAlex ID: https://openalex.org/W4384788748

Canonical identifier for this work in OpenAlex
DOI: https://doi.org/10.1016/j.procir.2023.06.189

Digital Object Identifier
Title: Predicting the solidification time of low pressure die castings using geometric feature-based machine learning metamodels

Work title
Type: article

OpenAlex work type
Language: en

Primary language
Publication year: 2023

Year of publication
Publication date: 2023-01-01

Full publication date if available
Authors: Tobias Rosnitschek, Maximilian Erber, Bettina Alber-Laukant, Christoph Hartmann, Wolfram Volk, Frank Rieg, Stephan Tremmel

List of authors in order
Landing page: https://doi.org/10.1016/j.procir.2023.06.189

Publisher landing page
Open access: Yes

Whether a free full text is available
OA status: diamond

Open access status per OpenAlex
OA URL: https://doi.org/10.1016/j.procir.2023.06.189

Direct OA link when available
Concepts: Artificial neural network, Hyperparameter, Process (computing), Artificial intelligence, Computer science, Machine learning, Die casting, Feature (linguistics), Casting, Die (integrated circuit), Engineering, Algorithm, Mechanical engineering, Materials science, Operating system, Composite material, Philosophy, Linguistics

Top concepts (fields/topics) attached by OpenAlex
Cited by: 3

Total citation count in OpenAlex
Citations by year (recent): 2025: 1, 2024: 2

Per-year citation counts (last 5 years)
References (count): 37

Number of works referenced by this work
Related works (count): 10

Other works algorithmically related by OpenAlex

Full payload

id	https://openalex.org/W4384788748
doi	https://doi.org/10.1016/j.procir.2023.06.189
ids.doi	https://doi.org/10.1016/j.procir.2023.06.189
ids.openalex	https://openalex.org/W4384788748
fwci	0.85654118
type	article
title	Predicting the solidification time of low pressure die castings using geometric feature-based machine learning metamodels
biblio.issue
biblio.volume	118
biblio.last_page	1107
biblio.first_page	1102
grants[0].funder	https://openalex.org/F4320320879
grants[0].award_id
grants[0].funder_display_name	Deutsche Forschungsgemeinschaft
topics[0].id	https://openalex.org/T11159
topics[0].field.id	https://openalex.org/fields/22
topics[0].field.display_name	Engineering
topics[0].score	0.9943000078201294
topics[0].domain.id	https://openalex.org/domains/3
topics[0].domain.display_name	Physical Sciences
topics[0].subfield.id	https://openalex.org/subfields/2209
topics[0].subfield.display_name	Industrial and Manufacturing Engineering
topics[0].display_name	Manufacturing Process and Optimization
topics[1].id	https://openalex.org/T10670
topics[1].field.id	https://openalex.org/fields/22
topics[1].field.display_name	Engineering
topics[1].score	0.9916999936103821
topics[1].domain.id	https://openalex.org/domains/3
topics[1].domain.display_name	Physical Sciences
topics[1].subfield.id	https://openalex.org/subfields/2202
topics[1].subfield.display_name	Aerospace Engineering
topics[1].display_name	Aluminum Alloy Microstructure Properties
topics[2].id	https://openalex.org/T11201
topics[2].field.id	https://openalex.org/fields/22
topics[2].field.display_name	Engineering
topics[2].score	0.9879999756813049
topics[2].domain.id	https://openalex.org/domains/3
topics[2].domain.display_name	Physical Sciences
topics[2].subfield.id	https://openalex.org/subfields/2211
topics[2].subfield.display_name	Mechanics of Materials
topics[2].display_name	Metallurgy and Material Forming
funders[0].id	https://openalex.org/F4320320879
funders[0].ror	https://ror.org/018mejw64
funders[0].display_name	Deutsche Forschungsgemeinschaft
is_xpac	False
apc_list
apc_paid
concepts[0].id	https://openalex.org/C50644808
concepts[0].level	2
concepts[0].score	0.7130262851715088
