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Beyond additive manufacturing–generative design shapes for milling too

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Generative designs don’t have to be 3D printed. Other manufacturing methods enter the fray.

by Jean Thilmany, Senior Editor

There are those that say generative design ensures the best product design possible. Engineers enter the specifications a product needs to meet, and the tool responds by creating a number of potential designs that fit the bill. It even recommends potential materials to be used.

Now, the resulting designs can be manufactured in a number of ways.

Increasingly, CAD software makers, such as Autodesk, are building manufacturing preferences into their topology optimization and generative design tools, meaning generative design can take into account a particular manufacturing method. The engineer enters the manufacturing method as one of the design constraints. The resulting generatively created designs depict products that can be made according to that method and that meet other desired specifications, says Kim Losey, Autodesk’s head of marketing for Fusion 360.

Two years ago, Autodesk released generative design to subscribers of its Fusion 360 Ultimate product development software. Autodesk moved to marry generative design with manufacturing methods when it announced late last year that PowerMill, PowerShape, and PowerInspect would become part of the company’s Fusion 360 solution.

Now, Autodesk says, CAD and CAM reside on the same Fusion 360 platform.

The inclusion of CAM brings manufacturing considerations to the front of the generative engineering process, saving engineers and manufacturers time and money.

The generative technique is a completely different approach to design. The design concept allows engineers to define design parameters: such as material, size, weight, strength, and cost constraints–before they begin to design. Then, using artificial-intelligence-based algorithms, the software presents an array of design options that meet the predetermined criteria, Losey says.

MJK recently turned to generative because weight, strength, and style were all necessary considerations for the triple clamps it makes for motorcycles. On motorcycles, stanchions from the telescopic fork are attached to the triple clamp, and sliders at the other end are attached to the front-wheel spindle. The clamps are part of the fork that connects the motorcycle’s handlebars, steering stem, and shock absorbers.

By calling upon advanced software and computing power the generative system runs through many possibilities, each meeting the engineers’ design specifications. It presents the best designs to engineers, allowing them to pick the optimal design. Engineers are involved at the beginning and at the end of the design process. If they don’t feel any of the returned designs meet their standards, they can tinker with inputs and cue the generative-design system to start again.

The computer-generated (“generative”) designs might be unorthodox, new, and unexpected, with geometries that wouldn’t naturally occur to the designer. No matter how different, if the design is shown to work, it can be created by additive manufacturing, also called 3D printing, Losey says.

In the past, the design software often created shapes that could be produced only by 3D printing because the resulting organic, nature-like forms that were commonly created did not lend themselves well to processes such as machining, casting or fabrication, she adds.

But that led many people to assume the designs could be produced only through additive-manufacturing techniques.

Now, the scope of generative-design automation is expanding to include traditional manufacturing processes, such as milling, die casting, and even water milling.

Today, you can input traditional manufacturing constraints into Autodesk Fusion 360 and use its generative-design functionality to produce optimal design solutions that can be manufactured according to one of several predetermined methods, she adds.

Autodesk’s generative design software, part of its Fusion 360 platform, includes capabilities to sort through the design possibilities reflected by particular manufacturability considerations. This enables engineers to compare how easily, quickly and cost-effectively components can be produced via different manufacturing methods, Losey says.

By applying constraints that sort design possibilities according to selected processes, design options can be evaluated in a new light. Both engineers and manufacturers are often surprised at the results, she says. Multi-axis machining might be the best choice, as it turns out, even for a very elaborate part, when certain constraints are in place.

And bringing manufacturing to the front of the decision-making process underscores the role generative design has to play in the choice of product, Losey adds.

Estimating manufacturing costs
PowerMill 5-axis CAM software provides expert CNC programming strategies for complex 3- and 5-axis subtractive, high-rate additive, and hybrid manufacturing. Meanwhile, PowerShape is CAD software that creates complex 3D geometry to better control CAM software such as PowerMill. It works with any combination of surface, solid, or mesh data and quickly creates damage and collision-free toolpaths for large, complex parts, Losey says.

A recent video from Autodesk, in reference to questions to keep in mind while populating a prospective generative design, asks: “Will you deviate from the traditional design scope to include manufacturing constraints? Will you use 5-axis, 3-axis or even 2.5-axis milling? What about die casting? Can your design be water milled? Or does additive manufacturing provide the best value and performance?”

Clearly, the manufacturing process is a big influence on the type of geometry produced, Losey says.

While generative design can provide results optimized for your manufacturing method of choice, how do you evaluate the tradeoffs between performance and the cost to make your part?

Autodesk includes software—the aPriori Cost Insight Engine—as part of its generative design package. It generates a manufacturing cost estimate for each design alternative created.

“It interrogates a model for features or tolerances that would be costly based on certain manufacturing methods,” she says. “It allows engineers to fully explore costs and to strike balance between performance and cost.”

Another way generative design reduces manufacturing costs: the generative process can result in a single, solid-mesh body that can replace multibody components, such as a welded assembly. This reduces a manufacturer’s need to spend money on jigs, fixtures, welders, and welding material. And single-body parts can be made via additive manufacturing, which also reduces the need to design and manufacture tooling.

Also, generative design allows engineers to replace small assemblies with a single component to reduce manufacturing costs and bill-of-materials complexity.

Milled motorcycle parts
MJK Performance had shied away from the generative design method because Phil Butterworth, MJK designer and co-owner, felt the visual style evoked through generative design wouldn’t fit his company’s style. The company, of Calgary, Canada, produces aftermarket parts for Harley Davidson motorcycles.

