Artificial Intelligence (AI) and generative design (GD) are transforming the architecture, engineering, and construction industry toward a more efficient design process. But is the built environment in danger of losing social and equity values as a result? The powerful combination of GD and Generative Artificial Intelligence (GAI) has the potential to assist architects in improving building functionality and sustainability, enhancing value for architects, developers, and residents. However, ethical and social sustainability values may be overlooked if the metrics of the GD and GAI are not instructed to identify and prioritize them. This class will combine findings from a multidisciplinary research project from Carnegie Mellon University, and real-life architectural projects by HED. Learn how to prioritize important equity and social sustainability values in human-in-the-loop AI powered design frameworks, making ethical and socio-sustainable design decisions measurable and transparent to all stakeholders, for a more equitable and resilient built environment.

This roundtable discussion will explore the power of computational design in promoting sustainable development. We'll provide practical knowledge of the tools and techniques used to implement circular design principles, and we'll evaluate the ethical and social implications of using data analytics and modeling to evaluate the environmental impact of design decisions. This topic highlights the importance of resource conservation and regeneration and promotes a more sustainable future. The concept of the circular economy has gained momentum in recent years as a more sustainable and efficient model for resource use. In this context, computational design has emerged as a key enabler of the circular economy by optimizing material usage and reducing waste.

This class will give users a look at the future of Inventor Connected Design beyond Inventor 2017.  Users who need to collaborate and share their Inventor designs will see how Connected Design is evolving to leverage A360 Team for secure viewing, markup and commenting with non-Inventor users. This session features Inventor Professional and A360 Team.

In the architecture, engineering, and construction (AEC) industry, we are challenged to consider many design options, to find the fittest solution in the shortest time, and to be leaders in economic and sustainable designs. During this presentation, you’ll learn about how computational design techniques can help you improve your design process for buildings. In this class, you’ll discover how our products generate better outcomes for designs using computational and generative design techniques. You’ll get an overview of how ‘traditional" design improves with design automation, computational modeling, and generative design methods with Dynamo and Refinery. All of this will be taught using examples from the architectural, urban planning, and structural industry.

Generative design is often seen as a new design methodology. However, the key principles of the process mirror the fundamentals of design. In this class, we'll present a case study of how generative design is being used at University College London (UCL) to reinforce the core design curriculum through industrially relevant technology. During this class, you'll gain an understanding of the generative design process, see how you can apply it in an educational setting, and evaluate its use through a real-world example. We'll explore how we can use generative design for multiobjective optimization, and how this can be turned into a hands-on graded assignment that forces students to consider real-world requirements. This will include evaluations of student submissions and analysis of how effective this assignment was at teaching the principles of design, as well as course materials for you to take away and use while running similar teaching exercises.

This industry talk will provide attendees with an inside look at how Innovation Forge is utilizing Generative Design to break barriers in engineering problem solving. Often times, there are additional engineering criteria other than mass and mechanical loading which must be included in the overall development of a design. Aesthetic qualities, surface area, flow characteristics (both internal and external), and manufacturing methods are just some of the additional criteria that will be explored in this course. Attendees will be presented with tips and tricks to achieve the best results for the given design requirements and follow through multiple real-world examples of how Autodesk Generative Design is able to contribute to a much larger design process. To round out the session, attendees will be presented with areas of research to further aid in problem setup and generation.

Generative Design is changing how designers and engineers bring new products to market. By leading with objectives and functional requirements, Generative Design allows users to rapidly generate and explore 100’s or 1000’s of higher performing design options that would have been previously unexplored. What’s new to many – is that the value of Generative Design is not exclusive to the aerospace industry and additive manufacturing. Generative Design now has the ability to explore options for traditional manufacturing techniques as well like CNC, and provide inspiration for casting. TB Wood’s is a recognized industry leader for highly-engineered industrial machinery applications. TB Wood’s has been producing commercial castings for over 160 years, while being a global leader in the design and manufacture of couplings and belted drive solutions. Join Autodesk & TB Wood’s for an overview on how to connect the benefits of Generative Design with the industrial machinery industry.

This hands-on lab will allow users to get some hands-on time with generative design. We will cover how to define a generative design study from scratch, apply loads, constraints, and manufacturing methods. Once completed, we will explore the results and export an outcome and then use the innovate tools with Fusion 360 to adjust the design to suit the manufacturing method we would like to use. We will cover 2 example through the workshop, one focused around manufacturing products and the other around building products.

In this session, we’ll discuss how design for additive manufacture (DFAM) can influence the performance of additively manufactured parts. This session will focus primarily on laser powder-bed fusion, but concepts can be transferable to other additive techniques. We’ll explore lattices, hollow geometries, and thin walls as common features in lightweight designs, including the challenges that these can pose in design, post processing, and actual performance. Autodesk Research is currently undertaking research to characterize how as-built features perform (mechanically) compared to idealized conditions—generic bulk-material values found in literature. This will enable better representation of these features at the design stage to facilitate more accurate simulation and optimization. Attendees will leave more familiar with DFAM, considerations during the design process, and the impacts these have on overall part performance.

