Additive Manufacturing is finally at the point where it’s possible to mass produce parts with cosmetic (Class A) surface finishes. This opens countless opportunities for consumer goods.
One of the main advantages of 3D printing is that every part can be different. This allows the use of data to drive the design. This data can come from many places; some examples are body measurements, force requirements or even weather patterns.
The following are some examples of parametric design techniques that can be used for computational implementation.
1. Procedural textures.
Every part can have its own unique texture, individually designed for, or by each customer. Imagine textures that come from the users unique characteristics, like their skin pattern, finger prints or even on a cellular level? This can add functionality, such as grip, or something decorative that’s personalized on a mass scale. Unlike injection molding, the designer has complete control over the texture design and density, there are no limits.
2. Parametric surface texture patterns.
There are also no limits to the application of surface designs onto 3D printed parts. Unlike injection molding, you don’t need to worry about the constraints of draft angles and part release - 360 degrees of a surface can be patterned in any direction.
This attention to detail adds design quality and gives the opportunity to target the product to an exact market segment or demographic.
As a functional example; data can be used to allow larger holes where airflow is required, or a smaller pattern to add strength to certain areas.
4. Lattice modelling.
Lattices are predominantly used for light weighting parts, but also offer interesting surface finishes. Traditionally parts are molded as a solid volume. However in nature, structures such as bones are not solid, they are made from intricate lattices. For the first time, we have the opportunity to design the properties of a volume, to perfectly meet the functional requirements.
This design approach is unique to 3D printing and can already be seen in sneaker soles and bike seats. But the opportunities are endless..
The images run in the order below:
Periodic Beam Lattices
Made from beams joined together in different configurations. Good for light weight structures. Also great for pressure absorption and energy transfer when used with a Polyurethane material (TPU). Often used for the soles of running shoes - Adidas 4d Futurecraft 💚
Conformal Surface Lattice
This is based on giving a thickness to the surface mesh lines. It can be used as a wall thickness or Boolean to a solid to make a texture. When you change the mesh format the lattice will follow creating some super interesting patterns.
TPMS Lattice
Triply periodic minimal surface (TPMS). These are lattices made from surfaces, they are good for accurately channeling heat within a small area. Used for heat exchanges etc. but also good for light weighting parts as they are very stiff in all directions. I think these are also nice to use just as a texture pattern.
Stochastic Delaunay
Creates a lattice from a random list of points within a volume. Delaunay has similar properties to Voronoi but as it is made from triangles it tends to be stiffer.
Stochastic Voronoi
This is naturally found in the structure of bones, so it’s perfect for designing medical implants. When printed in TPU its also great as a 3D printed foam. You can easily manipulate the cell size and control the density to mass customize parts to individually fit users.
Periodic Honeycomb Lattice
A honeycomb is most commonly made from extruded polygons. They have very high stiffness in the direction of the extrusion. If used in the right way, it should have the best strength to weight ratio of all the lattices. If you don’t believe me, ask a bee..
Infill lattices.
An example of an infill lattice structure - this design dramatically increases the strength to weight ratio.
This could well be the strongest and lightest bottle opener in the world ;)
Topography Optimization - Data driven lattice design.
Data is used to increase the density in areas where more strength or elasticity is required.
This can be large scale, as per the examples below, or on a micro level to control the properties of foam like structures.
Topography Optimization - Data driven lattice design.
Here, shapes are merged from a solid to a lattice structure. For applications where a part needs to be stiff in one area and flexible in another. Or smooth and rough for example. 3D printing the parts allow you to have single parts with different properties, where historically you’d have to fix two parts together.
Organic growth simulations.
Growth simulations are often used in video game or animation to replicate organic forms. We can make use of this technology to mass produce organic forms that are completely unique from each other. These are conceptual examples of solid volumes produced with growth simulation data.
This gives us the opportunity to take a dramatic departure from the simple generic formfactors we see everywhere today.
Organic growth simulations.
Further experiments, using growth simulation data to creates forms to fit the body. The parametric data comes from from body scans and the organic lattices are grown to fit the parts.
Topography optimization.
The aim of this exercise is to create furniture pieces using the minimum amount of material. Starting with solid shapes, we simulate a force being applied to the top of the volume. The perfect shape is created to meet the weight requirement, using the least amount of material.
This is made possible as we can 3D print any shape, so there are no limitations.
Generative design.
Using generative software, we specify the outer and inner rim of the wheel. By running a force simulation a perfect shape is produced, using the minimum amount of material.
Computer generated shapes are surprisingly similar to those found in nature. Imagine this approach applied to other products!
Please check out my Instagram page for more work examples: Nik_3D