Las Vegas is a fitting place to present visions of the future. The whole city has an air of the unlikely, spotted as it is with oases of luxury and randomness plonked in the middle of the arid Nevada desert. When you have seen a rollercoaster teetering precariously on the edge of a skyscraper roof, or a facsimile of St Mark’s Square in Venice that appears so close to the original until you look closer and realise that the Basilica is missing, the Doge’s Palace is the wrong shape and the clouds in the sky never move, you may be more likely to believe anything you see on the exhibition floor.
It is, therefore, a favourite location for technology exhibitions and conferences and in November last year, it hosted the annual Autodesk University event, showcasing the latest innovations from the manufacturing technology and software company. In such an environment, the natural response to what appears to be a giant silver spider squatting on an exhibition stand is not “I must be seeing things” but “I wonder how that interesting thing got there”.
Most engineers are now familiar with the characteristic look of objects produced using additive manufacturing (AM) or 3D printing. They tend to look organic and skeletal, with the rectilinear shafts and angles of conventional machined items replaced by sweeping curves, tapering columns and wasp-waisted members, thanks to geometry optimisation design programmes that analyse the patterns of mechanical stress through a component and ensure that material is built up only where it needs to withstand the forces that will be placed on them.
Although the cost of AM is falling fast it is still beyond the reach of many, if not most, companies in the manufacturing sector. Others are unwilling to completely redesign their processes to accommodate the new technology while, for some –notably aerospace –the certification of material properties remains an issue. However, as manufacturing technology and software specialist Autodesk revealed in Las Vegas, conventional manufacturing and machining can still deliver some of the advantages associated with the newer technique.
The key to this, the company presented, is a process it calls generative design. It is powered by a basic –almost fundamental –property of computerised design: the ability to iterate, taking a design which is approximately close to what might be needed to fulfil a function and repeating the calculations that produced it over and over again to refine that design, bringing it closer to an “ideal” form with each iteration. In this way, explained chief executive Andrew Anagnost, it is analogous to the process of evolution as explained by the theory of natural selection, where each subsequent generation makes the species more advantageously adapted to their environmental niches.
“We believe that generative design will become an increasingly important part of engineers’ toolbox,” Anagnost told journalists. “It fits in ideally with the digital workflow, from design through to manufacture, that we are seeing take hold across automotive, aerospace, construction and many of the other industries in which we are involved.”
The basic algorithms driving this kind of design are the same as those used in geometry optimisation for AM, placing material at the points in a structure where they need to withstand the greatest forces. However, generative design works by regarding this as merely a constraint on the form of the final component.
The capabilities of the machine that is to make an item are regarded as additional constraints. The design system takes into account where tools such as grinding heads will not reach. The software then iterates through its constraints, both those of stress distribution and of machining capability, refining the design with each set of calculations and eventually arriving at an optimised shape. Although this form may be made by five-axis machining, casting, CNC bending or whichever forming and shaping method the manufacturer chooses, the items tend to resemble the bird-bone-like forms of AM components.
Which brings us back to that silver spider. Its four legs are composed of curvaceous ladder-like sections, hinged at the ‘knee’ and ‘ankle’ and terminating in organic-looking pads. Where the thorax of the spider should be, a boxy construction with walls resembling sections of skull sits suspended. This is a conceptual lander for missions to explore the rocky and icy moons of the solar system’s gas giant planets, manufactured by NASA’s Jet Propulsion Laboratory (JPL) in Pasadena in partnership with Autodesk using generative design principles as part of a digital workflow to power conventional metal shaping equipment.
JPL’s first foray into generative design, the lander was a third lighter than conventionally-formed landers without sacrificing any performance in mechanical terms and would not require any compromise in the functionality of its payload. Payload mass is always a vital consideration in space exploration missions; every extra gram makes it more difficult to launch a payload out of Earth’s gravity and to catapult it beyond the inner planets of the solar system.
