Avant-garde CAD: Generative Design

Abstract

With the advent of Additive Manufacturing (AM), it is possible to realize complex shapes and structures which would have been difficult to manufacture by conventional processes, therefore AM offers an unprecedented morphological freedom. It enables a wider diffusion of Generative Design (GD), a design approach empowered by advanced computation, allowing the designer to define initial constraints and objectives, then instruct an algorithm to generate numerous variations and optimize the design until the desired solution is achieved. The idea of generative potential was present already at the birth of CAD over half a century ago, but emerged mainly in the past decade through widely publicized experimental research projects both in academy and in the private sector. GD is expected to spread across various industries due to advantages including optimized weight and mechanical performance, better use of raw materials, but also because it enhances the creative process by helping designers to explore solutions in a brief timeframe. The paper starts with describing the place of GD in the evolution of CAD, then it outlines current technological directions, including topology optimization, morphogenesis and biomimicry. Afterwards we examine how the design research community and design professionals use GD to achieve various goals, with a particular attention on transportation design. Finally, the study concludes by observing how the designer’s role is shifting towards being a “curator” of input data and output geometry, with the consequence that they will need to adapt their tools and their skills.

Presenters

Sarvpriya Raj Kumar
Student, Master of Science, University of Rome "La Sapienza", Lazio, Italy

Viktor Malakuczi
Assistant Professor, Department PDTA, Sapienza University of Rome, Roma, Italy

Details

Presentation Type

Paper Presentation in a Themed Session

Theme

2021 Special Focus: Towards a (Design) New Deal

KEYWORDS

Generative Design, Additive Manufacturing, Innovation, Lightweight, Optimization