China3D printingNet March 8th, self-driving car manufacturer PIX Moving will metal3D printingCombined with generative design inspired by molds to improve automobile production efficiency.
The company’s “C-ZONE 01” end-to-end digital manufacturing plant utilizes large-format DED 3D printingForms of Arc Additive Manufacturing (WAAM) produces its PIXBOT and PIXLOOP autonomous vehicle chassis models.According to PIX, topology optimization and3D printingThe use of has reduced the manufacturing cost by 60% and the delivery time by about 75%.
A PIX spokesperson said: “We believe that what we are doing is contributing to a paradigm shift in the automotive industry. With new tools and vision, we can rebuild the manufacturing and mobility of automobiles.”
PIX designs and manufactures self-driving car chassis products, such as PIXLOOP. The picture is from PIX.
Slime molding algorithm
PIX adopts WAAM for the first time 3D printingThe technology is in 2019, when the company produced a prototype for its first self-driving car chassis. The main challenge was to incorporate WAAM constraints into the generated design workflow. The company tried to use off-the-shelf tools (such as Autodesk Generative Design, PTC Frustum and Altair Inspire) for structural optimization. Although these procedures are very important for conventional manufacturing techniques and even PBF 3D printingBoth are very effective, but it turns out that WAAM requires a stricter parameter set.
In order to overcome this problem, PIX engineers personally designed their own generative design algorithm, which they called the “slime molding algorithm.” The algorithm draws inspiration from the pathfinding capabilities of slime molds in Petri dishes, and the algorithm allows the company to consider WAAM 3D printingAutomatically model its chassis prototype under constraints.
Use generative design3D printingChassis structure
Each design iteration created by the tool undergoes a static finite element analysis (FEA), in which the performance of the structure is evaluated by simulating stress and deformation. Then, a human designer performs the “retouching” and further optimizes the basic model according to the strict constraints of WAAM. Ultimately, it is up to the designer to strike a balance between structural integrity and weight, because reducing material consumption often increases the risk of part deformation.
To this day, this design-oriented3D printingThe workflow still contains most of the PIX production process.The company’s current goal is to realize the next-generation autonomous vehicle chassis structure in large quantities through WAAM.3D printing, The structure has significant parts consolidation, significant weight reduction and minimum delivery time.
PIX’s computational design team wrote: “This is a necessary condition for revolutionizing automobile manufacturing. Since Ford first introduced the assembly line about 100 years ago, automobile manufacturing has not changed much.”
PIX specially designed chassis structure. The picture is from PIX.
Generative design and topology optimization are the main parts of design for additive manufacturing (DfAM), and its use is not limited to the automotive field. In the sporting goods industry,3D printingThe service provider ADDIT・ION used generative design to3D printingA set of topologically optimized snowboard bindings. The straps developed in cooperation with the sports company Nidecker Group provide maximum stiffness and minimum mass.
In other places,3D printingMachine OEM Stratasys recently announced a partnership with engineering software developer nTopology to simplify the DfAM process for fixtures, fixtures and other tools. Specifically, the partners will start with the FDM assembly fixture generator and jointly develop a series of accessible and customizable DfAM programs for users.
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