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https://hdl.handle.net/11147/13738
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DC Field | Value | Language |
---|---|---|
dc.contributor.author | Ozbey, Sayit | - |
dc.contributor.author | Artem, Hatice Secil | - |
dc.date.accessioned | 2023-09-29T11:34:46Z | - |
dc.date.available | 2023-09-29T11:34:46Z | - |
dc.date.issued | 2025 | - |
dc.identifier.issn | 2196-7229 | - |
dc.identifier.issn | 2196-7237 | - |
dc.identifier.uri | https://doi.org/10.1007/s40516-025-00297-6 | - |
dc.description.abstract | Industrial applications require materials with specific surface quality and hardness properties. Laser surface treatment stands out as a cost-effective and effective method that improves surface performance by changing the structural and physical properties of the material. 1.2379 cold work tool steel is a commonly used material in die and mold industries for injection mold inserts; therefore, the surface properties of the material play a significant role. In this study, it is aimed to optimize laser parameters; the laser power, pulse duration, repetition rate and line spacing for the responses such as hardness and surface roughness. For this purpose, 1.2379 cold work tool surfaces were treated using a commercially available industrial ytterbium low-power pulsed fiber laser experimentally. Experiments were conducted based on 34 full factorials. Vickers hardness and micro-roughness measurements were performed on the laser-treated surfaces. Regression models were developed using experimental data and the appropriate models were selected for each response. The response variables were then optimized based on stochastic optimization methods: Nelder-Mead, Differential Evolution, Random Search and Simulated Annealing. The results indicate that a maximum hardness of 495 HV0.5 and a minimum surface roughness of 0.277 mu m were achieved, corresponding to a 61% increase and a 43% decrease, respectively, compared to the base metal. | en_US |
dc.description.sponsorship | Kocaeli University- Laser Technologies Research and Application Center (LATARUM) | en_US |
dc.description.sponsorship | This research was partly supported by Kocaeli University- Laser Technologies Research and Application Center (LATARUM). | en_US |
dc.format.extent | xi, 73 leaves | - |
dc.language.iso | en | en_US |
dc.publisher | Springernature | en_US |
dc.rights | info:eu-repo/semantics/closedAccess | en_US |
dc.subject | Fiber Laser | en_US |
dc.subject | Laser Surface Treatment | en_US |
dc.subject | 1.2379 Tool Steel | en_US |
dc.subject | Hardness | en_US |
dc.subject | Roughness | en_US |
dc.subject | Stochastic Optimization | en_US |
dc.subject | Neuro-Regression | en_US |
dc.title | Laser Surface Treatment Optimization of 1.2379 (Aisi D2) Tool Steel | en_US |
dc.type | Article | en_US |
dc.authorid | 0000-0002-9782-6997 | - |
dc.department | İzmir Institute of Technology | en_US |
dc.identifier.wos | WOS:001502018900001 | - |
dc.identifier.scopus | 2-s2.0-105005120043 | - |
dc.relation.publicationcategory | Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı | en_US |
dc.identifier.doi | 10.1007/s40516-025-00297-6 | - |
dc.authorscopusid | 57551890300 | - |
dc.authorscopusid | 23388598600 | - |
dc.identifier.wosquality | N/A | - |
dc.identifier.scopusquality | Q3 | - |
dc.identifier.yoktezid | 813106 | en_US |
dc.description.woscitationindex | Emerging Sources Citation Index | - |
item.grantfulltext | open | - |
item.openairecristype | http://purl.org/coar/resource_type/c_18cf | - |
item.fulltext | With Fulltext | - |
item.cerifentitytype | Publications | - |
item.languageiso639-1 | en | - |
item.openairetype | Article | - |
crisitem.author.dept | 03.10. Department of Mechanical Engineering | - |
Appears in Collections: | Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection |
Files in This Item:
File | Description | Size | Format | |
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10554957.pdf | Master Thesis | 3.37 MB | Adobe PDF | View/Open |
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