{"id":9679,"date":"2025-10-14T21:27:35","date_gmt":"2025-10-14T19:27:35","guid":{"rendered":"https:\/\/www.sharebot.it\/?p=9679"},"modified":"2025-10-14T21:30:39","modified_gmt":"2025-10-14T19:30:39","slug":"optimizing-proces","status":"publish","type":"post","link":"https:\/\/www.sharebot.it\/en\/optimizing-proces\/","title":{"rendered":"Optimizing Process Parameters for metal alloy"},"content":{"rendered":"
TECHNICAL WHITE PAPER<\/h5>\n

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Optimizing Process Parameters for Metal Alloy<\/h2>\n

3D Printing Advanced Testing Tools Developed by Sharebot<\/h2>\n

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1. Introduction<\/h3>\n

In the field of metal additive manufacturing (AM), the optimization phase of metal powders and process parameters is critical to achieving components with optimal mechanical and microstructural properties.<\/p>\n

Powder Bed Fusion (PBF-LB\/M)\u00a0technologies\u2014where a laser beam selectively melts thin layers of metal powder\u2014require precise control over the energy parameters governing melting and subsequent solidification.<\/p>\n

Among the most influential parameters are\u00a0laser power (P),\u00a0scan speed (v), and\u00a0focal plane position (z\u2080).<\/p>\n

The combination of these factors determines the amount of energy locally delivered to\u00a0the powder bed, directly affecting part density, melt pool morphology, and residual porosity.<\/p>\n

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2. Process Fundamentals<\/h3>\n

The efficiency of the PBF process is commonly described using Volumetric Energy Density (VED), calculated as:<\/p>\n

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where:<\/p>\n

P\u00a0= laser power (W)<\/p>\n

v\u00a0= scan speed (mm\/s)<\/p>\n

h = hatch distance (mm)<\/p>\n

t\u00a0= layer thickness (mm)<\/p>\n

VED represents the energy input per unit volume and helps predict the degree of material melting.<\/p>\n

Too low VED\u00a0leads to\u00a0lack-of-fusion defects\u00a0and high porosity, while\u00a0excessive VED\u00a0can cause\u00a0melt instability, localized evaporation, or residual stresses.<\/p>\n

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3. Sharebot\u2019s Automated Parametric Testing Function<\/h3>\n

To streamline powder qualification and process optimization, Sharebot has developed an integrated automated parametric testing function within its machine software.<\/p>\n

This tool generates a\u00a0matrix of cubic test specimens, systematically varying\u00a0laser power\u00a0and\u00a0scan speed\u00a0along two axes.<\/p>\n

In a\u00a0single print session, up to\u00a025 test cubes\u00a0(e.g., a 5\u00d75 array) can be produced\u2014each with a unique combination of process parameters.<\/p>\n

The ordered layout enables immediate visual and analytical comparison, simplifying the identification of the\u00a0optimal processing window\u00a0and drastically reducing calibration time.<\/p>\n

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4. Density Characterization<\/h3>\n

The printed specimens can undergo\u00a0hydrostatic density measurement\u00a0based on\u00a0Archimedes\u2019 principle, a method that determines the\u00a0actual density\u00a0of the material.<\/p>\n

By comparing the measured density with the theoretical density of the alloy, researchers can estimate\u00a0residual porosity\u00a0and assess fusion quality.<\/p>\n

Further metallographic analyses (optical microscopy, SEM) and mechanical tests (microhardness, tensile strength) allow correlation between microstructural features and the applied process conditions.<\/p>\n

5. Low-Volume Powder Printing<\/h3>\n

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To support R&D on\u00a0advanced or experimentally formulated alloys, Sharebot has engineered a\u00a0low-volume powder dispensing system.<\/p>\n

This innovative solution enables the production of single 1 cm\u00b3 test cubes using just a few grams of powder, making it ideal for evaluating small lab-scale powder batches.<\/p>\n

This capability significantly reduces development costs and accelerates preliminary validation of novel high-performance alloys for aerospace, medical, and advanced research applications.<\/p>\n

With\u00a0 our metalONE is possible to print a single cube with few powder’s grams to start test !<\/p>\n

6. Conclusions<\/h3>\n

Sharebot\u2019s approach provides an\u00a0efficient and scalable method\u00a0for calibrating process parameters in metal 3D printing.<\/p>\n

By integrating automated parametric testing and low-powder-volume printing, the company reduces experimentation time, optimizes material usage, and fosters the development of innovative materials.<\/p>\n

These tools empower researchers to efficiently explore the\u00a0relationship between process parameters, microstructure, and mechanical properties, opening new pathways for\u00a0high-performance alloy design\u00a0and\u00a0applied research in additive manufacturing.<\/p>\n

Author<\/strong>
\n R&D Department \u2013 Sharebot Srl<\/strong>
\nSpecialists in additive manufacturing technologies and advanced materials development<\/p>\n

metalone@sharebot.it | \u00a0www.sharebot.it<\/p>\n","protected":false},"excerpt":{"rendered":"

TECHNICAL WHITE PAPER   Optimizing Process Parameters for Metal Alloy 3D Printing Advanced Testing Tools Developed by Sharebot   1. Introduction In the field of metal additive manufacturing (AM), the optimization phase of metal powders and process parameters is critical to achieving components with optimal mechanical and microstructural properties. Powder Bed Fusion (PBF-LB\/M)\u00a0technologies\u2014where a laser […]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[50],"tags":[53],"class_list":["post-9679","post","type-post","status-publish","format-standard","hentry","category-metalone","tag-metalone"],"_links":{"self":[{"href":"https:\/\/www.sharebot.it\/en\/wp-json\/wp\/v2\/posts\/9679","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.sharebot.it\/en\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.sharebot.it\/en\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.sharebot.it\/en\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.sharebot.it\/en\/wp-json\/wp\/v2\/comments?post=9679"}],"version-history":[{"count":10,"href":"https:\/\/www.sharebot.it\/en\/wp-json\/wp\/v2\/posts\/9679\/revisions"}],"predecessor-version":[{"id":9693,"href":"https:\/\/www.sharebot.it\/en\/wp-json\/wp\/v2\/posts\/9679\/revisions\/9693"}],"wp:attachment":[{"href":"https:\/\/www.sharebot.it\/en\/wp-json\/wp\/v2\/media?parent=9679"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.sharebot.it\/en\/wp-json\/wp\/v2\/categories?post=9679"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.sharebot.it\/en\/wp-json\/wp\/v2\/tags?post=9679"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}