concepts[0].wikidata	https://www.wikidata.org/wiki/Q192776
concepts[0].display_name	Artificial neural network
concepts[1].id	https://openalex.org/C8642999
concepts[1].level	2
concepts[1].score	0.6809490323066711
concepts[1].wikidata	https://www.wikidata.org/wiki/Q4171168
concepts[1].display_name	Hyperparameter
concepts[2].id	https://openalex.org/C98045186
concepts[2].level	2
concepts[2].score	0.6163679361343384
concepts[2].wikidata	https://www.wikidata.org/wiki/Q205663
concepts[2].display_name	Process (computing)
concepts[3].id	https://openalex.org/C154945302
concepts[3].level	1
concepts[3].score	0.5250694155693054
concepts[3].wikidata	https://www.wikidata.org/wiki/Q11660
concepts[3].display_name	Artificial intelligence
concepts[4].id	https://openalex.org/C41008148
concepts[4].level	0
concepts[4].score	0.49067461490631104
concepts[4].wikidata	https://www.wikidata.org/wiki/Q21198
concepts[4].display_name	Computer science
concepts[5].id	https://openalex.org/C119857082
concepts[5].level	1
concepts[5].score	0.44062933325767517
concepts[5].wikidata	https://www.wikidata.org/wiki/Q2539
concepts[5].display_name	Machine learning
concepts[6].id	https://openalex.org/C2776624666
concepts[6].level	3
concepts[6].score	0.42930927872657776
concepts[6].wikidata	https://www.wikidata.org/wiki/Q3325511
concepts[6].display_name	Die casting
concepts[7].id	https://openalex.org/C2776401178
concepts[7].level	2
concepts[7].score	0.415205180644989
concepts[7].wikidata	https://www.wikidata.org/wiki/Q12050496
concepts[7].display_name	Feature (linguistics)
concepts[8].id	https://openalex.org/C16635281
concepts[8].level	2
concepts[8].score	0.41387292742729187
concepts[8].wikidata	https://www.wikidata.org/wiki/Q496098
concepts[8].display_name	Casting
concepts[9].id	https://openalex.org/C111106434
concepts[9].level	2
concepts[9].score	0.33411484956741333
concepts[9].wikidata	https://www.wikidata.org/wiki/Q1072430
concepts[9].display_name	Die (integrated circuit)
concepts[10].id	https://openalex.org/C127413603
concepts[10].level	0
concepts[10].score	0.3263188302516937
concepts[10].wikidata	https://www.wikidata.org/wiki/Q11023
concepts[10].display_name	Engineering
concepts[11].id	https://openalex.org/C11413529
concepts[11].level	1
concepts[11].score	0.32289618253707886
concepts[11].wikidata	https://www.wikidata.org/wiki/Q8366
concepts[11].display_name	Algorithm
concepts[12].id	https://openalex.org/C78519656
concepts[12].level	1
concepts[12].score	0.2712174355983734
concepts[12].wikidata	https://www.wikidata.org/wiki/Q101333
concepts[12].display_name	Mechanical engineering
concepts[13].id	https://openalex.org/C192562407
concepts[13].level	0
concepts[13].score	0.11123168468475342
concepts[13].wikidata	https://www.wikidata.org/wiki/Q228736
concepts[13].display_name	Materials science
concepts[14].id	https://openalex.org/C111919701
concepts[14].level	1
concepts[14].score	0.0
concepts[14].wikidata	https://www.wikidata.org/wiki/Q9135
concepts[14].display_name	Operating system
concepts[15].id	https://openalex.org/C159985019
concepts[15].level	1
concepts[15].score	0.0
concepts[15].wikidata	https://www.wikidata.org/wiki/Q181790
concepts[15].display_name	Composite material
concepts[16].id	https://openalex.org/C138885662
concepts[16].level	0
concepts[16].score	0.0
concepts[16].wikidata	https://www.wikidata.org/wiki/Q5891
concepts[16].display_name	Philosophy
concepts[17].id	https://openalex.org/C41895202
concepts[17].level	1
concepts[17].score	0.0
concepts[17].wikidata	https://www.wikidata.org/wiki/Q8162
concepts[17].display_name	Linguistics
keywords[0].id	https://openalex.org/keywords/artificial-neural-network
keywords[0].score	0.7130262851715088
keywords[0].display_name	Artificial neural network
