CLUSTER 2: The Detergent Bottle as Building Block: From Geometry to Pattern to Surface Structure

In this part of our ongoing exploration into how detergent bottles can become building blocks, we return to the idea of designing the shape of the bottle. Not by changing the form in complex ways, but by applying what we’ve learned from space-filling geometry.
Instead of completely transforming the bottle, we focused on minimal modifications, while making it suitable for a second life as a modular element.

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CLUSTER 2: The Detergent Bottle as Building Block: Exploring Interlocking, Puzzle Logic, and Shape-Driven Reuse 

Learning from the WOBO bottle – (you can read more in our previous blog post) – we were fascinated by how the design embedded reuse directly into the form of the packaging.
We’ve been exploring the idea of giving packaging not just a second life through recycling, but a second function through design. This led us to experiment with how detergent bottles could be transformed into interlocking, modular components, inspired by Japanese joinery, 3D puzzle logic.

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Cluster 3: Space Filling Geometry Systems – Approximating Artefacts Through Geometry

In this phase of the project, we’ve shifted our perspective. Until now, the physical experiments revolved around pressing artefacts into a predefined geometric mold. Specifically, we worked with the Peter Pearce’s Curved Space System, using saddle pentagons to form a continuous surface. This approach treated geometry as the fixed system, and artefacts as materials to be adapted. But what if we turned the concept around?

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clustering of an inventory

Applying a clustering algorithm to an inventory of irregular unique objects can help to reduce the complexity involved in designing with such parts significantly. By dividing the inventory items into groups with similar characteristics, each group can then be represented by one “proto-part” instead, therefore reducing the amount of unique elements to be handled in setting up aggregation logics and the aggregation processes.
The decision about the number of different groups (Fig. 1) can be completely left to an algorithm (depending on various predefined – by the programmer – conditions) or be manually determined by the user/designer.

Fig. 1: clustering of inventory with different amounts of groups (“proto-parts”)
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