“It always made me think of those spiderlike, organic, alien models,” he says. “I just thought it’d give us the same style only blockier, covered in intricate little pieces and looking silly.”

Autodesk’s generative design technology developed parts for conventional 2.5- and 3-axis milling and set Fusion 360 to design parts that could be made exclusively through those methods. Using that input, the CAD and CAM product quickly returned a range of designs that are lightweight and fully machinable.

But MJK recently turned to generative because weight, strength, and style were all necessary considerations for the triple clamps it makes for motorcycles and Butterworth knew the method could help with weight reduction.

On motorcycles, stanchions from the telescopic fork are attached to the triple clamp, and sliders at the other end are attached to the front-wheel spindle. The clamps are part of the fork that connects the motorcycle’s handlebars, steering stem, and shock absorbers.

“Our clients want the look of a 200-pound race bike for their 1,000-pound Harley,” Butterworth says. “As a result, we need to make our parts as light and strong as possible but also stylish. Every part has to look like it belongs on a hundred-thousand-dollar bike.”

But the triple clamps are large and bulky, leading Butterworth and his fellow designers to attempt to reduce their weight. With an additional factor: The clamps had to be fully machinable on a 2.5-axis mill because the company makes all its parts at its small, four-machine shop.

Butterworth says he was surprised to learn that generative design might be the answer to his needs. He’d assumed generative design was mostly limited to additive manufacturing.
He soon discovered that Autodesk’s generative design technology could develop parts for conventional 2.5- and 3-axis milling and set Fusion 360 to design parts that could be made exclusively through those methods. Using that input, the CAD and CAM product quickly returned a range of designs that are lightweight and fully machinable, Butterworth says.

Not only that, “when the model came back, it looked like something I would buy immediately. I was blown away. It looks racy; it’s got all the cool geometry. It has all the cool stuff generative does but in a style people understand and recognize,” he says.
After studying the potential designs, Butterworth selected one and then spent approximately 20 minutes editing it to suit the characteristic MJK Parts style.

Through use of generative design, engineers went from computer model to a prototype within a few hours. And the weight of the triple clamp was reduced by 23% compared to a similar triple clamp designed by an engineer rather than the generative program. Nor did the generative design sacrifice safety, Butterworth says.

Normally, this process would take one or two days to complete. But with generative design MJK was able to accelerate this process. They went from a computer model to a prototype in a few hours. Fusion 360 can easily be set to produce designs for 2.5-axis milling, he says.

Within JPL, its Atelier division is the team charged with trying new approaches and processes, and its recommendations are passed on to teams working on specific missions. This division is collaborating with Autodesk to evaluate generative design for the proposed lander.

Topology optimization joins in
Capabilities are also changing fast in topology optimization, which differs from generative design. When using topological optimization, an engineer defines loads within a 3-D space and the program removes material to attain a shape that uses the least amount of material while still retaining required stiffness and density. The method also creates parts with odd shapes, though it typically gives fewer results than does generative design.

Additive manufacturing, with its capability to create never-before-seen shapes, seemed a natural for both.

But, to give you an example of the move to find methods beyond additive has quickened, take the example of the following two engineering journal submissions.

An October 2016 paper in the journal “Advances of Engineering Software” stated that: “Despite being an effective and a general method to obtain optimal solutions, topology optimization generates solutions with complex geometries, which are neither cost-effective nor practical from a manufacturing perspective.” That paper was written by Sandro Vatanabe and his coauthors.

In it, Vatanabe, now an engineering professor at the FEI University Center in São Paulo, Brazil, and his colleagues proposed techniques to restrict the range of solutions for the optimization problem. The paper was entitled Topology optimization with manufacturing constraints: A unified projection-based approach.

Three years later, a paper entitled “Topology optimization for multi-axis machining” presented a topology-optimization approach that incorporates restrictions of multi-axis machining processes. In it, author Matthijs Langelaar posits that particular cutting tool shapes and maximum insertion lengths can be included in topology optimization without much additional computational effort. He then shows examples of how to generate optimized, machinable, three-dimensional parts. Langelaar is an associate professor of structural optimization and mechanics at Delft University of Technology in the Netherlands.

Langelaar set out a formulation developed for 5-axis processes, though the technique also covers other multi-axis milling configurations, 2.5-axis milling and 4-axis machining by including the appropriate machining directions. In addition to various tool orientations, user-specified tool length and tool shape constraints can also be incorporated in the filter.

So, while a generative design or topology optimization study can result in interesting new designs, perhaps previously unfathomable designs, engineers needn’t limit themselves to 3-D printing to manufacturing the design of their choosing.

Butterworth says generative design has opened up countless new avenues at his company.

“Before I even start programming a mill, I know my part is going to pass any performance test,” he says. “Whatever the weight optimization in the simulation does, the 2.5-axis generative design just gave us a solid model right away.”

Autodesk
www.autodesk.com

Immersive reality headset makes remote collaboration easy

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KIA Motors has always been an industry leader when it comes to implementing new and innovative tech in their design process. Now, with Varjo XR-1 supported by Autodesk VRED, the designers are moving into an immersive photorealistic environment. The benefit is that global design reviews can go from days to an hour.

Photorealistic, real-scale and hands-on – seeing is believing
Thomas Unterluggauer is the the Europe Design Center of KIA Motors Creative Manager CGI. He’s wearing the Varjo XR-1 headset as he works on a KIA model in the studio; moving seamlessly between the real and virtual car in front of him, and making changes on the fly. What he’s seeing and doing in the KIA studio hasn’t been possible until now.

