CAM as a Tool for Creative Expression: Informing Digital Fabrication through Human Interaction
Although design as a profession often deals with material artifacts in various scales, the role of the designer has long been defined to be highly conceptual and immaterial. This distinct definition constitutes the basis for today’s design workflow, in which designers are mainly concerned with the representation of the design through drawing and not so much with its materialization through making. Even though the introduction of computer-aided systems enabled faster and more accurate fabrication and representation tools, these systems are far from capturing non-linear and complex design workflow, and the fundamental model of interaction remained the same, merely replicating a more capable drafting board. Building upon precedents in adaptive and interactive fabrication methods, this thesis proposes a design-fabrication workflow where users can actively manipulate the fabricated artifact within design-fabrication workflow. This geometric manipulation can be captured using computer-vision based feedback loop to inform digital representation. By introducing a feedback loop, the proposed workflow captures design intentions introduced by the user using basic geometric decomposition and reconstruction algorithms. Using the updated digital representation, the proposed system can adapt and extrapolate future tool paths to continue fabrication and offers a design hypothesis for the user to evaluate, presenting a range of geometrical potentials. By doing so, this thesis argues that active engagement with materials can enhance creative freedom and inform design decisions, and that creative human agency can coexist along deterministic machines to facilitate creative exploration through making.
This research has been submitted in partial fulfillment of the requirements for the degree of Master of Science in Computational Design and partially funded by Graduate Small project Help (GuSH) Research Grant at Carnegie Mellon University in 2019.
//Advisors: Joshua Bard, Mine Özkar, Daniel Cardoso Llach