Measuring and analyzing defects of Additive Manufactured Ti-6Al-4V Specimens through Image Segmentation

Measuring and analyzing defects of Additive Manufactured Ti-6Al-4V Specimens through Image Segmentation | Authorea try { document.documentElement.classList.add('js'); } catch (e) { } var _gaq = _gaq || []; _gaq.push(['_setAccount', 'G-8VDV14Y67G']); _gaq.push(['_trackPageview']); (function() { var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true; ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js'; var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s); })(); Skip to main content Preprints Collections Wiley Open Research IET Open Research Ecological Society of Japan All Collections About About Authorea FAQs Contact Us Quick Search anywhere Search for preprint articles, keywords, etc. Search Search ADVANCED SEARCH SCROLL Fatigue & Fracture of Engineering Materials & Structures This is a preprint and has not been peer reviewed. Data may be preliminary. 9 January 2025 V1 Latest version Share on Measuring and analyzing defects of Additive Manufactured Ti-6Al-4V Specimens through Image Segmentation Authors : Ro’i Lang 0009-0001-9176-4561 [email protected] , Or Haim Anidjar , Sahar Slonimsky , Chen Hajaj , Oz Golan , Carmel Matias , Alex Diskin , Strokin Evgeny , and Mor Mega Authors Info & Affiliations https://doi.org/10.22541/au.173641900.06597179/v1 Published Fatigue & Fracture of Engineering Materials & Structures Version of record Peer review timeline 381 views 218 downloads Contents Abstract Supplementary Material Information & Authors Metrics & Citations View Options References Figures Tables Media Share Abstract Additive manufacturing (AM) has expanded significantly, particularly in aerospace; however, AM materials often have defects that impair fatigue performance. This study examines the geometry and morphology of critical defects in Ti-6Al-4V specimens produced using three printing quality settings, followed by hot isostatic pressing (HIP) or heat treatment (HT). We present an automated fatigue failure analysis framework using computer vision and AI to identify critical defects, measure surface proximity, and quantify 14 geometric and morphological features. The model achieved a mean IoU of 0.836 and approximately 10% error in feature measurement. Results show that surface proximity is the most influential factor on fatigue life, with near-surface defects degrading performance for HT specimens with lack-of-fusion (LOF) defects. For HIP specimens, failure sources were typically within 0.16–0.6 mm from the surface. Additionally, for LOF defects the X -parameter model achieved R 2 = 0 . 9 1 with measured cycles to failure. Supplementary Material File (ffems___ti6al4v_fatigue_life_ml_prediction.pdf) Download 2.67 MB Information & Authors Information Version history V1 Version 1 09 January 2025 Peer review timeline Published Fatigue & Fracture of Engineering Materials & Structures Version of Record 18 Sep 2025 Published Copyright This work is licensed under a Non Exclusive No Reuse License. Collection Fatigue & Fracture of Engineering Materials & Structures Keywords additive materials defect assessment fractography high cycle fatigue Authors Affiliations Ro’i Lang 0009-0001-9176-4561 [email protected] Ariel University View all articles by this author Or Haim Anidjar Ariel University View all articles by this author Sahar Slonimsky Ariel University View all articles by this author Chen Hajaj Ariel University View all articles by this author Oz Golan Afeka College of Engineering View all articles by this author Carmel Matias Israel Aerospace Industries Ltd View all articles by this author Alex Diskin Israel Aerospace Industries Ltd View all articles by this author Strokin Evgeny Technion Israel Institute of Technology View all articles by this author Mor Mega Ariel University View all articles by this author Metrics & Citations Metrics Article Usage 381 views 218 downloads .FvxKWukQNSOunydq8rnd { width: 100px; } Citations Download citation Ro’i Lang, Or Haim Anidjar, Sahar Slonimsky, et al. Measuring and analyzing defects of Additive Manufactured Ti-6Al-4V Specimens through Image Segmentation. Authorea . 09 January 2025. DOI: https://doi.org/10.22541/au.173641900.06597179/v1 If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download. For more information or tips please see 'Downloading to a citation manager' in the Help menu . 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