keywords[1].id	https://openalex.org/keywords/hyperparameter
keywords[1].score	0.6809490323066711
keywords[1].display_name	Hyperparameter
keywords[2].id	https://openalex.org/keywords/process
keywords[2].score	0.6163679361343384
keywords[2].display_name	Process (computing)
keywords[3].id	https://openalex.org/keywords/artificial-intelligence
keywords[3].score	0.5250694155693054
keywords[3].display_name	Artificial intelligence
keywords[4].id	https://openalex.org/keywords/computer-science
keywords[4].score	0.49067461490631104
keywords[4].display_name	Computer science
keywords[5].id	https://openalex.org/keywords/machine-learning
keywords[5].score	0.44062933325767517
keywords[5].display_name	Machine learning
keywords[6].id	https://openalex.org/keywords/die-casting
keywords[6].score	0.42930927872657776
keywords[6].display_name	Die casting
keywords[7].id	https://openalex.org/keywords/feature
keywords[7].score	0.415205180644989
keywords[7].display_name	Feature (linguistics)
keywords[8].id	https://openalex.org/keywords/casting
keywords[8].score	0.41387292742729187
keywords[8].display_name	Casting
keywords[9].id	https://openalex.org/keywords/die
keywords[9].score	0.33411484956741333
keywords[9].display_name	Die (integrated circuit)
keywords[10].id	https://openalex.org/keywords/engineering
keywords[10].score	0.3263188302516937
keywords[10].display_name	Engineering
keywords[11].id	https://openalex.org/keywords/algorithm
keywords[11].score	0.32289618253707886
keywords[11].display_name	Algorithm
keywords[12].id	https://openalex.org/keywords/mechanical-engineering
keywords[12].score	0.2712174355983734
keywords[12].display_name	Mechanical engineering
keywords[13].id	https://openalex.org/keywords/materials-science
keywords[13].score	0.11123168468475342
keywords[13].display_name	Materials science
language	en
locations[0].id	doi:10.1016/j.procir.2023.06.189
locations[0].is_oa	True
locations[0].source.id	https://openalex.org/S2898565713
locations[0].source.issn	2212-8271
locations[0].source.type	journal
locations[0].source.is_oa	True
locations[0].source.issn_l	2212-8271
locations[0].source.is_core	True
locations[0].source.is_in_doaj	False
locations[0].source.display_name	Procedia CIRP
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].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	Procedia CIRP
locations[0].landing_page_url	https://doi.org/10.1016/j.procir.2023.06.189
locations[1].id	pmh:oai:mediatum.ub.tum.de:node/1759841
locations[1].is_oa	False
locations[1].source.id	https://openalex.org/S4306400453
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	mediaTUM – the media and publications repository of the Technical University Munich (Technical University Munich)
locations[1].source.host_organization	https://openalex.org/I62916508
locations[1].source.host_organization_name	Technical University of Munich
locations[1].source.host_organization_lineage	https://openalex.org/I62916508
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
locations[1].landing_page_url	https://mediatum.ub.tum.de/1759841
indexed_in	crossref
authorships[0].author.id	https://openalex.org/A5068243940
authorships[0].author.orcid	https://orcid.org/0000-0002-4876-2536
authorships[0].author.display_name	Tobias Rosnitschek
authorships[0].countries	DE
authorships[0].affiliations[0].institution_ids	https://openalex.org/I54009628
authorships[0].affiliations[0].raw_affiliation_string	Engineering Design and CAD, University of Bayreuth, Universitaetsstr. 30, 95447, Bayreuth, Germany
authorships[0].institutions[0].id	https://openalex.org/I54009628
authorships[0].institutions[0].ror	https://ror.org/0234wmv40
authorships[0].institutions[0].type	education
authorships[0].institutions[0].lineage	https://openalex.org/I54009628
authorships[0].institutions[0].country_code	DE