When KIA’s European team tried out Varjo’s VR headset for the first time, they were impressed by the clarity and the resolution of the headsets.

“For the first time, we could literally see the metallic flakes in the paint and perceive the depth and quality of the material shaders. We could see the beauty of the details more than ever before in the virtual world. Varjo is the only device capable of this level of clarity and sharpness,” Unterluggauer says.

Seeing more details in the car exterior was a breakthrough. But when Unterluggauer and the team got to explore the Varjo XR-1 mixed reality device, they realized they could also use it to take their design work to new heights.

With Varjo XR-1, designers can work with their colleagues in the physical design space they’re used to and collaborate on photorealistic, real-scale virtual car models while seeing their hands and bodies. In an immersive mixed reality experience like this, they’re able to talk as they go, give immediate feedback, and run more engaging reviews.

KIA’s European design studio, led by Gregory Guillaume, is a pioneer in integrating new technologies into their design workflow. With a digital 3D department, design teams and visualization experts, its goal is to always exceed expectations – both for KIA customers and the company’s leadership in South Korea.

“Immersive collaboration works more naturally than we expected. This is something I’ve always wished for,” adds Gregory Guillaume, Vice President of Design at KIA Motors Europe.

At the end of a mixed reality session, Unterluggauer takes off the Varjo XR-1 headset and looks back into the room. “It’s fascinating how quickly you adapt to the mixed reality.

You’re tricked into thinking for a moment that reality is wrong, that there is something missing. It’s completely different to any other experience I’ve ever had in VR,” he says.

KIA’s workflow changes up a gear with VR/XR
Located in Frankfurt, Germany, Kia’s Europe Design Center is helping to change perceptions of the Kia brand across the continent as well as worldwide. Its dedicated team of designers create concept cars of the future as well as production models for both Europe and the global market.

The ability to design and collaborate with Varjo’s photorealistic VR/XR and Autodesk VRED is a game-changer for KIA’s designers.

Until recently, the automotive design process relied on 2D reviews on screens and powerwalls, followed by physical clay models and prototypes to further refine and develop the surfaces.

As manager of the studio’s digital department, Frank Hübbe knows that a 2D model is always a projection that lacks volume. “Although you can use keyboard, mouse, and screen to work efficiently in 2D, you’ll never get a fully realistic impression of the car,” he says. Today, KIA Europe’s designers are complementing their entire workflow with virtual and mixed reality. The teams are using VR/XR technologies to make their visualization work more effective and showcase projects in new ways.

With Varjo XR-1, KIA designers can review new virtual car models next to physical ones; or take a physical clay model and overlay parts of it with virtual data. For instance, in interior design, it allows them to overlay digital content onto a physical seating buck.

For example, designers can review a virtual model directly against a physical model in the same room, or even augment an existing clay model with virtual details.

“With VRED and the Varjo XR-1, you have the context of the real world and the flexibility of the virtual world,” Hübbe says.

Remote collaboration when the world needs it most

In the midst of a global pandemic, the ability to collaborate remotely and reliably with teams across the globe has never been more crucial.

With COVID-19 currently preventing most business travel, KIA Europe has turned to Varjo’s VR/XR and Autodesk VRED’s virtual collaboration feature to continue working with the other global studios. Designers can collaborate on the same photorealistic models from wherever they’re based around the world, trusting that everything from the smallest details to the full-scale appearance of the car looks correct.

As Gregory Guillaume says, until now, if he wanted to discuss a model with the design management at KIA’s global headquarters; he’d have to fly to Korea to do it. Reviewing a digital model with design management always took a minimum of four days. “Now, I can do it in one hour,” he says. The ability to carry out design reviews virtually presents KIA with the opportunity to save time, work and money.

And while professionals worldwide are currently struggling with often unreliable phone and video conferencing technology, Guillaume has had promising experiences with this new collaboration technology. Despite the complexity of the VR/XR hardware and visual rendering software, his team hasn’t had any reliability issues with the Varjo XR-1 and Autodesk VRED at all.

“You’d think this is so much more complicated than a video call. But collaboration has been very reliable,” he says. Guillaume and his team can be in the same virtual room with the design management team and look at and discuss the same car model in perfect detail. “That’s only possible if we trust what we’re seeing and the tools we’re using. It amazes me that something so complicated is working so naturally and easily.”

Despite all the restrictions and uncertainties that come with the global pandemic, using Varjo and Autodesk VRED is enabling KIA to continue their design collaboration with studios across the globe. “This technology is bringing us together at a time when we can’t be present in the same physical place,” Guillaume says.

Autodesk
www.autodesk.com

Autodesk makes Generative Design in Autodesk Fusion 360 more available to users

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Autodesk is making it easier for customers to take advantage of the features and functions of generative design with the Fusion 360 Generative Design Extension subscription offering. The company is offering unlimited access to the generative design functions as a separate subscription, at either $1,000 monthly or $8,000 annually.

Wheels for a Briggs supercar developed with Generative Design software. Image courtesy of Briggs Automotive Company

The introductory pricing is for a limited time. Through July 17, annual subscriptions to Fusion 360 and the Generative Design Extension are available for 50% off the regular price.

MJK Performance used generative design technology to create a set of lighter and stronger triple clamps for a drag bike.

For those who prefer to pay as they go, access to the generative design extension will continue to be available using Autodesk Cloud Credits.

