Fuzzy applications of Best–Worst method in manufacturing environment
Abstract High-strength steel alloys, titanium, ceramics, composites are in the group of materials that are hard to machine. Conventional manufacturing techniques are not sufficient to machine these materials. For this reason, these materials are generally machined with non-conventional manufacturing...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Sofuoğlu, Mehmet Alper [verfasserIn] |
|---|
| Format: |
Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2019 |
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| Schlagwörter: |
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| Anmerkung: |
© Springer-Verlag GmbH Germany, part of Springer Nature 2019 |
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| Übergeordnetes Werk: |
Enthalten in: Soft computing - Springer Berlin Heidelberg, 1997, 24(2019), 1 vom: 08. Nov., Seite 647-659 |
|---|---|
| Übergeordnetes Werk: |
volume:24 ; year:2019 ; number:1 ; day:08 ; month:11 ; pages:647-659 |
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| DOI / URN: |
10.1007/s00500-019-04491-5 |
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OLC2034903188 |
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| 520 | |a Abstract High-strength steel alloys, titanium, ceramics, composites are in the group of materials that are hard to machine. Conventional manufacturing techniques are not sufficient to machine these materials. For this reason, these materials are generally machined with non-conventional manufacturing methods. In this study, a fuzzy application of Best–Worst method and a novel hybrid decision-making model (Best–Worst decision-making approach with fuzzy TOPSIS) are proposed to solve different non-traditional machining method selection problems which were taken from the literature. Using these models, the Best–Worst method shortens the steps of solutions in the fuzzy environment compared to the AHP/ANP-based fuzzy solutions in the literature. The proposed models produce successful results. | ||
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Abstract High-strength steel alloys, titanium, ceramics, composites are in the group of materials that are hard to machine. Conventional manufacturing techniques are not sufficient to machine these materials. For this reason, these materials are generally machined with non-conventional manufacturing methods. In this study, a fuzzy application of Best–Worst method and a novel hybrid decision-making model (Best–Worst decision-making approach with fuzzy TOPSIS) are proposed to solve different non-traditional machining method selection problems which were taken from the literature. Using these models, the Best–Worst method shortens the steps of solutions in the fuzzy environment compared to the AHP/ANP-based fuzzy solutions in the literature. The proposed models produce successful results. © Springer-Verlag GmbH Germany, part of Springer Nature 2019 |
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Abstract High-strength steel alloys, titanium, ceramics, composites are in the group of materials that are hard to machine. Conventional manufacturing techniques are not sufficient to machine these materials. For this reason, these materials are generally machined with non-conventional manufacturing methods. In this study, a fuzzy application of Best–Worst method and a novel hybrid decision-making model (Best–Worst decision-making approach with fuzzy TOPSIS) are proposed to solve different non-traditional machining method selection problems which were taken from the literature. Using these models, the Best–Worst method shortens the steps of solutions in the fuzzy environment compared to the AHP/ANP-based fuzzy solutions in the literature. The proposed models produce successful results. © Springer-Verlag GmbH Germany, part of Springer Nature 2019 |
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Abstract High-strength steel alloys, titanium, ceramics, composites are in the group of materials that are hard to machine. Conventional manufacturing techniques are not sufficient to machine these materials. For this reason, these materials are generally machined with non-conventional manufacturing methods. In this study, a fuzzy application of Best–Worst method and a novel hybrid decision-making model (Best–Worst decision-making approach with fuzzy TOPSIS) are proposed to solve different non-traditional machining method selection problems which were taken from the literature. Using these models, the Best–Worst method shortens the steps of solutions in the fuzzy environment compared to the AHP/ANP-based fuzzy solutions in the literature. The proposed models produce successful results. © Springer-Verlag GmbH Germany, part of Springer Nature 2019 |
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<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a22002652 4500</leader><controlfield tag="001">OLC2034903188</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230502112042.0</controlfield><controlfield tag="007">tu</controlfield><controlfield tag="008">200820s2019 xx ||||| 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1007/s00500-019-04491-5</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)OLC2034903188</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-He213)s00500-019-04491-5-p</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">004</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">004</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">11</subfield><subfield code="2">ssgn</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Sofuoğlu, Mehmet Alper</subfield><subfield code="e">verfasserin</subfield><subfield code="0">(orcid)0000-0003-4681-6390</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Fuzzy applications of Best–Worst method in manufacturing environment</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2019</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">ohne Hilfsmittel zu benutzen</subfield><subfield code="b">n</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Band</subfield><subfield code="b">nc</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="500" ind1=" " ind2=" "><subfield code="a">© Springer-Verlag GmbH Germany, part of Springer Nature 2019</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Abstract High-strength steel alloys, titanium, ceramics, composites are in the group of materials that are hard to machine. Conventional manufacturing techniques are not sufficient to machine these materials. For this reason, these materials are generally machined with non-conventional manufacturing methods. In this study, a fuzzy application of Best–Worst method and a novel hybrid decision-making model (Best–Worst decision-making approach with fuzzy TOPSIS) are proposed to solve different non-traditional machining method selection problems which were taken from the literature. Using these models, the Best–Worst method shortens the steps of solutions in the fuzzy environment compared to the AHP/ANP-based fuzzy solutions in the literature. 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