authorships[0].institutions[0].display_name	University of Bayreuth
authorships[0].author_position	first
authorships[0].raw_author_name	Tobias Rosnitschek
authorships[0].is_corresponding	True
authorships[0].raw_affiliation_strings	Engineering Design and CAD, University of Bayreuth, Universitaetsstr. 30, 95447, Bayreuth, Germany
authorships[1].author.id	https://openalex.org/A5038064303
authorships[1].author.orcid	https://orcid.org/0000-0002-9799-6371
authorships[1].author.display_name	Maximilian Erber
authorships[1].countries	DE
authorships[1].affiliations[0].institution_ids	https://openalex.org/I62916508
authorships[1].affiliations[0].raw_affiliation_string	Metal Forming and Casting, Technical Univeristy of Munich, Walther-Meiner-Str. 4, 85748 Garching, Germany
authorships[1].institutions[0].id	https://openalex.org/I62916508
authorships[1].institutions[0].ror	https://ror.org/02kkvpp62
authorships[1].institutions[0].type	education
authorships[1].institutions[0].lineage	https://openalex.org/I62916508
authorships[1].institutions[0].country_code	DE
authorships[1].institutions[0].display_name	Technical University of Munich
authorships[1].author_position	middle
authorships[1].raw_author_name	Maximilian Erber
authorships[1].is_corresponding	False
authorships[1].raw_affiliation_strings	Metal Forming and Casting, Technical Univeristy of Munich, Walther-Meiner-Str. 4, 85748 Garching, Germany
authorships[2].author.id	https://openalex.org/A5074470799
authorships[2].author.orcid	https://orcid.org/0000-0002-4200-7329
authorships[2].author.display_name	Bettina Alber-Laukant
authorships[2].countries	DE
authorships[2].affiliations[0].institution_ids	https://openalex.org/I54009628
authorships[2].affiliations[0].raw_affiliation_string	Engineering Design and CAD, University of Bayreuth, Universitaetsstr. 30, 95447, Bayreuth, Germany
authorships[2].institutions[0].id	https://openalex.org/I54009628
authorships[2].institutions[0].ror	https://ror.org/0234wmv40
authorships[2].institutions[0].type	education
authorships[2].institutions[0].lineage	https://openalex.org/I54009628
authorships[2].institutions[0].country_code	DE
authorships[2].institutions[0].display_name	University of Bayreuth
authorships[2].author_position	middle
authorships[2].raw_author_name	Bettina Alber-Laukant
authorships[2].is_corresponding	False
authorships[2].raw_affiliation_strings	Engineering Design and CAD, University of Bayreuth, Universitaetsstr. 30, 95447, Bayreuth, Germany
authorships[3].author.id	https://openalex.org/A5006346206
authorships[3].author.orcid	https://orcid.org/0000-0001-7565-3709
authorships[3].author.display_name	Christoph Hartmann
authorships[3].countries	DE
authorships[3].affiliations[0].institution_ids	https://openalex.org/I62916508
authorships[3].affiliations[0].raw_affiliation_string	Metal Forming and Casting, Technical Univeristy of Munich, Walther-Meiner-Str. 4, 85748 Garching, Germany
authorships[3].institutions[0].id	https://openalex.org/I62916508
authorships[3].institutions[0].ror	https://ror.org/02kkvpp62
authorships[3].institutions[0].type	education
authorships[3].institutions[0].lineage	https://openalex.org/I62916508
authorships[3].institutions[0].country_code	DE
authorships[3].institutions[0].display_name	Technical University of Munich
authorships[3].author_position	middle
authorships[3].raw_author_name	Christoph Hartmann
authorships[3].is_corresponding	False
authorships[3].raw_affiliation_strings	Metal Forming and Casting, Technical Univeristy of Munich, Walther-Meiner-Str. 4, 85748 Garching, Germany
authorships[4].author.id	https://openalex.org/A5065691152
authorships[4].author.orcid	https://orcid.org/0000-0002-5759-3551
authorships[4].author.display_name	Wolfram Volk
authorships[4].countries	DE
