Feature selection for constructing datasets toward automated lifecycleassessment for additive manufacturing Article Swipe
Ahmed Naser
,
Fantahum Defersha
,
Sheng Yang
·
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.17118/11143/21050
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.17118/11143/21050
Additive Manufacturing (AM) is considered an innovative technology to fabricate goods with green characteristics. In comparison to conventional manufacturing (CM) approaches, AM technologies have shown impressive results in enhancing sustainability in production systems. Various research has been conducted to assess the environmental impacts of AM based on the well-known life cycle assessment (LCA) framework. However, this approach requires intensive domain knowledge to build the environmental impact model and interpret the impacts of input variances. This knowledge barrier may cause delays and challenges in the selection of the optimal design and process parameters for additively manufactured parts in the product design and planning stages due to the iterative designevaluation process. As such, the research community demands an automated LCA tool for supporting AM toward elevated sustainability. To achieve this ambitious goal, this paper particularly investigates the fundamental question – “What are the key influential parameters that pose an impact on the environmental sustainability of AM?”. A methodological framework for identifying the key influential parameters for AM is proposed. The framework was demonstrated by taking the fused filament fabrication (FFF) process as an example. Based on instantiation, LCA of over 200 AM instances, and correlation analysis, the key influential parameters are identified. Finally, a dataset with the identified features could be constructed. This dataset is expected to establish a common base for scale-up with joint efforts from the AM community.
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- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.17118/11143/21050
- https://savoirs.usherbrooke.ca/bitstream/11143/21050/1/103_CSME-CFDCanada_2023.pdf
- OA Status
- gold
- References
- 39
- Related Works
- 10
- OpenAlex ID
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All OpenAlex metadata
Raw OpenAlex JSON
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https://openalex.org/W4389584917Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.17118/11143/21050Digital Object Identifier
- Title
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Feature selection for constructing datasets toward automated lifecycleassessment for additive manufacturingWork title
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2023Year of publication
- Publication date
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2023-01-01Full publication date if available
- Authors
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Ahmed Naser, Fantahum Defersha, Sheng YangList of authors in order
- Landing page
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https://doi.org/10.17118/11143/21050Publisher landing page
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https://savoirs.usherbrooke.ca/bitstream/11143/21050/1/103_CSME-CFDCanada_2023.pdfDirect link to full text PDF
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YesWhether a free full text is available
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goldOpen access status per OpenAlex
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https://savoirs.usherbrooke.ca/bitstream/11143/21050/1/103_CSME-CFDCanada_2023.pdfDirect OA link when available
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Feature selection, Computer science, Selection (genetic algorithm), Feature (linguistics), Artificial intelligence, Data mining, Pattern recognition (psychology), Linguistics, PhilosophyTop concepts (fields/topics) attached by OpenAlex
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0Total citation count in OpenAlex
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.influential | 143, 162, 197 |
| abstract_inverted_index.constructed. | 210 |
| abstract_inverted_index.conventional | 18 |
| abstract_inverted_index.demonstrated | 171 |
| abstract_inverted_index.investigates | 134 |
| abstract_inverted_index.manufactured | 95 |
| abstract_inverted_index.particularly | 133 |
| abstract_inverted_index.technologies | 23 |
| abstract_inverted_index.Manufacturing | 2 |
| abstract_inverted_index.environmental | 42, 65, 151 |
| abstract_inverted_index.manufacturing | 19 |
| abstract_inverted_index.instantiation, | 185 |
| abstract_inverted_index.methodological | 156 |
| abstract_inverted_index.sustainability | 30, 152 |
| abstract_inverted_index.sustainability. | 125 |
| abstract_inverted_index.characteristics. | 14 |
| abstract_inverted_index.designevaluation | 108 |
| cited_by_percentile_year | |
| countries_distinct_count | 1 |
| institutions_distinct_count | 3 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/12 |
| sustainable_development_goals[0].score | 0.41999998688697815 |
| sustainable_development_goals[0].display_name | Responsible consumption and production |
| citation_normalized_percentile.value | 0.20782126 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |