Progress and Challenges in Generative Product Design: A Review of Systems

Abstract

Design is a challenging task that is crucial to all product development. Advances in design computing may allow machines to move from a supporting role to generators of design content. Generative Design systems produce designs by algorithms and offer the potential for the exploration of vast design spaces, the fostering of creativity, the combination of objective and subjective requirements, and the revolutionary integration of conceptual and detailed design phases. The application of generative methods to the design of discrete, physical, engineered products has not yet been reviewed. This paper reviews the Generative Product Design systems developed since 1998 in order to identify significant approaches and trends. Systems are analyzed according to their primary goal, generative method, the design phase they focus on, whether the generation is automatic or interactive, the number of design options they generate, and the types of design requirements involved in the generation process. Progress using this approach is recognized, and a number of challenges that must be addressed in order to achieve widespread acceptance are identified. Possible solutions are offered, including innovative approaches in Human–Computer Interaction.

What Is Generative in Generative Design Tools? Uncovering Topological Generativity With a C-K Model of Evolutionary Algorithms

“…Self-evidently, GDA operates on a parametrically defined object with constraints on the parameters, which restrict its use in design processes. (Mountstephens and Teo, 2020) proposed to distinguish between autonomous and interactive generative design: in a parametrically defined solution space, autonomous design might sound quite self-evident and generativity could appear only coming from interaction (capacity to use the GDA in a more or less creative way, at varied moments in the design process). Still, maybe counterintuitively, in this paper we first focus precisely on the specific generativity of the algorithm itself, its capacity to generate a collection of varied artefacts.…”

“…We test them on a sample of most recent GDA. This sample was built on GDA recent reviews (Caetano et al, 2020, Mountstephens andTeo, 2020). We hence selected the following methods:…”

Big Data driven Product Design: A Survey

“…Generating new product images based on image data. By reviewing a large amount of literature on generative product design, James and Jason [189] found that deep learning techniques can facilitate product design. Scholars have made some explorations in applying generative models to product design.…”

Exploring Generative Design Thinking for Engineering Design and Design Education

“…Generative design (GD) is a design method that utilizes computational methods and algorithms to generate designs [1]. Under a set of rules and constraints, GD can generate thousands of design options, allowing designers to explore a broader range of the design space to discover new designs compared to traditional design methods.…”

“…It is garnering more attention from both academia and industry. Mountstephens and Teo [1] claim that GD in engineering product design research demonstrates considerable progress and promise. Also, there has been a success in applications of GD in the industry (e.g., Airbus A320 partition redesign [3]), which proves the statement that the time of GD has come with the development of cloud computing and additive manufacturing [4].…”