Autodesk
www.autodesk.com

Updates in CAD focus on better simulation

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While the latest upgrades to major CAD systems don’t make major changes to the way those programs operate, they do include significant updates. Here’s a look at some of the biggest enhancements and key features of these programs.

Jean Thilmany, Senior Editor

CAD packages continue to see regular updates, whether a major release, or the minor updates that happen throughout the year. Some updates include major enhancements or new features, as is the case with NX, which now includes machine learning and artificial intelligence features. The company will quit bringing out yearly NX updates, as the software is now offered on continuous release.

Other popular programs like Creo, Solid Edge, SolidWorks, and Autodesk Fusion 360 have seen changes as well. More than one company has changed the way in which they name the new versions of their software and several boast new or enhanced simulation capabilities.

Here’s a look at the most recent updates.

NX from Siemens PLM

In February, Siemens announced an update to its NX CAD software, which now includes machine learning and artificial intelligence features that, by following users’ patterns over time, come to automatically predict their next steps and anticipate their needs.

The programs do this by monitoring the actions of the user and following their success and failures. In that way, the features determine how to serve up the right NX commands and also modify the user interface accordingly, says Bob Haubrock, senior vice President, product engineering software at Siemens PLM Software.

Machine learning is increasingly used in the product design process because it has the power to process, analyze, and learn from large volumes of data, he adds. In this way, designers can more efficiently use software to increase productivity. The ability to automatically adapt the user interface to meet the needs of different types of users in various departments can increase CAD adoption rates at a company, continues Haubrock.

In another recent change, Siemens PLM Software began delivering NX using a continuous release model. This means the software updates are produced in short cycles and are released when needed, at any time.

The model gives NX users faster access to new enhancements and quality improvements, while reducing the efforts needed to effectively deploy NX, Haubrock says. “With automatic updates, customers do not have to search for updates online and will not miss critical fixes. The NX Update mechanism will automatically notify and install important updates as they become available.”

With continuous release, users can turn on “automatic updates” within their system to ensure they always receive the updates. The approach helps reduce the cost, time, and risk of delivering changes by allowing for more incremental updates to applications.

Thus, NX will no longer be identified by a release number and will only be referred to as NX. In other words, there will be no NX13.

The CADmaker says it’s the first major CAD, CAM, and analysis vendor to deliver its products in this way.
The company says the new approach will enable Siemens’ NX users to:
–Receive enhancements faster to help boost productivity
–Have a consistent schedule for updates
–Better plan for the adoption of new technologies
–Reduce deployment costs

Creo from PTC

In February PTC released Creo Simulation Live, which allows engineers to perform simulation in real time on their parametric models because ANSYS simulation capabilities have been integrated with the Creo CAD tool.

Creo Simulation Live, from PTC, lets engineers perform simulation in real time on their parametric models because ANSYS simulation capabilities have been integrated with the Creo CAD tool.

“Every time you make a change in your model, you’ll see the consequences instantaneously in the modeling environment,” says Brian Thompson, PTC senior vice president, CAD segment.

“The goal is to remove the barrier between the CAD and CAE world,” says Andrew Leedy, a PTC applications engineer. “This is targeted toward the engineer or designer rather than the analyst.”

The simulation software runs linear, structural, thermal, and modal analyses. The solver uses GPU rather than CPU for instantaneous analysis, Leedy adds. “So as soon as you make changes to the model it updates the graphics that drive the simulation.

The capability to simulate and design simultaneously helps engineers understand the implications of what they’re making, he adds.

The integrated tool also eliminates the need for the engineer to mesh the model before running a simulation and does away with the post-processing step.

The integrated simulation software from ANSYS is called Discovery Live.

“Engineers can ask ‘What if I add this hole, what will it do to the model?’” he said. “This works on top of the model, it works directly within the environment an engineer is used to.”

The CAD software does require a graphics card that supports the ANSYS tool.

Solid Edge from Siemens PLM

Solid Edge 2019 brings a new naming convention to the tool, which will now be referred to by the year in which it is released. This makes it easier for engineers to identify the release they’re using as well and to identify the products within the Solid Edge portfolio, says Ben Weisenberg, applications engineer at product lifecycle management company Prolim. Weisenberg frequently details Solid Edge updates to the CADmaker’s user community.

Solid Edge 2019, from Siemens PLM, makes it easier for engineers to identify the products within the Solid Edge portfolio. The most significant updates for mechanical designers are tools that allow engineers to model and simulate the entire production process along with the final product.

The most significant updates for mechanical designers are tools that allow engineers to model and simulate the entire production process along with the final product, Weisenberg says.

These include the convergent modeling tools that designers can use to integrate mesh models directly into their workflows. They can use these tools for the milling, casting, and molding of generative designs and 3D printed designs.

Manufacturing constraints allow engineers to optimize the weight and strength requirements of their model. A new design-for-cost feature shows the anticipated cost of the part, to help keep product development on track and within budget.

Updated simulation capabilities include:
–Enhanced structural and thermal simulation, including transient heat transfer.
–Time-based history analysis enables simulation of thermal and cooling performance.
–Free surface flow simulation, lighting and radiation capabilities allow digital “what if” analysis.
–The ability to display simulation results on geometry faces to help engineers make more informed judgments about the model.

SolidWorks from Dassault Systèmes

New features to the program, released in September 2018, let product development teams better manage large amounts of data and capture a more complete digital representation of a design. The program also offers new technologies and workflows that improve collaboration and enable immersive, interactive experiences during design and engineering.

