Generative Design employs computational algorithms along with artificial
intelligence and machine learning to mimic nature’s evolutionary processes.
It offers new high-performance design iterations that optimise a product’s
mechanical performance. Engineers can also explore design possibilities
according to part constraints and requirements to deliver a first-time-right
additive manufacturing solution.
While engineers and designers can provide the best starting points, design exploration can quickly build on those parameters and generate the most effective and refined alternatives that we may never have thought possible. The engineering simulation community is now embracing this technology more than ever before.
In the recent nTop Platform 2.24 update, we introduced the topology optimization overhang constraint for Additive Manufacturing. In this blog post, we take a deeper look at the unique capabilities of this new feature and how it allows you to create optimization workflows that are different from every other solution currently in the market.
The more that systems thinking becomes an integral part of how design processes are performed, the more our engineers will examine critically the interaction of the various subsystems and components inherent to an overall system, rather than in an isolated manner. This webinar will look at how model-based design and model-based development can work alongside generative design, powered by pervasive simulation for the entire product team. Is this the next major step that is needed in our industry to design, validate and support our products with advanced integrated systems that have been increasing exponentially in complexity?
The vision for Generative Design is that it could enable a significant paradigm shift in the design processes used today by enabling designs to be computer-generated based on a proper specification of rules, requirements, and constraints. This overturns the current practice of design, where designs must first be created so they can be evaluated against their performance requirements.
Generative Design is the use of algorithmic methods to quickly and automatically, or iteratively, transform requirements, constraints, uncertainties, and design space to create/drive viable designs or outcomes. Requirements, constraints, and uncertainties may include factors from multiple areas including: design, performance, manufacturing, usability, aesthetics, ergonomics, and cost.
This paper provides an assessment of the Generative Design workflow in Autodesk Fusion 360. This assessment is based on the capability assessment model related to the Key Capability Areas of Generative Design for General Applicability and their associated criteria outlined in the intrinSIM Market Report entitled “A Vision for Generative Design”.
“A Vision for Generative Design” is a software independent intrinSIM market research paper that explores the potential paradigm shift enabled by Generative Design and what is required to enable that design paradigm shift. This market research paper looks at the key capability areas required to support a paradigm shift and proposes a capability assessment model with detailed assessment criteria for each of the key capability areas.
The term “generative design” has been used in architecture and civil engineering for more than a decade. It is now gaining currency in the mechanical design (MCAD) world.
CAD programs are ideal for design engineers who need to express their concepts, whether the shape of an automotive part or the housing of a smartphone, in detailed 3D geometry. Dassault Systèmes’ SolidWorks and CATIA, Autodesk Inventor, Siemens PLM Software’s Solid Edge and PTC’s Creo Parametric exemplify such programs.
In today’s design environment, it’s increasingly necessary to combine multiple file types in a single project. If you need to work with parametric, direct and facet modeling within the same project, some CAD platforms require you to move design data across multiple pieces of software.
Generative design replicates natural world's evolutionary approach with cloud computing to provide thousands of solutions to one engineering problem.
Generative design is opening new opportunities for solving design problems — and turning traditional workflows upside down, moving simulation ahead of model creation. Understanding the basics of the technology can help you decide if it’s time to share your AEC or MCAD workload with generative design tools.
To complement this issue on generative design, Ian Symington, NAFEMS Technical Officer, reached out to members of the NAFEMS Vendor Network nafe.ms/vendor to get their thoughts on the topic.
Topology Optimization that accounts for Additive Manufacturing constraints is a solid beginning for Generative Design. But Generative Design is more than this and may include multiple forms of
Design Optimization.
A presentation by CIMdata's Dr. Keith Meintjes at the 2018 CAASE conference.
A Digital Engineering Webcast from November, 2018.
This presentation illustrates the Generative Design requirements assessment using the ASSESS assessment model and intrinSIM quantification method.
From CAASE 20: The vision for Generative Design is to enable a significant paradigm shift in the current design processes through the creation of algorithmically-generated designs by Design Engineers in the early concept design stage.
Generative Design is an innovation that significantly alters this way of thinking. It leverages topology optimization, artificial intelligence, and advanced simulation which automatically creates multiple viable design alternatives by specifying simple design criteria.
Generative Design is a holistic methodology that augments the capabilities of engineers with digital tools, enabling them to innovate faster. In this 20+ page guide, we explain how you can use nTop Platform as a powerful Generative Design toolbox that gives you complete control over every aspect of your design workflows.
Generative Design is getting a lot of attention — but what is it exactly? Here is why the current Generative Design concepts fall short and how nTop’s alternative approach enables you to unlock its full potential today.
Smart algorithms won’t just lead to better products—they could redefine how product development is done.
This article focuses on the application of Generative Design to mechanical engineering. Note that Generative Design also refers to the autonomous generation of electrical schematics based on diagrams, as well as placing components and routing traces through circuit boards that are based on diagrams.
In this speaker series, experts in the field of Design for Additive Manufacturing will discuss applications for metal 3D printing and the constant trade off between engineering requirements and design for the manufacturing process.
Ian Symington, NAFEMS Technical Officer, reached out to members of the NAFEMS Vendor Network nafe.ms/vendor to get their thoughts on Generative Design.
Whitepaper by Chad Jackson, analyst, researcher and
blogger with Lifecycle Insights
