{"title":"Multiscale basis modeling of 3D melt-pool morphological variations for manufacturing process monitoring","authors":"","doi":"10.1007/s00170-024-13377-2","DOIUrl":null,"url":null,"abstract":"<h3>Abstract</h3> <p>Laser powder bed fusion is a key technology of additive manufacturing that enables the fabrication of metal parts with complex geometry through a multilayer process. Despite its great promise in design flexibility, wide application of this technology is hindered by a lack of quality assurance in fabrication parts. Melt-pool morphological characteristics are eminent indicators for manufacturing process stability and part quality. However, existing studies on melt-pool morphology focused on key geometric properties (e.g., length, width, size) extracted from melt-pool images for characterizing its variations, and tend to overlook 3D morphological variations of melt pools and ejected spatters. In this paper, we develop a multiscale modeling framework to represent, characterize, and monitor melt-pool variations through 3D morphological features, including multiscale basis function modeling of 3D melt-pool morphology and an iterative search of predominant components for sparse representation of morphological variations in melt-pool images. A case study with real-world experimental data shows that the proposed framework effectively characterizes 3D melt-pool morphological variations and provides salient features for tracking process variations, predicting melt-pool sizes, and detecting spatters. This framework is generally flexible for a wide variety of additive manufacturing (AM)applications such as melt-pool simulation, process monitoring, and anomaly detection.</p>","PeriodicalId":50345,"journal":{"name":"International Journal of Advanced Manufacturing Technology","volume":"42 1","pages":""},"PeriodicalIF":2.9000,"publicationDate":"2024-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Advanced Manufacturing Technology","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.1007/s00170-024-13377-2","RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"AUTOMATION & CONTROL SYSTEMS","Score":null,"Total":0}
引用次数: 0
Abstract
Laser powder bed fusion is a key technology of additive manufacturing that enables the fabrication of metal parts with complex geometry through a multilayer process. Despite its great promise in design flexibility, wide application of this technology is hindered by a lack of quality assurance in fabrication parts. Melt-pool morphological characteristics are eminent indicators for manufacturing process stability and part quality. However, existing studies on melt-pool morphology focused on key geometric properties (e.g., length, width, size) extracted from melt-pool images for characterizing its variations, and tend to overlook 3D morphological variations of melt pools and ejected spatters. In this paper, we develop a multiscale modeling framework to represent, characterize, and monitor melt-pool variations through 3D morphological features, including multiscale basis function modeling of 3D melt-pool morphology and an iterative search of predominant components for sparse representation of morphological variations in melt-pool images. A case study with real-world experimental data shows that the proposed framework effectively characterizes 3D melt-pool morphological variations and provides salient features for tracking process variations, predicting melt-pool sizes, and detecting spatters. This framework is generally flexible for a wide variety of additive manufacturing (AM)applications such as melt-pool simulation, process monitoring, and anomaly detection.
期刊介绍：
The International Journal of Advanced Manufacturing Technology bridges the gap between pure research journals and the more practical publications on advanced manufacturing and systems. It therefore provides an outstanding forum for papers covering applications-based research topics relevant to manufacturing processes, machines and process integration.
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