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You are here: Home / 3D Printing Case Studies / SolidThinking Case Study: Mountain Bicycles and Additive Manufacturing

SolidThinking Case Study: Mountain Bicycles and Additive Manufacturing

by Rapid 3D

Robot Bike Company (RBC) is a start-up established in the UK by aerospace engineers and mountain biking enthusiasts.

When creating the company, RBC’s founders identified the potential of combining additive manufacturing technologies with carbon fiber too. RBC’s goal is to use additive manufacturing (AM) technologies to create very high-end mountain bikes that are tailored to an individual’s weight, height, and riding style.
Although the team at RBC had considerable experience in additive manufacturing and developing products, it required multiple partnerships.
Robot-bike-company-new-design (2)The team approached HiETA Technologies, a specialist in design and engineering solutions for additive manufacturing technologies.
Renishaw, a leading developer of additive manufacturing machinery, and Altair ProductDesign, were given the role of ensuring that the bike took full advantage of the flexibility that additive manufacturing offers.
In recent years, there have been several interesting examples where 3D printing or additive manufacturing have been employed in the bike industry.
RBC’s goal for the project was to design and manufacture a fully customizable product that could be sold online to the public.
AM is an exciting proposition to bike manufacturers as it has huge potential to allow for greater customization.
However, designing bikes that take full advantage of the technology is a challenge that requires a great range of engineering and design specialties.
To deliver on its promise of a lightweight, high strength bike, RBC’s frame was intended to be created from carbon fiber, a material very common in the industry.
The carbon fiber tubes, as well as the bike’s other components and systems were joined by additively manufactured titanium ‘nodes’, manufactured based on the specification of individual riders (height, weight, riding style, etc.).
Altair Product Design’s engineering team was tasked with designing these joints, which included the head tube, seat post, and chain stay lugs.
The goal for these parts was to ensure they were as lightweight as possible, yet still able to withstand the forces of downhill mountain bike riding.

SOLIDTHINKING INSPIRE AND EVOLVE IN THE DESIGN PROCESS

Altair ProductDesign’s first task was to perform optimization studies on each of the nodes to find a material efficient design that met the required performance characteristics and could be sized for different riders’ specifications.
Robot-bike-company-new-design (1)To find an optimal design solution as early in the design process as possible, Altair ProductDesign utilized solidThinking Inspire.
The technology allowed the team to quickly take the existing designs into the virtual environment.
SolidThinking Inspire used this data to output a new geometry that maximized the efficiency of the material layout while still achieving all performance targets.
Throughout this process, the new designs had to be optimized for the AM process which included determining the ideal print angle and placement of the supporting structure.
This process was conducted in conjunction with HiETA Technologies.
In addition to designing weight efficient components, Altair ProductDesign was also able to look for opportunities to simplify the frame design to lower the cost of production. Utilizing both solidThinking’s Inspire for optimization, and Evolve for final part refinement.
The team was even able to build in the additive manufacturing requirements from HiETA Technologies, to redesign the lug as a single component, optimized for mass, performance, and manufacturing cost.
The optimization work conducted by Altair ProductDesign successfully delivered mass optimized designs for the additively manufactured titanium frame nodes.
The new material layout, driven by solidThinking Inspire and interpreted with solidThinking Evolve, created innovative, organic looking design solutions which were highly optimized for AM.

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