Energy-saving Optimized Parameters for 3D Selective Laser Melting using Dimensionless Model and Machine Learning

Energy-saving Optimized Parameters for 3D Selective Laser Melting using Dimensionless Model and Machine Learning | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Energy-saving Optimized Parameters for 3D Selective Laser Melting using Dimensionless Model and Machine Learning Chung-Yang Hung, Jia-Wei Guo, Yu-Lung Lo, Wei-Bo Liao, Hong-You Lin, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7127180/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract In selective laser melting (SLM), determining the optimal processing parameters, such as laser power, scanning speed, hatching space, etc., often relies on trial-and-error experiments. In this study, the final optimal parameters for SLM of Ti6Al4V were effectively characterized using the dimensionless model, melting pool geometry model, energy-saving index, and maximum hatching space. First, by combining the criteria of an optimization zone from a dimensionless model, the ratio of melting pool, and energy saving, the optimal two parameters in laser power and scanning speed were defined that not only provided excellent mechanical properties in as-built samples but also achieved a green design in manufacturing. As a result, for Ti6Al4V with the hatching space of 80 µm, an impressive relative density of 99.977% was achieved, with the tensile strength reaching approximately 1201 MPa, the yield strength reaching 1171 MPa, and the elongation rate reaching 8.2%. Subsequently, the corresponding maximum hatching space of up to 120 µm was achieved by a novel methodology proposed by our group. As a result, the energy saving was much improved to 33.4%, and the relative density of 99.948% was still held compared to the case with the hatching space of 80 µm. It is concluded that this novel approach, with an optimal parameter set in laser power and scanning speed based upon the dimensionless model, melting pool geometry, energy saving, and its corresponding maximum hatching space, can effectively minimize energy consumption and maximize throughput while still maintaining the superior mechanical qualities of the as-built samples. Dimensionless Selective Laser Melting Optimization Energy Saving Full Text Additional Declarations No competing interests reported. Supplementary Files Highlights.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7127180","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":551520948,"identity":"8897df78-5d42-4e38-88f6-eb5697527863","order_by":0,"name":"Chung-Yang Hung","email":"","orcid":"","institution":"National Cheng Kung University","correspondingAuthor":false,"prefix":"","firstName":"Chung-Yang","middleName":"","lastName":"Hung","suffix":""},{"id":551520949,"identity":"36f86936-4f58-4417-ad7c-4dc53db9c56f","order_by":1,"name":"Jia-Wei Guo","email":"","orcid":"","institution":"National Cheng Kung 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In this study, the final optimal parameters for SLM of Ti6Al4V were effectively characterized using the dimensionless model, melting pool geometry model, energy-saving index, and maximum hatching space. First, by combining the criteria of an optimization zone from a dimensionless model, the ratio of melting pool, and energy saving, the optimal two parameters in laser power and scanning speed were defined that not only provided excellent mechanical properties in as-built samples but also achieved a green design in manufacturing. As a result, for Ti6Al4V with the hatching space of 80 \u0026micro;m, an impressive relative density of 99.977% was achieved, with the tensile strength reaching approximately 1201 MPa, the yield strength reaching 1171 MPa, and the elongation rate reaching 8.2%. Subsequently, the corresponding maximum hatching space of up to 120 \u0026micro;m was achieved by a novel methodology proposed by our group. 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