SolidWorks 2019, from Dassault Systèmes, is powered by the company’s 3DExperience platform, which runs the CAD, simulation, and other tools on which designers and engineers rely. Those applications on the 3DExperience platform are tailored to SolidWorks users and mid-market companies.

Other new features include the capability for engineers to interrogate or rapidly make changes to a model through an enhanced large design review capability. Another upgrade gives teams a way to communicate with others not involved in design. With this feature, viewers of the CAD design can add markups to parts and assemblies and then export the marked-up designs as a PDF.

The most recent update from Dassault Systèmes involves the Works portfolio, which will bring applications like SolidWorks together with business solutions like a company’s enterprise resource planning (ERP) system. Typically, ERP systems track all pertinent companywide business processes, including accounting, supply chain, and human resources.

When parent company Dassault Systèmes launched SolidWorks 2019, executives stated that the CAD tool was “powered” by the company’s 3DExperience platform, which runs the CAD, simulation, and other tools on which designers and engineers rely.

Those applications continue to run on the company’s 3DExperience platform and are tailored to SolidWorks users and mid-market companies. They have been folded in the 3DExperienceWorks portfolio.

SolidWorks executives term the new portfolio a “business experience platform.” It provides software solutions for every organization within a company—from design to enterprise resource management, says Bernard Charlès, vice chairman and chief executive officer for Dassault Systèmes. “It’s a way for mid-market companies to tie all processes together, from design to manufacturing.”

Use of the applications across the platform should improve collaboration, manufacturing efficiency, and business agility, he added. Companies can accomplish their work using one cohesive digital innovation environment instead of using a complex series of point solutions that requires jumping between applications and interfaces, Charlès, says.

The software on the platform includes SolidWorks, analysis, simulation, manufacturing, and ERP applications. It is available on-premise and in the public or private cloud. The platform connects data and streamlines business and design processes by providing dashboard templates, managed services, access to industry-focused communities and user groups, and applications specific to a variety of job roles, Charlès says.

Autodesk

Like other CADmakers Autodesk has consolidated its design, simulation, and other computer-aided engineering capabilities in one product, Fusion 360, which is available as a cloud-based product. The product unifies design, engineering, and manufacturing into a single platform, according to Autodesk.

Fusion is a 3D modeling took that includes simulation, visualization, rendering, CAM, and other functions within a single interface. It also includes a 3D animation tool and 2D drawing tools. The product runs on both Windows and Macintosh systems.

In March, updates to that product included the capability to know when a teammate is working on your design at the same time to avoid doing work that will be over-ridden by another designer. When someone is working on the same design, an icon is displayed in the toolbar. By using a mouse to hover over the icon, a designer can see who is working on the same design. If one person makes a change to the design and saves it, the icon in the toolbar will change, letting the designer know that the design now has a newer version.

The toolbar has been updated to include quick access tools and documents tabs that line up with one another for more space on the design desktop.

Also new is a hole-tap tool called taper tapped, which allows designers to choose among a variety of thread types.

Autodesk also maintains its AutoCAD and Inventor CAD tools with no plans to immediately discontinue those products. Those two CAD systems usually see a new release in March of each year; though as of press time Autodesk hasn’t announced 2020 versions of AutoCAD or Inventor.

At Autodesk University in November 2018, Greg Fallon, vice president of business strategy at Autodesk, did announce updates to a collection of tools that work inside Inventor as well as a suite of specialized toolsets now available with AutoCAD.

Two years previously at Autodesk University 2016, company officials said they expect to maintain Inventor for another five to ten years and plan to continue updating it and enhancing functions. The Inventor emphasis will continue to be on industrial machinery design, officials said at that time.

While Inventor may be phased out in favor of Fusion 360, this has not been explicitly stated by Autodesk executives.

As ever, there are too many CAD packages to include in a single roundup. Other applications include IronCAD, TurboCAD, OnShape, Catia, and KeyCreator. All these will include new and updated features in future updates.

As designers and engineers know, when it comes to CAD software, the key phrase is, constant evolution.

Ansys
www.ansys.com

Autodesk
www.autodesk.com

Dassault Systèmes
www.3ds.com

PTC
www.ptc.com

Siemens PLM
www.plm.automation.siemens.com

International TechneGroup announces GoToINVENTOR for Autodesk customers

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International TechneGroup Incorporated (ITI) introduces GoToINVENTOR software. GoToINVENTOR offers feature-based translation that enables the transfer of complete design intelligence from major CAD systems to INVENTOR with up to 100% automation and enhanced efficiency.

GoToINVENTOR is based on ITI’s Proficiency software technology. By providing functional models that retain the original product knowledge in INVENTOR, GoToINVENTOR maximizes CAD data re-use and offers a reliable basis for further product design and development. Users can convert geometry, features, history, sketch relations, manufacturing information, metadata and assembly information from CATIA V5, NX, Creo/Wildfire, Solid Edge and SOLIDWORKS seamlessly to INVENTOR. GoToINVENTOR can also convert associative drawings along with the linked 3D models in one automated procedure.

International TechneGroup Inc.
www.iti-global.com/gotoinventor

Utilities for Autodesk software

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IMAGINiT Technologies’ customers who subscribe to Autodesk software have complimentary access to several new IMAGINiT Utilities for Autodesk Revit, Autodesk AutoCAD Civil 3D and Autodesk Vault Client. With more than 40 individual IMAGINiT utilities now available, building information modeling (BIM) coordinators and computer aided design (CAD) managers can increase team efficiencies and reduce human error by automating redundancies.

