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Modeling the surface hardness of metal materials produced by 3D selective laser melting
ID Calì, Michele (Author), ID Babič, Matej (Author), ID Baiamonte, Giuliana (Author), ID Magnano, Sebastiano (Author), ID Šturm, Roman (Author)

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Abstract
The present study introduces a novel approach for pattern recognition to analyze the surface hardness of metal parts made by 3D selective laser melting (SLM). A printed part’s hardness is further influenced by post-processing, printing parameters, and post-print material handling. Layer by layer, material is deposited in 3D printing, sometimes referred to as additive manufacturing, to turn a digital design into a tangible product. More complex and adaptable designs are possible because 3D printing adds material rather than removes it, in contrast to conventional manufacturing techniques (such as machining or molding). The current work models the surface hardness of 3D selective laser melting of metal materials using genetic programming and network theory. To assess the hardness of 3D selective laser melting of metal materials, we introduce a novel pattern recognition technique. We apply fractal geometry analysis to determine the complexity of 3D selective laser melting of metal materials.

Language:English
Keywords:additive manufacturing, selective laser melting, surface hardness, fractal geometry, network theory, genetic programming
Work type:Article
Typology:1.01 - Original Scientific Article
Organization:FS - Faculty of Mechanical Engineering
Publication status:Published
Publication version:Version of Record
Year:2026
Number of pages:8 str.
PID:20.500.12556/RUL-179055 This link opens in a new window
UDC:620.1/.2:004.45
ISSN on article:0268-3768
DOI:10.1007/s00170-025-17268-y This link opens in a new window
COBISS.SI-ID:267320835 This link opens in a new window
Publication date in RUL:04.02.2026
Views:409
Downloads:246
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Record is a part of a journal

Title:International journal of advanced manufacturing technology
Shortened title:Int. j. adv. manuf. technol.
Publisher:Springer
ISSN:0268-3768
COBISS.SI-ID:25636352 This link opens in a new window

Licences

License:CC BY 4.0, Creative Commons Attribution 4.0 International
Link:http://creativecommons.org/licenses/by/4.0/
Description:This is the standard Creative Commons license that gives others maximum freedom to do what they want with the work as long as they credit the author.

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