authorships[4].affiliations[0].institution_ids	https://openalex.org/I62916508
authorships[4].affiliations[0].raw_affiliation_string	Metal Forming and Casting, Technical Univeristy of Munich, Walther-Meiner-Str. 4, 85748 Garching, Germany
authorships[4].institutions[0].id	https://openalex.org/I62916508
authorships[4].institutions[0].ror	https://ror.org/02kkvpp62
authorships[4].institutions[0].type	education
authorships[4].institutions[0].lineage	https://openalex.org/I62916508
authorships[4].institutions[0].country_code	DE
authorships[4].institutions[0].display_name	Technical University of Munich
authorships[4].author_position	middle
authorships[4].raw_author_name	Wolfram Volk
authorships[4].is_corresponding	False
authorships[4].raw_affiliation_strings	Metal Forming and Casting, Technical Univeristy of Munich, Walther-Meiner-Str. 4, 85748 Garching, Germany
authorships[5].author.id	https://openalex.org/A5086457965
authorships[5].author.orcid
authorships[5].author.display_name	Frank Rieg
authorships[5].countries	DE
authorships[5].affiliations[0].institution_ids	https://openalex.org/I54009628
authorships[5].affiliations[0].raw_affiliation_string	Engineering Design and CAD, University of Bayreuth, Universitaetsstr. 30, 95447, Bayreuth, Germany
authorships[5].institutions[0].id	https://openalex.org/I54009628
authorships[5].institutions[0].ror	https://ror.org/0234wmv40
authorships[5].institutions[0].type	education
authorships[5].institutions[0].lineage	https://openalex.org/I54009628
authorships[5].institutions[0].country_code	DE
authorships[5].institutions[0].display_name	University of Bayreuth
authorships[5].author_position	middle
authorships[5].raw_author_name	Frank Rieg
authorships[5].is_corresponding	False
authorships[5].raw_affiliation_strings	Engineering Design and CAD, University of Bayreuth, Universitaetsstr. 30, 95447, Bayreuth, Germany
authorships[6].author.id	https://openalex.org/A5048521375
authorships[6].author.orcid	https://orcid.org/0000-0003-1644-563X
authorships[6].author.display_name	Stephan Tremmel
authorships[6].countries	DE
authorships[6].affiliations[0].institution_ids	https://openalex.org/I54009628
authorships[6].affiliations[0].raw_affiliation_string	Engineering Design and CAD, University of Bayreuth, Universitaetsstr. 30, 95447, Bayreuth, Germany
authorships[6].institutions[0].id	https://openalex.org/I54009628
authorships[6].institutions[0].ror	https://ror.org/0234wmv40
authorships[6].institutions[0].type	education
authorships[6].institutions[0].lineage	https://openalex.org/I54009628
authorships[6].institutions[0].country_code	DE
authorships[6].institutions[0].display_name	University of Bayreuth
authorships[6].author_position	last
authorships[6].raw_author_name	Stephan Tremmel
authorships[6].is_corresponding	False
authorships[6].raw_affiliation_strings	Engineering Design and CAD, University of Bayreuth, Universitaetsstr. 30, 95447, Bayreuth, Germany
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.procir.2023.06.189
open_access.oa_status	diamond
open_access.any_repository_has_fulltext	False
created_date	2025-10-10T00:00:00
display_name	Predicting the solidification time of low pressure die castings using geometric feature-based machine learning metamodels
has_fulltext	False
is_retracted	False
updated_date	2025-11-06T03:46:38.306776
primary_topic.id	https://openalex.org/T11159
primary_topic.field.id	https://openalex.org/fields/22
primary_topic.field.display_name	Engineering
primary_topic.score	0.9943000078201294
primary_topic.domain.id	https://openalex.org/domains/3
primary_topic.domain.display_name	Physical Sciences
primary_topic.subfield.id	https://openalex.org/subfields/2209
primary_topic.subfield.display_name	Industrial and Manufacturing Engineering
