Hyperganic

18/10/2020

"Why can't I fly to space yet?"

Lin Kayser was invited to speak on Alex Mrozek’s popular German podcast series “Digitale Optimisten”. In this conversation, Lin talks about his entrepreneurial journey, from digitizing Hollywood to transforming manufacturing through A.I. with Hyperganic. If you too are wondering, why you can’t fly into space yet, if you want to know why it’s ok to ignore the naysayers and if you want to get a glimpse of how our future will look like, you should listen to the latest episode of “Digitale Optimisten” (content in German).

Digitale Optimisten | Geschäftsideen, Tech-Talk, Interviews · Episode

18/10/2020

“A DPP is a physical product, a tangible object — but it is conceived, traded and shipped in digital form. At the last mile it is transformed into a physical product. Only late, shortly before it ends up in the hands of the customer, is it actually manufactured.”

The trade magazine Develop3D published an essay by Hyperganic CEO Lin Kayser in their latest print issue, reflecting on the impact of Digital Physical Products on innovation, collaboration and the economy. The magazine is available on newsstands in the UK and the US.

18/10/2020

“Artificial intelligence can only be as creative as the human who thought it to be creative”

Duy-Anh Pham, Co-Founder and Design Director at Hyperganic spoke to Anton Rahlwes, editor in chief of form design magazine about the impact of artificial intelligence to design and creative work. From the changes in the day-to-day work of a designer to the role of aesthetics and creativity in algorithms, this discussion covers inspiring aspects of Hyperganic’s groundbreaking and disruptive technology in the fields of design.

04/08/2020

How will a Digital Physical Product economy foster global collaboration, transform supply chains and jumpstart innovation? In this essay published by Develop 3D, Hyperganic CEO Lin Kayser shares how digital mass production is going to help us change traditional supply chains into a collaborative web that works at the speed of light:

Hyperganic CEO Lin Kayser talks additive manufacturing in mass production, and how Digital Physical Products can boost supply chains and innovation

15/07/2020

On the occasion of todays 3D Pioneers Challenge Digital Award Ceremony, a conversation between Hyperganic Co-Founder and CEO Lin Kayser and designer Ross Lovegrove on a „Paradigm shift in Design" will be streamed today, July 15 2020, 4 p.m. CET:

International competition for additive manufacturing technologies 3DPC - the international platform for pioneers in 3D printing - offers with the competition...

20/05/2020

Lin Kayser, Hyperganic Co-Founder and CEO will host tonight’s episode of "Entrepreneur's Kitchen" by The Mindshift TV
Join Lin in his kitchen on https://buff.ly/3e48fWk at 21:00 CET / 12pm PT / 3pm ET.

06/04/2020

The latest feature on the Hyperganic rocket engine demonstrator on engineering.com:

Hyperganic used Digital Evolution Feedback to “grow” and print rocket engine.

12/03/2020

THE HYPERGANIC A.I. ENGINEERING APPROACH

In the Hyperganic approach you are not designing one object in a linear fashion. Instead, you create a process that results in an object. You are creating DNA, not a blueprint. This process can result in objects that look radically different, depending on your input.

You can evaluate different parameter sets and use techniques like genetic algorithms to explore a vast design space. Feedback, in the form of physical simulation, can then be used as a fitness function to evaluate the performance.

In the Hyperganic ecosystem, geometry can be infinitely complex. We move tiny particles in space, at the resolution of the 3D printer. Where to place each particle is up to the algorithm. There is no limitation to what shapes you can build. Large features with complex curves, but also very small, even microscopic structures.

In Hyperganic A.I. engineering, you constantly regenerate objects from scratch. You generate hundreds or thousands of variants that can be evaluated. In traditional engineering, redesigns are costly and need to be avoided; in Hyperganic engineering, it is the norm and the key to coming up with a global optimum.

11/03/2020

OVERCOMiNG THE CHALLENGES OF TRADITIONAL ENGINEERING

The biggest challenge in traditional engineering is the number of possible solutions to a problem. Combined with the almost unlimited freedom of shapes and structures possible in industrial 3D printing, engineers and designers face a formidable task.

Traditionally we split work into many small parts that are treated separately. But this stands in the way of coming up with a solution that is globally optimized. Most of today‘s objects are an assembly of subcomponents, which are often individually over-engineered for the task at hand.

With Additive Manufacturing, industrial 3D printing, we are starting with a clean slate. We can build functionally integrated objects using AI software components instead of assembling physical disjointed parts.

10/03/2020

HOW TO BUILD A ROCKET ENGINE THROUGH A.I.

From our work with space companies, we understand the complexity of creating rocket combustion chambers with conformal cooling. We engaged the Hyperganic Lab team to create a rocket engine demonstrator, using an entirely algorithmic approach. We decided to give the algorithms just one geometric starting point, a spline curve that describes the inside of the combustion chamber, stored in an Excel spreadsheet. There were no CAD files, no existing models, just numbers, plus the algorithms that interpret the data to generate the functional parts of the engine.

With this minimal starting point, our A.I. generated the geometry.

We used Hyperganic‘s capability to precisely control the process parameters for every point in space to modify the structure of the metal itself. The inside of the chamber is printed very densely, using high laser power, whereas the outside becomes almost porous to keep the weight down.

09/03/2020

A PARADIGM SHIFT THROUGH A.I.-DRIVEN DESIGN

Industrial 3D printing and A.I.-based design are promising to shift the freedom of engineering in a dramatic way. In this new paradigm, designers have unprecedented freedom. Engineers can work with complex and intricate shapes and even use digital materials to change physical properties selectively. Since every printed object is unique, products can be customized for each individual person.

In this case study, created by the Hyperganic Lab in Munich, the team worked with partners to implement the entire automated workflow from a 3D head scan to a finished bicycle helmet.

The Hyperganic workflow results in a 3D printed bike helmet that fits the rider perfectly, generated for individual comfort, style and safety.

The study clearly demonstrates the potential for fully automated individualization workflows. Creative What-If scenarios can quickly be tested. Data from many sources, can automatically be taken into account and used in the generation of each subsequent object.

By using the Hyperganic platform to encapsulate time-consuming engineering tasks in AI-components, designers are empowered to build objects of unprecedented intricacy and functionality.

06/03/2020

A.I. WORKFLOW DISRUPTS CONVENTIONAL DESIGN PROCESSES

The Hyperganic platform enables a completely automated workflow and manufacturing process through A.I.-driven design. For this case study, the Hyperganic Lab team built an automated workflow from individual 3D head scan to final 3D-printed end product.

Using Hyperganic Studio, the team created a process that takes information of the individual 3D cyclist’s head scan, historical data of crash impact statistics and a previously defined shell shape to automatically design an individualized helmet. The output is ready to print.

The central part is filled with algorithmic patterns with specific properties. They provide protection and support exactly where individually needed and optimize the airflow for optimum aerodynamics. For additional shock absorption and comfort, specially designed 3D printed silicon inlays where added to the inside of the shell.