The Dys-functional Mug
Algorithimic forms for daily function.
The dysfunctional mug is a computational design project that is situated between two halves - that of man and machine design. It is a commentary on
the relationships we share with our daily objects. The mug, generatively
designed with a growth algorithm, although unique, is not functional.
What happens when some objects we are so familiar with - functionally and visually - become unfamiliar? What happens if the algorithm takes over a design process and embraces fallacies?
What happens when some objects we are so familiar with - functionally and visually - become unfamiliar? What happens if the algorithm takes over a design process and embraces fallacies?
CONCEPT FORMATION
A mug which looks like a mug, but doesn’t quiet function like one. I realized early on that my hands, by the virtue of my brain, will not be able to satisfactorily create a dysfunction. I decided to give up the design agency to an algorithm inturn revealing an unpredictable growth pattern, which to stop, I would have to intervene.
A mug which looks like a mug, but doesn’t quiet function like one. I realized early on that my hands, by the virtue of my brain, will not be able to satisfactorily create a dysfunction. I decided to give up the design agency to an algorithm inturn revealing an unpredictable growth pattern, which to stop, I would have to intervene.
ALGORITHM IN ACTION
Differential line growth algorithm was used to achieve the form. I start with a simple shape made of points, circles or lines. New nodes are then introduced in between existing pairs of nodes at random. In every subsequent iteration, the nodes try to find a perfect position for themselves - to not be too far from their neighbours nor be too close.
The jagged drinking edge makes it impossible for someone to drink comfortably. Had I stopped running the algorithm a few stages before, it would be perfect, but that is not the point here. As soon as I programmed an autonomous algorihtm to do the design, I let go my ideas of what works and what doesn’t. The machine doesn’t know when to stop, or when to start. Man defines those two points - what happens in between, is a story in it’s own.
Differential line growth algorithm was used to achieve the form. I start with a simple shape made of points, circles or lines. New nodes are then introduced in between existing pairs of nodes at random. In every subsequent iteration, the nodes try to find a perfect position for themselves - to not be too far from their neighbours nor be too close.
The jagged drinking edge makes it impossible for someone to drink comfortably. Had I stopped running the algorithm a few stages before, it would be perfect, but that is not the point here. As soon as I programmed an autonomous algorihtm to do the design, I let go my ideas of what works and what doesn’t. The machine doesn’t know when to stop, or when to start. Man defines those two points - what happens in between, is a story in it’s own.