Generative design is often seen as an alien parts generator. In this session, we will share how we incorporated this design exploration method into our traditional design process, and how we applied the method on a very typical welded parts assembly of an automatic tools changer on a CNC machine tool. With no specific expectations, as we believed it was already fully optimized, we achieved almost 20% of mass reduction, positively impacting the overall machine precision. And as a side benefit—we got really good-looking parts. You'll learn which selection method we used to identify potential parts for generative design and how we defined the success criteria. We'll cover the whole process, from multiple designs exploration up to production and installation itself. We'll also discuss our generative design rollout plan.

Engineers and designers face an internal struggle when choosing between traditional design methods engrained through years of practice and new Generative Design workflows. Simply applying traditional design methods to Generative Design tools often leads to insufficient results which can be used for inspiration, but are not ready for manufacture. This hands-on lab will bridge the gap between traditional and Generative Design workflows, empowering users to complete the design process by leveraging Generative Design in powerful ways. Attendees will leverage Autodesk Generative Design alongside Meshmixer, Netfabb, Fusion 360, and Nastran to create a finished product, while exploring workflows which greatly improve productivity.

Contemporary shifts in technology and environmental concerns are changing the circumstances of building performance. Integrated teams that employ interdisciplinary design and construction personnel are responding to this changed set of conditions. The foundation of interdisciplinary architectural, engineering, and construction (AEC) practices begins with the education of the next generation of AEC practitioners. In this class, we will discuss how students engaged in an iterative design and learning process build knowledge and communication skills toward an integrated design-build studio. This integrated design-build studio uses a series of assignments housed in dedicated design labs where students solve realistic design problems. Faculty-implemented Building Information Modeling (BIM) technologies and established ecological accounting methods increase interaction and innovation in the interdisciplinary design-build studio.

This class will expand your learning with VRED Design and introduce you to preparing a scene to use in virtual reality. We will cover scene considerations, data optimisation, and workflows to utilise VR for design review with animation, interactions, and collaboration. We will show how to utilise VRED presenter as a platform to share your visual rich interactive designs.

Traditionally, design decisions are made and solutions are developed before understanding the potential outcomes of those decisions. We then validate the solutions, revise decisions, and redesign, creating massive waste in the process. This is the paradox of design. Design optimization techniques and technology (APIs, visual programming, and simulation tools) can help break this paradox by simulating many options and the potential outcomes—informing decisions rather than simply validating them after the fact. This technology will change how we design, much like the advent of Building Information Modeling (BIM) did a decade ago. Therefore, it is critical to understand the fundamental changes to the design process that will be necessary to capitalize on this new technology. This round-table discussion will explore the paradox of design, as well as the challenges of design optimization, lean design processes, simulation technology, and computational design.

The demand for medical devices is rapidly growing with a forecast of global annual sales to reach nearly US$800 billion by 2030. But a one-size-fits-all approach in surgery often results in major complications such as infection, delayed or incomplete healing, and revision surgeries that contribute to diminishing clinical outcomes. A new approach with design thinking is now necessary to help solve these challenges. Researchers at University of Birmingham, Autodesk, Manufacturing Technology Centre (UK), and the University Hospitals Birmingham NHS Trust have developed a novel design framework to create personalized knee implants from a CT scan using generative design for treating arthritis. This class will showcase how generative design can be implemented in an all-encompassing digital workflow to explore customized devices and make a positive impact to improve patient outcomes. The team will also discuss the fabrication of functional prototypes using cutting-edge manufacturing, post-processing, and validation techniques.

An increasing number of designers, architects, and engineers are using graph-based visual programming and scripting techniques to generate and optimize design solutions. The Design Computation Symposium is a forum for presenting the results of this new approach to design and for discussing the development and use of computational design tools. With conventional computer-aided design, the designer uses interactive and direct modeling techniques to create or edit the design. By comparison, a computational designer uses scripting and other graph-based programming techniques. The script essentially captures the logic of the design and its execution generates the design solution, or indeed generates numerous design alternatives. This year's symposium features a number of different presentations from accomplished researchers, practitioners, and educators which focus on the fascinating relationship between logic, geometry, architectural form, analysis, simulation, and digital fabrication.

Unlike generative design for manufacturing, generative design for architecture requires the incorporation of the user’s unique design intents and ideas into the generative model. As most of our work shows—from the Autodesk office at MaRS to the Autodesk University exhibit hall layout, and from urban developments in the Netherlands to housing complexes in Japan—each project’s output looks different because each geometric system has been developed as a combination of the designer’s intent and reusable geometric tools. This session will show how to approach design problems through the generative design framework (problem formulation) with a focus on how to incorporate design intents in the form of geometric systems (model parameterization). Through Dynamo and Refinery, we’ll take a look at and customize a variety of custom geometric tools and test them in real-world case studies: from subdivision logic for office and urban neighborhoods to automated massing strategies and building siting algorithms.

The evolution of design and drafting has increasingly given us tools that inform and expedite our processes. But what can we learn from the implementation of CAD, building information modeling (BIM), and now AI to prepare teams for the future of design tools? Working at a multidisciplinary design firm encompassing planning, landscape, architecture, and interiors has shown me that technology adoption and digital maturity happen at different rates. But regardless of the tools used and efficiency in practice, projects are completed. Focusing on the finished work, lessons learned can become the quantitative outcomes we bring to the beginning of projects in this era of outcome-focused process. By distilling 50+ years of digital asset creation and the analysis of completed projects, we can uncover the potential embedded within our digital archives.