Performance-driven generative design methods are capable of producing concepts and stimulating solutions based on robust and rigorous models of design conditions and performance criteria. Using generative methods, the computer becomes a design generator in addition to its more conventional role as draftsperson, visualizor, data checker and performance analyst. To enable designers to readily develop meaningful input models, this paper describes a preliminary integration of a generative structural design system, eifForm, and an associative modeling system, Generative Components, through the use of XML models. An example is given involving generation of 20 lightweight, cantilever roof trusses for a saddle shaped stadium roof modeled in Generative Components. Synergies between the two systems and future extensions are discussed.

Towards integrated performance-driven generative design tools

Computer-aided design (CAD) is the use of computer-based software to aid in design modeling, design analysis, design review, and design documentation. Nevertheless, the benefits of CAD can be elevated in combination with artificial intelligence (AI), extended reality, and manufacturing. AI can create an intelligent graphics interface and change tedious design processes into sophisticated ones. In extended reality technology, simulation can take place in a 3D virtual environment, thereby providing excellent interaction and better analysis. In manufacturing, as seen in 3D printing technology, CAD systems can be directly connected to manufacturing to produce complex parts easily and rapidly. In this paper, the integration of artificial intelligence (AI) in CAD, as well as CAD application in extended reality and 3D printing is examined. The primary aim of this review is to present an overview of current state-of-the-art CAD and its applications, as well as to forecast its future prospects. The article is written using a systematic review of journal papers with a focus on a wide spectrum of potentially relevant researches on CAD. The benefits of incorporating AI into the CAD systems, the use of CAD in extended reality and 3D printing, and finally a brief discussion of issues that are pushing CAD to new levels are all discussed. Finally, the review concluded that the demand for several varied products based on a single object input, immersive and interactive simulation, and direct design-to-manufacturing integration is driving CAD to new levels. • Incorporating AI into the CAD system will reduce the lead time dramatically and creates knowledge-based design environment. • Utilizing CAD for 3D printing allows design flexibility, enabling the fabrication of complex items that would be impossible to construct with traditional machining methods. • Through immersive simulation, VR, AR, and MR provide detailed conceptualization of various complicated pro-cuts that exist in the real world. 

Future prospects of computer-aided design (CAD) – A review from the perspective of artificial intelligence (AI), extended reality, and 3D printing

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.

https://www.mdpi.com/2073-431X/9/4/80/pdf

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

A 3D shape generative method for aesthetic product design

Metal additive manufacturing is an emerging technology in the industry and has a great potential. Moreover, new technologies like generative design can maximize this potential by computing complex optimized parts for additive manufacturing solutions. However, there is a lack of methodologies combining both recent and promising technologies. This paper first establishes a state of the art of design for additive manufacturing (DfAM) and generative design methodologies. Then it proposes a generic workflow for generative design tools and it proposes a challenge approach to develop a new DfAM method including generative design tools. Finally, a global 4-step methodology maximizing the potential of generative design and additive manufacturing, the G-DfAM method, is presented and validated through an automotive use case.

/pdf/g-dfam-a-methodological-proposal-of-generative-design-for-3pcdryeqzf.pdf

G-DfAM: a methodological proposal of generative design for additive manufacturing in the automotive industry

A generative design technique for exploring shape variations

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A generative design technique for exploring shape variations