{"id":10,"date":"2020-03-31T09:50:26","date_gmt":"2020-03-31T13:50:26","guid":{"rendered":"https:\/\/blogs.sw.siemens.com\/additive\/?p=10"},"modified":"2026-03-26T14:58:56","modified_gmt":"2026-03-26T18:58:56","slug":"mightyduct-optimization","status":"publish","type":"post","link":"https:\/\/blogs.sw.siemens.com\/additive\/mightyduct-optimization\/","title":{"rendered":"Next-Level Optimization for Additive Manufacturing"},"content":{"rendered":"\n

Is your \u201coptimized\u201d\npart REALLY optimized?<\/strong><\/p>\n\n\n\n

One promising technology that has come into its own in the\nera of 3D printing is design optimization. \nIn the past, design optimization was used sparingly because it often\nresults in parts with complex b-surfaces or complex internal geometries.  However, the nature of 3D printing allows companies\nto manufacture parts with highly complex geometries with lower cost than is\nusually possible using other manufacturing methods.  This means that the complex b-surfaces and\nshapes that result from optimization can often be printed with little increase\nover the cost of printing the non-optimized part.  But how do you know your \u201coptimized\u201d part is fully<\/em> optimized?  Have you thought about optimizing for more\nthan just a single goal?  It might be\npossible to squeeze even more efficiency out of your \u201coptimized\u201d parts if you\nthink about optimization as a multi-level or multi-objective process.<\/p>\n\n\n\n

Optimizing for\ndollars<\/strong><\/p>\n\n\n\n

\"Combining
HP combined six parts into one to save cost – Part courtesy HP<\/figcaption><\/figure><\/div>\n\n\n\n

One way that companies are optimizing their\ndesigns is by combining multiple parts or assemblies into a single part.  This act of combining multiple parts into a\nsingle part often results in a final part of increased geometrical complexity\nwhen compared against any of the original constituent parts.  However, part complexity is not a problem for\n3D printing.  In fact, it is often the\ncase that assemblies were created, instead of single parts, specifically\nbecause manufacturing the assembly as a single part would have been difficult\nor impossible using traditional methods.<\/p>\n\n\n\n

One example of part consolidation is a duct design from\nHP.  HP took an assembly that would have been\nsix individual injection molded parts and combined them into one printed part.  The cost analysis they did on this part told\nthem that they could achieve a 34.3% cost reduction by printing the assembly as\na single part.  Through this example we\ncan see that part consolidation is one way that you can optimize a design, in\nthis case for cost.<\/p>\n\n\n\n

Optimizing for efficiency<\/strong><\/p>\n\n\n\n

\"Two
The original duct part and the optimized version – Original part courtesy HP<\/figcaption><\/figure><\/div>\n\n\n\n

Part consolidation is only one way a\ndesign can be optimized, however. \nSiemens and HP also worked together on a new example of how a part can\nbe topology optimized for better fluid flow characteristics.  This entirely new take on an old idea brings\nabout new opportunities for optimization of parts with fluid channels like air\nducts, piping and tubing, and cooling channels in molds.  HP and Siemens used a combination of NX, Star\nCCM+, and HP Jet Fusion printing to create a new version of the HP duct we call\nthe \u201cMighty Duct\u201d part, achieving a 22% flow increase to the system as a\nresult.  This second layer of\noptimization was performed on top of the part consolidation optimization that achieved\nthe 34.3% cost reduction.  In this case,\nthese two layers of optimization did not contradict one another and the sum of\nthe two optimizations was much greater than either single optimization alone.<\/p>\n\n\n\n

Deep optimization<\/strong><\/p>\n\n\n\n

I believe that this type of \u201cdeep optimization\u201d or \u201cmulti-objective\noptimization\u201d, where multiple layers of optimization are applied to a part or a\nsystem, is the next wave of optimization. \nApplying multiple layers of optimization, especially when the layers of\noptimization do not conflict or contradict one another, can result in a part\nthat is more<\/em> optimal than with any\nsingle optimization alone.  As you can\nsee with the Siemens\/HP Mighty Duct example, deep optimization is entirely possible,\nand it is all due to the geometric freedom afforded us by additive\nmanufacturing and by new optimization methods and tools available on the market\ntoday.<\/p>\n\n\n\n

Do you have any experience with optimization? Have you done any multi-objective optimization for 3D printing? Tell us about it in the comments below. <\/p>\n\n\n\n

You can find the whole Mighty Duct story at https:\/\/www.siemens.com\/mightyduct<\/a>.<\/p>\n","protected":false},"excerpt":{"rendered":"

Is your \u201coptimized\u201d part REALLY optimized? One promising technology that has come into its own in the era of 3D…<\/p>\n","protected":false},"author":28801,"featured_media":28,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"spanish_translation":"","french_translation":"","german_translation":"","italian_translation":"","polish_translation":"","japanese_translation":"","chinese_translation":"","footnotes":""},"categories":[107],"tags":[116,117,118,122,124,125,127,128],"industry":[66,72,85,89,106],"product":[],"coauthors":[],"class_list":["post-10","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-customer-success-story","tag-3d-printing","tag-additive-manufacturing","tag-computer-aided-design-cad","tag-design-optimization","tag-digital-transformation","tag-digital-twin","tag-generative-design","tag-industry-4-0","industry-automotive-transportation","industry-consumer-products-retail","industry-energy-utilities","industry-industrial-machinery-heavy-equipment","industry-small-medium-business"],"featured_image_url":"https:\/\/blogs.sw.siemens.com\/wp-content\/uploads\/sites\/30\/2020\/03\/HP-Additive-Printers-Digitalization-1500px.jpg","_links":{"self":[{"href":"https:\/\/blogs.sw.siemens.com\/additive\/wp-json\/wp\/v2\/posts\/10","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/blogs.sw.siemens.com\/additive\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/blogs.sw.siemens.com\/additive\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/blogs.sw.siemens.com\/additive\/wp-json\/wp\/v2\/users\/28801"}],"replies":[{"embeddable":true,"href":"https:\/\/blogs.sw.siemens.com\/additive\/wp-json\/wp\/v2\/comments?post=10"}],"version-history":[{"count":5,"href":"https:\/\/blogs.sw.siemens.com\/additive\/wp-json\/wp\/v2\/posts\/10\/revisions"}],"predecessor-version":[{"id":204,"href":"https:\/\/blogs.sw.siemens.com\/additive\/wp-json\/wp\/v2\/posts\/10\/revisions\/204"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/blogs.sw.siemens.com\/additive\/wp-json\/wp\/v2\/media\/28"}],"wp:attachment":[{"href":"https:\/\/blogs.sw.siemens.com\/additive\/wp-json\/wp\/v2\/media?parent=10"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/blogs.sw.siemens.com\/additive\/wp-json\/wp\/v2\/categories?post=10"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/blogs.sw.siemens.com\/additive\/wp-json\/wp\/v2\/tags?post=10"},{"taxonomy":"industry","embeddable":true,"href":"https:\/\/blogs.sw.siemens.com\/additive\/wp-json\/wp\/v2\/industry?post=10"},{"taxonomy":"product","embeddable":true,"href":"https:\/\/blogs.sw.siemens.com\/additive\/wp-json\/wp\/v2\/product?post=10"},{"taxonomy":"author","embeddable":true,"href":"https:\/\/blogs.sw.siemens.com\/additive\/wp-json\/wp\/v2\/coauthors?post=10"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}