Every gram saved on lander structural elements can be used for sensors and other scientific instruments. With their complex atmospheres rich in organic chemicals, and surfaces covered with water oceans, the moons of the solar system’s gas giants Jupiter and Saturn are fascinating environments believed to be similar to those of early Earth. Planetary scientists are very keen to explore them for signs of the precursors of life. But getting there will require significant advances in design of landers, so JPL teamed up with Autodesk to investigate whether its technology could be of help.
Unfortunately, since the beginning of the joint project, budgetary constraints and changing priorities have led to the shelving of the missions to land on these moons but it remains a future goal for NASA. The demands of such a mission are extreme: Jupiter is 385 million miles away from Earth and Saturn 381 million miles beyond that. The temperature on the surface of their moons is typically hundreds of degrees below zero and radiation levels are thousands of times greater than those on Earth.
Made using a combination of CNC machining, AM and casting (used for the central body section, the only sign of which is its matt-finished surface compared with the highly-polished machined leg elements), the concept lander is believed to be the most complex item ever made using generative design. At 2.5 metres across and a metre tall, it’s certainly one of the biggest. Autodesk approached JPL to pitch the project, and found it to be a demanding potential partner.
“They were clear that they weren’t interested in incremental gains: if they were only able to improve performance by 10 per cent, they basically weren’t interested,” said Mark Davies, senior director of industry research and one of the team which first approached JPL. “If we could deliver software tools to help them achieve a performance improvement of 30 per cent or more, then we had their attention. This project demonstrates that Autodesk technologies may deliver mass savings at this level.”
Exploring new technologies is second nature for JPL.
“What they do is carefully infuse new technology into their processes,” said Karl Willis, Autodesk’s technology lead on the project. “They know they have to explore new ways to do things while keeping risk at a minimum.”
In the Lander project, JPL took advantage of previous Autodesk’s experience with other sectors that demand high performance. “We had developed a custom version of our software for high performance motorsports that enabled us to help our customers solve for multiple constraints at once. We then applied it to the problems JPL needed to consider,” Davis said.
“We took a system developed to help our customer solve system level suspension problems on a Formula 1 race car and applied new requirements for structural constraints critical to space exploration. This gave us a chance to push the capabilities of the software even further and help our customers solve larger and more sophisticated problems.”
Closer to earth, generative design has also been used in the automotive sector, allied to some of the techniques which come under the Internet of things (IoT)/industry 4.0 banner. Custom car builder Hack Rod –founded by Felix Holst, former creative vice president for a toy manufacturer, and Mike “Mouse” McCoy, a film director and former motorbike racer, is no stranger to using advanced technologies and new ideas in projects.
Holst and McCoy decided to work with Autodesk to see whether its design techniques could be used to create visually striking new cars with high-performance properties. The first stage was to optimise one of its existing designs. The Hack Rod team, working with Autodesk research fellow Mickey McManus, made a 3D scan of an existing chassis with a proven design and uploaded it to the cloud.
They then equipped the chassis with dozens of wireless sensors and gave it to a stunt driver to take it on a joyride around the Mojave Desert, observed by a drone which captured a 3D model of the driving landscape. This resulted in an enormous dataset on the car’s structure and all the forces acting upon it. This information was then sent to Autodesk’s cloud-based CAD system. Known as Project Dreamcatcher, the system incorporates the user’s design objectives, the project’s material types and available manufacturing methods, and the required performance criteria and cost restrictions. Dreamcatcher is a generative design system that iterates around the defined constraints and presents the user with a series of design alternatives.
“The power of generative design running together with cloud processing outstrips anything a team of human minds can come up with,” said Holst.
As with many generative design projects, the resulting structure looks skeletal; but not like any skeleton evolved on Earth. The team put together the chassis from chromium-molybdenum steel using conventional welding techniques and the resulting structure measures 3.6m x 2.1m x 1.2m and weighs 136kg. The skin that surrounds the chassis was also designed digitally. The full results from the project, however, are not yet available.
McManus, McCoy and Holst continue to refine their design through additional runs in the Mojave, generating more data for Dreamcatcher to refine the car. Despite the ever-evolving nature of this project, the team believe it could form the basis of a new philosophy for vehicle manufacturing, using the IoT capabilities of networked sensors with cloud-based solutions to refine designs and eventually drive manufacturing.
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