primary_topic.display_name	Manufacturing Process and Optimization
related_works	https://openalex.org/W2379665820, https://openalex.org/W2071655285, https://openalex.org/W2041633646, https://openalex.org/W2024062656, https://openalex.org/W4400742327, https://openalex.org/W2351693182, https://openalex.org/W775357020, https://openalex.org/W3149311625, https://openalex.org/W2204902895, https://openalex.org/W2372050652
cited_by_count	3
counts_by_year[0].year	2025
counts_by_year[0].cited_by_count	1
counts_by_year[1].year	2024
counts_by_year[1].cited_by_count	2
locations_count	2
best_oa_location.id	doi:10.1016/j.procir.2023.06.189
best_oa_location.is_oa	True
best_oa_location.source.id	https://openalex.org/S2898565713
best_oa_location.source.issn	2212-8271
best_oa_location.source.type	journal
best_oa_location.source.is_oa	True
best_oa_location.source.issn_l	2212-8271
best_oa_location.source.is_core	True
best_oa_location.source.is_in_doaj	False
best_oa_location.source.display_name	Procedia CIRP
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.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	Procedia CIRP
best_oa_location.landing_page_url	https://doi.org/10.1016/j.procir.2023.06.189
primary_location.id	doi:10.1016/j.procir.2023.06.189
primary_location.is_oa	True
primary_location.source.id	https://openalex.org/S2898565713
primary_location.source.issn	2212-8271
primary_location.source.type	journal
primary_location.source.is_oa	True
primary_location.source.issn_l	2212-8271
primary_location.source.is_core	True
primary_location.source.is_in_doaj	False
primary_location.source.display_name	Procedia CIRP
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.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	Procedia CIRP
primary_location.landing_page_url	https://doi.org/10.1016/j.procir.2023.06.189
publication_date	2023-01-01
publication_year	2023
referenced_works	https://openalex.org/W3045069402, https://openalex.org/W2513222915, https://openalex.org/W2775530282, https://openalex.org/W6754614366, https://openalex.org/W6760738939, https://openalex.org/W6600617704, https://openalex.org/W1563102018, https://openalex.org/W2807129294, https://openalex.org/W2487800405, https://openalex.org/W2563933290, https://openalex.org/W2760557260, https://openalex.org/W3176856133, https://openalex.org/W3167546085, https://openalex.org/W226566298, https://openalex.org/W2965742591, https://openalex.org/W2918175718, https://openalex.org/W2074766433, https://openalex.org/W2285776795, https://openalex.org/W2998722642, https://openalex.org/W6755509158, https://openalex.org/W3035965352, https://openalex.org/W3150635270, https://openalex.org/W3209575515, https://openalex.org/W2342249984, https://openalex.org/W6969646697, https://openalex.org/W2011301426, https://openalex.org/W6675354045, https://openalex.org/W3210800143, https://openalex.org/W6893982476, https://openalex.org/W2034437670, https://openalex.org/W2053056251, https://openalex.org/W2169528473, https://openalex.org/W2101234009, https://openalex.org/W3099878876, https://openalex.org/W3003716403, https://openalex.org/W4392271976, https://openalex.org/W3171696784
referenced_works_count	37
abstract_inverted_index.%	127
abstract_inverted_index.a	102
abstract_inverted_index.3D	47
abstract_inverted_index.60	126
abstract_inverted_index.an	120
abstract_inverted_index.by	101
abstract_inverted_index.in	68
abstract_inverted_index.of	65, 137
abstract_inverted_index.on	122
abstract_inverted_index.to	6, 41, 52, 80, 93, 107, 113
abstract_inverted_index.The	117
abstract_inverted_index.Two	89
abstract_inverted_index.and	8, 21, 29, 38, 49, 75, 111, 128
abstract_inverted_index.are	3, 27, 98, 135
abstract_inverted_index.can	17, 57
abstract_inverted_index.die	70