“IMAGINiT utilities extend the power of your Autodesk software, and each year, our development team releases new utilities to ensure customers spend their time focused on the design process instead of manual tasks,” says Bill Zavadil, senior vice president of professional services, IMAGINiT Technologies. “Our utilities aim to automate those time consuming, manual tasks, thereby freeing up design teams so that they can accomplish more in less time.”

IMAGINiT Utilities for Autodesk Revit

Now with 27 tools that run directly inside Revit software, IMAGINiT Utilities for Revit include three new utilities.

New Utilities for Revit 2019 include:

Annotation Font Update scans the model for all font references and, through an easy-to-use wizard, allows users to update fonts throughout the entire model.

Family Placement looks at families that are in a folder structure and – with just a few clicks – allows users to load and place them so they are available in the current model. Running as a Palette inside Revit, it is available to users whenever needed.

Shared Parameter Check scans your model for the shared parameters that should be migrated to your centralized file or for inconsistent shared parameter identifiers and type/instance settings.

IMAGINiT Utilities for AutoCAD Civil 3D

With the addition of this latest tool, IMAGINiT Utilities for Civil 3D now includes a total of 10 tools designed to help BIM coordinators, infrastructure project managers and CAD champions to increase collaboration by leveraging new design workflows.

KML/KMZ Import brings geometry from Google Earth/Google Maps into the model allowing the creation of new workflows and collaboration with individuals who do not need access to Civil 3D. Individuals can mark out areas for development in Google Earth/Google Maps and engineers can import the KML file into Civil 3D to create a baseline for the design.

IMAGINiT Utilities for Autodesk Vault Client

IMAGINiT Utilities for Vault Client help CAD managers and non-CAD users better manage data workflows. New tools for 2019 are:

Create Local Folders allows users to generate folders in their Windows working folder hierarchy to match the Vault folders.

Visual Lifecycle Tab provides a visual description of the current file’s lifecycle definition, including its current state as well as the available transitions to other states.

Link Generator easily sends information to others by retrieving links to the Vault Thin Client for selected items or files.

Auto-Update Folder Properties to File offers a way to quickly synchronize properties applied at the folder level to corresponding properties at the file level.

IMAGINiT Utilities Availability

IMAGINiT Utilities for Revit, IMAGINiT Utilities for AutoCAD Civil 3D and IMAGINiT Utilities for Vault Client are available to customers maintaining their annual Autodesk subscription through IMAGINiT. These free software utilities can be accessed via IMAGINiT’s ProductivityNOW Portal. Those who are not already IMAGINiT customers may purchase these utilities directly from the IMAGINiT eStore.

IMAGINiT Technologies
www.imaginit.com

The perfect, unorthodox design

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What if you could create the perfect part unlike anything that exists today? New CAD tools combined with 3D printing can make that happen, makers say.

Jean Thilmany, Senior Editor

No matter what you call the design method, having the computer generate the designs from am engineer’s directions may just be the future. Unorthodox, 3D printed shapes can be found in aerospace now. Soon, such designs will be all around you.

3D printing methods are enabling the development of shapes unproducible by other manufacturing methods. Now, CAD developers are including design tools that take full advantage of the capabilities of 3D printing. These tools are often labeled generative design or topology optimization. They enable engineers to use design software in a new way to best fit design needs.

In April, Autodesk released generative design to subscribers of its Fusion 360 Ultimate product development software. The design concept allows engineers to define design parameters such as material, size, weight, strength, manufacturing methods, and cost constraints–before they begin to design. Then, using artificial-intelligence-based algorithms, the software presents an array of design options that meet the predetermined criteria, says Ravi Akella, director of product management at Autodesk.

“Our effort now is in helping people define the problem they’re trying to solve,” Akella says. “That’s a shift in focus in this industry and makes people have to change the way they have to work.

“The software asks the user preliminary questions. ‘What sorts of materials would you consider for your design? Where does it connect with other things as part of an assembly? What are the loads? What are the pieces of geometry?’” Akella says.

This Elbo chair was designed using Project Dreamcatcher, which was the name Autodesk used for its generative design tool before officially unveiling it this spring.

The software then presents designers and engineers with an array of design options that best meet their requirements. Designers choose the best option. Or, if none of the options meet their needs, they can begin the generative process again, this time offering slightly different inputs.

The computer-generated (“generative”) designs might be unorthodox, new, and unexpected, with geometries that wouldn’t naturally occur to the designer. Yet, no matter how different, if the design is shown to work, it can be created through additive manufacturing,” Akella says.

The method adds value to the present way designers use CAD software, he adds.

“None of these generative questions are asking ‘What is your solution and please start documenting it,” he says. “Without generative design, it’s like engineers were using a piece of paper to explain the problem to themselves. Our job is to get all of that into software.”

He compares generative design with the job of the wine merchant.

By using Autodesk’s generative design and additive manufacturing technologies, engineers at Stanley Black & Decker shaved more than three pounds off this crimping tool attachment, reducing the weight by more than 60%.

“Someone walks into a wine store and wants a Cabernet Sauvignon,” he says. “To get the best version you go in and say ‘It’s summer and this is what’s on my dinner menu’ and you’re trusting the sommelier to present you with a variety or vintage you’ve never heard of.

“Generative expands your solution options, which sometimes aren’t intuitive,” Akella adds. “Users look at their results and think ‘I never would have thought of it. I’m not sure it’s the right answer but I’m going to check it out further.”

