Selection of Additive Manufacturing Machines via Ontology-Supported Multi-Attribute Three-Way Decisions
Selection of a suitable additive manufacturing (AM) machine to manufacture a specific product is one of the important tasks in design for AM. So far, many selection approaches based on multi-attribute decision making have been proposed within academia. Each of these approaches works well in its spec...
| Main Authors: | , , , , |
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| Format: | Article |
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MDPI AG
2023-02-01
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| Series: | Applied Sciences |
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| Online Access: | https://www.mdpi.com/2076-3417/13/5/2926 |
| _version_ | 1797615826693521408 |
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| author | Meifa Huang Bing Fan Long Chen Yanting Pan Yuchu Qin |
| author_facet | Meifa Huang Bing Fan Long Chen Yanting Pan Yuchu Qin |
| author_sort | Meifa Huang |
| collection | DOAJ |
| description | Selection of a suitable additive manufacturing (AM) machine to manufacture a specific product is one of the important tasks in design for AM. So far, many selection approaches based on multi-attribute decision making have been proposed within academia. Each of these approaches works well in its specific context. However, the approaches are not flexible enough and could produce undesirable results as they are all based on multi-attribute two-way decisions. In this paper, a selection approach based on ontology-supported multi-attribute three-way decisions is presented. Firstly, an ontology for AM machine selection is constructed according to vendor documents, benchmark data, expert experience, and the Senvol database. Supported by this ontology, a selection approach based on multi-attribute three-way decisions is then developed. After that, four AM machine selection examples are introduced to illustrate the application of the developed approach. Finally, the effectiveness and advantages of the approach are demonstrated via a set of comparison experiments. The demonstration results suggest that the presented approach is as effective as the existing approaches and more flexible than them when the information for decision making is insufficient or the cost for undesirable decision results is high. |
| first_indexed | 2024-03-11T07:32:24Z |
| format | Article |
| id | doaj.art-f5ccd61dcc504872be11788125906190 |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-03-11T07:32:24Z |
| publishDate | 2023-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj.art-f5ccd61dcc504872be117881259061902023-11-17T07:16:54ZengMDPI AGApplied Sciences2076-34172023-02-01135292610.3390/app13052926Selection of Additive Manufacturing Machines via Ontology-Supported Multi-Attribute Three-Way DecisionsMeifa Huang0Bing Fan1Long Chen2Yanting Pan3Yuchu Qin4Guangxi Key Laboratory of Manufacturing System and Advanced Manufacturing Technology, School of Mechanical and Electrical Engineering, Guilin University of Electronic Technology, Guilin 541004, ChinaGuangxi Key Laboratory of Manufacturing System and Advanced Manufacturing Technology, School of Mechanical and Electrical Engineering, Guilin University of Electronic Technology, Guilin 541004, ChinaGuangxi Key Laboratory of Manufacturing System and Advanced Manufacturing Technology, School of Mechanical and Electrical Engineering, Guilin University of Electronic Technology, Guilin 541004, ChinaGuangxi Key Laboratory of Manufacturing System and Advanced Manufacturing Technology, School of Mechanical and Electrical Engineering, Guilin University of Electronic Technology, Guilin 541004, ChinaGuangxi Key Laboratory of Manufacturing System and Advanced Manufacturing Technology, School of Mechanical and Electrical Engineering, Guilin University of Electronic Technology, Guilin 541004, ChinaSelection of a suitable additive manufacturing (AM) machine to manufacture a specific product is one of the important tasks in design for AM. So far, many selection approaches based on multi-attribute decision making have been proposed within academia. Each of these approaches works well in its specific context. However, the approaches are not flexible enough and could produce undesirable results as they are all based on multi-attribute two-way decisions. In this paper, a selection approach based on ontology-supported multi-attribute three-way decisions is presented. Firstly, an ontology for AM machine selection is constructed according to vendor documents, benchmark data, expert experience, and the Senvol database. Supported by this ontology, a selection approach based on multi-attribute three-way decisions is then developed. After that, four AM machine selection examples are introduced to illustrate the application of the developed approach. Finally, the effectiveness and advantages of the approach are demonstrated via a set of comparison experiments. The demonstration results suggest that the presented approach is as effective as the existing approaches and more flexible than them when the information for decision making is insufficient or the cost for undesirable decision results is high.https://www.mdpi.com/2076-3417/13/5/2926additive manufacturingmachine selectionthree-way decisionsmulti-attribute decision makingontology |
| spellingShingle | Meifa Huang Bing Fan Long Chen Yanting Pan Yuchu Qin Selection of Additive Manufacturing Machines via Ontology-Supported Multi-Attribute Three-Way Decisions Applied Sciences additive manufacturing machine selection three-way decisions multi-attribute decision making ontology |
| title | Selection of Additive Manufacturing Machines via Ontology-Supported Multi-Attribute Three-Way Decisions |
| title_full | Selection of Additive Manufacturing Machines via Ontology-Supported Multi-Attribute Three-Way Decisions |
| title_fullStr | Selection of Additive Manufacturing Machines via Ontology-Supported Multi-Attribute Three-Way Decisions |
| title_full_unstemmed | Selection of Additive Manufacturing Machines via Ontology-Supported Multi-Attribute Three-Way Decisions |
| title_short | Selection of Additive Manufacturing Machines via Ontology-Supported Multi-Attribute Three-Way Decisions |
| title_sort | selection of additive manufacturing machines via ontology supported multi attribute three way decisions |
| topic | additive manufacturing machine selection three-way decisions multi-attribute decision making ontology |
| url | https://www.mdpi.com/2076-3417/13/5/2926 |
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