abstract_inverted_index.for	62, 84, 143
abstract_inverted_index.the	63, 82, 95, 108, 114
abstract_inverted_index.This	55
abstract_inverted_index.data	110
abstract_inverted_index.from	45
abstract_inverted_index.into	14
abstract_inverted_index.over	125
abstract_inverted_index.test	104
abstract_inverted_index.that	131
abstract_inverted_index.them	51
abstract_inverted_index.this	33
abstract_inverted_index.thus	129
abstract_inverted_index.used	5, 35, 79, 92
abstract_inverted_index.were	78, 91
abstract_inverted_index.Their	12
abstract_inverted_index.avoid	9
abstract_inverted_index.graph	36
abstract_inverted_index.paper	34
abstract_inverted_index.these	25
abstract_inverted_index.train	94
abstract_inverted_index.which	97
abstract_inverted_index.defect	10
abstract_inverted_index.enable	18
abstract_inverted_index.method	56
abstract_inverted_index.neural	86, 132
abstract_inverted_index.search	83
abstract_inverted_index.showed	119
abstract_inverted_index.theory	37
abstract_inverted_index.Casting	0
abstract_inverted_index.capable	136
abstract_inverted_index.casting	59, 140
abstract_inverted_index.extract	42
abstract_inverted_index.further	103
abstract_inverted_index.machine	53, 73
abstract_inverted_index.network	87, 133
abstract_inverted_index.predict	7
abstract_inverted_index.process	1, 60, 141
abstract_inverted_index.replace	58
abstract_inverted_index.results	118
abstract_inverted_index.unknown	106, 123
abstract_inverted_index.accuracy	121
abstract_inverted_index.casting.	71
abstract_inverted_index.commonly	4
abstract_inverted_index.compared	112
abstract_inverted_index.example,	105
abstract_inverted_index.examples	90
abstract_inverted_index.features	44
abstract_inverted_index.learning	74
abstract_inverted_index.results.	116
abstract_inverted_index.specific	144
abstract_inverted_index.training	109
abstract_inverted_index.Automated	72
abstract_inverted_index.arbitrary	46
abstract_inverted_index.automated	19
abstract_inverted_index.castings.	23
abstract_inverted_index.evaluated	100
abstract_inverted_index.geometric	43
abstract_inverted_index.replacing	138
abstract_inverted_index.systemize	81
abstract_inverted_index.Therefore,	32
abstract_inverted_index.emphasized	130
abstract_inverted_index.expensive.	31
abstract_inverted_index.formation.	11
abstract_inverted_index.geometries	48, 124
abstract_inverted_index.metamodels	134
abstract_inverted_index.prediction	64
abstract_inverted_index.simulation	61, 115, 142
abstract_inverted_index.structural	15
abstract_inverted_index.structure-	20
abstract_inverted_index.techniques	40
abstract_inverted_index.directional	66
abstract_inverted_index.integration	13
abstract_inverted_index.metamodels,	96
abstract_inverted_index.objectives.	145
abstract_inverted_index.simulations	2, 26
abstract_inverted_index.transferred	50
abstract_inverted_index.well-suited	85
abstract_inverted_index.low-pressure	69
abstract_inverted_index.optimization	16, 77
abstract_inverted_index.subsequently	99
abstract_inverted_index.Nevertheless,	24
abstract_inverted_index.architectures.	88
abstract_inverted_index.hyperparameter	76
abstract_inverted_index.solidification	67
abstract_inverted_index.time-consuming	28, 139
abstract_inverted_index.computationally	30
abstract_inverted_index.skeletonization	39
abstract_inverted_index.process-optimized	22
abstract_inverted_index.learning-metamodels.	54
cited_by_percentile_year.max	96
cited_by_percentile_year.min	91
corresponding_author_ids	https://openalex.org/A5068243940
countries_distinct_count	1
institutions_distinct_count	7
corresponding_institution_ids	https://openalex.org/I54009628
citation_normalized_percentile.value	0.75342114
citation_normalized_percentile.is_in_top_1_percent	False
citation_normalized_percentile.is_in_top_10_percent	False