By any other name?

Akella takes issue with what he calls “technologies that masquerade as generative design,” which, he says, include topology optimization, lattice optimization, or parametrics.

“Topology optimization assumes you have a solution you’ve thought of and are making a better version of that solution,” he says. “But generative design expects the user to define the problem they’re trying to solve. Then we use cloud computing and other technologies to present them with a set of solutions that solve their problem in a practical, manufacturable way.”

Generative design produces many valid designs instead of an optimized version of an already-modeled part.

“Optimization usually involves removing excess material without any notion of how something is made or used,” he says.

Generative design also takes manufacturability into account, which reduces an engineer’s need to redesign products after manufacturing weighs in, Akella says.

But developers and executives at other makers of CAD technology may take issue with that depiction of their topology optimization features, which can radically change designs and reduce weight and slash costs, they say.

SolidWorks introduced topology optimization capabilities into its recent release of SolidWorks 2018 Simulation Professional and Simulation Premium.

“We expect the computing platform to anticipate your design goals,” said Gian Paolo Bassi, chief executive officer at Dassault Systèmes SolidWorks, when he spoke at SolidWorks World 2018 in January.

“The era of design and validate is about to end. We are entering the era of optimize and manufacture,” Bassi said.

That means designers specify the aspects of the part they absolutely need, including loads, constraints, boundary conditions, and manufacturing methods. The CAD tool then supplies many versions of a near-optimized part, Bassi says.

Topology optimization can be an additive or subtractive algorithm, meaning it can create parts based on user inputs like loads and boundaries or it can subtract from an existing design by essentially chiseling away at the part, says Robbie Hoyler, a SolidWorks elite application engineer for TPM, an engineering services and design provider in Greenville, S.C.

SolidWorks uses the subtractive method. It creates a meshed part based user-defined loads, constraints and boundary conditions. The software cuts out elements that offer few structural or manufacturing benefits. This process is then repeated until the part meets all constraint requirements, Hoyler says.

The optimized CAD design shows engineers the areas of the part that need to stay and the areas where material can be removed, Hoyler says. He cited an example in which SolidWorks topology optimization reduced the weight of an existing part by 50% without removing areas designers had flagged as necessary.

The part can then be saved as a mesh body in the stereolithography (SL) format for 3D printing or can be retraced as a new SolidWorks part.

Another software package, Inspire, also features generative design and topology optimization tools. It allows users to save the enhanced design as a CAD model (skipping the retracing step). The software is from Altair channel partner solidThinking.

The Inspire’s generative feature is easy to learn and is ideal for small and medium-size businesses with little or no simulation experience, says James Dagg, Altair’s chief technology officer for user experience.

Solid Edge, from Siemens PLM Software, of Plano, Texas, also includes a generative design feature that brings topology optimization to the Solid Edge 3D product development toolkit, according to the company. With the feature, designers define a specific material, design space, permissible loads and constraints and a target weight, and the software automatically computes the geometric solution.

The results can be immediately manufactured on 3D printers, or further recreated as a Solid Edge model for traditional manufacturing. Designers can run multiple weight targets, load cases and constraint scenarios simultaneously, according to Siemens PLM.

Refining the real world
Recently, engineers at automaker General Motors began putting Autodesk’s generative tool to the test to cut weight from GM vehicles. Lighter cars use less fuel, emitting less carbon.
Since 2016, the automaker has launched 14 new vehicle models with a total mass reduction of 350 pounds per vehicle, says Ken Kelzer, GM vice president of global vehicle components and subsystems. The 2019 Chevrolet Silverado, for example, reduced mass by up to 450 pounds as compared to earlier model years.

To further lighten the load, as it were, in May the automaker announced an alliance with Autodesk that will use additive manufacturing and Autodesk’s generative tool to develop future cars and trucks, Kelzer says. The pairing of additive and generative capabilities is a natural for the automaker, Kelzer adds.

GM has used additive technologies for more than 30 years to print 3D parts. The automaker has more than 50 rapid prototype machines that have produced more than 250,000 prototype parts over the last decade, Kelzer says.

And the generative capabilities now included in the Autodesk CAD systems put those printers to work in unique ways, he adds. “When we pair the design technology with manufacturing advances such as 3D printing, our approach to vehicle development is fundamentally different; to co-create with the computer in ways we simply couldn’t have imagined before, Kelzer says.

But the design of formerly unimaginable parts doesn’t mean the engineer lacks ingenuity. Rather, those reduced weight, and perhaps rather odd-looking shapes are the whole point of the generative process, which provides thousands of solutions to one engineering problem, Akella says.

He gives the example of a designer who wants to create a chair. Typically, the designer would start with some geographical representation of the chair humans have taken for granted for centuries; that is, four legs, a seat, and a back. But if the designer were to begin by specifying the amount of weight the chair must support, the materials it will be comprised of, and its cost, “the designer will get hundreds or even thousands of options he or she couldn’t have conceived of on their own,” Akella says.

The nature of the creation process also allows for a part with such complex geometries that it can replace multi-part assemblies. And they can be created with 3D printing, he adds.
The process is also being tested in other industries that design with CAD tools.

For instance, architects at Arup, the building and infrastructure design consultancy in the Netherlands, paired topology optimization and additive manufacturing to redesign a steel node for a unique, public lighting and artistic tensegrity structure.

Needle Tower, public art by American sculptor Kenneth Snelson demonstrates the concept of tensegrity. The piece is located outside of the Hirshhorn Museum and Sculpture Garden in Washington, D.C.

Buckminster Fuller coined the term tensegrity to refer to a structure that uses the principle of floating compression, with parts compressed inside a net of continuous tension with cables or tendons delineating the system. Think, of course, of his famous geodesic domes.
Arup designers created their trio of tensegrity structures for a shopping street, the Markstraat, in The Hague. Unveiled in 2013, the “urban chandeliers” integrate street lighting and add an artful element to the area.

Arup architects designed several variations of the node using conventional and optimization techniques. The third figure, on the right, is the final, lightest shape attained through topology optimization.

The urban chandeliers are beautiful. But they weren’t easy to create, says Salomé Galjaard, an Arup senior designer for the project.

Due to the irregular shape of the structures most of the 1,600 nodes that connected the cables to the struts, were different due to the more than one thousand variations in angle and position of the attached cables, Galjaard told attendees at the 2015 Future Visions symposium in Amsterdam.

The Arup architectural firm created this 3D-printed, optimized node for a study of nodes used in its urban chandeliers street-lighting project in The Hague.

“This ‘uniqueness’ inspired us to learn more about additive manufacturing,” she says.
Curious as to what optimization could have done for them on a project like the urban chandeliers, Arup designers conducted a study. Both topology optimization and additive manufacture have been little used in the architectural world, so this seemed like an excellent opportunity.

After performing topology optimization, using the Optistruct software from Altair, they found the node they’d modeled traditionally closely resembled the optimized node. And yet, that optimized design reduced the weight the node from 44 pounds to 11 pounds, a 75% drop, without compromising the functional and structural performance of the product, Galjaard says.

Still, the designers spent much more time working with the complex, optimization software than they normally would, and the process could be frustrating, she says.

“Our research illustrates that 3D printing can have a positive impact on the design and production process and the functional product,” she says. “The resulting costs of future construction products could be decreased significantly, whereas architectural freedom will be increased dramatically.”

Generative design and topology optimization can bring the same design freedom and cost reduction to engineering and other types of design of course. Imagine a complex, oddly shaped part that is printed and performs as an assembly. In other words, a part beyond your imagining. That’s the promise of generative design and topology optimization.

Altair
www.altair.com

Autodesk
www.autodesk.com

Dassault Systèmes
www.3ds.com

Siemens PLM Software
www.plm.automation.siemens.com

AutoCAD 2019 with specialized toolsets released

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Autodesk released its 2019 version of AutoCAD. Included in the release are multiple specialized toolsets to help improve design productivity.

Subscribers will have access to seven specialized toolsets, more than 750,000 intelligent objects, styles, parts, features, and symbols to choose from when drawing. Designers can automate floor plans; quickly draw piping, plant equipment, or electrical panel layouts; incorporate GIS data into the planning process; edit scanned drawings and convert raster images into DWG objects all while working in a familiar AutoCAD interface.

The toolsets are:
–Architecture Toolset: specialized building design features and 8,000+ intelligent architectural objects and styles speed architectural drawing and documentation.

–Mechanical Toolset: specialized mechanical design features and 700,000+ intelligent manufacturing parts, features and symbols speed product design.

–Electrical Toolset: specialized electrical design features and 65,000+ intelligent electrical symbols boost productivity for creating, modifying, and documenting electrical controls systems.

–MEP Toolset: specialized MEP engineering features and 10,500+ intelligent mechanical, electrical, and plumbing objects to draft, design, and document building systems.

–Plant 3D Toolset: specialized plant design and engineering toolset efficiently produces P&IDs and then integrates them into a 3D plant design model.

–Map 3D Toolset: specialized mapping features use GIS and CAD data to support planning, design, and data management. Access spatial data stored in files, databases and web services, and aggregates it with your AutoCAD design data.

–Raster Design Toolset: Use raster to vector tools to edit scanned drawings and convert raster images into DWG objects.

This update is available from the Autodesk Account portal, or from the Autodesk Desktop App.

The DWG Compare feature in AutoCAD 2019 and AutoCAD LT 2019 helps users identify graphical differences between two revisions of a drawing or Xref. Quickly view changes, see clashes, review constructability, and more.

An AutoCAD 2019 or AutoCAD LT 2019 subscription also includes access to the all-new AutoCAD web app and the AutoCAD mobile app.

The AutoCAD web app gives users access to AutoCAD through web browsers or through web.autocad.com. This capability simplifies demos or consultations with clients.

Shared Views is an enhancement to the “Share Design Views” feature. This AutoCAD 2019 and AutoCAD LT 2019 feature makes it easier to share designs with stakeholders without sending DWG files to them.

The AutoCAD mobile app lets users view, edit, create, and share CAD drawings anytime, anywhere. DWGs can be downloaded to devices to access them even without WiFi. This app is available across Windows, Android, and iOS devices, and is optimized for the iPhone X, iPad Pro, and Windows Surface.

Autodesk
www.autodesk.com

Webinar: Cloud Premium: Cluster Computing Arrives for Autodesk CFD

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Following is the transcript from the recent webinar, “Cloud Premium: Cluster Computing Arrives for Autodesk CFD,” presented by James Neville of Autodesk.

My name is James Neville and I am a simulation engineering here at Autodesk. I want to welcome everyone here today to our webinar, and thank you all for coming out to learn a little bit about the Autodesk simulation. Today, in addition to giving a brief overview of Autodesk’s CDF, our flagship computational fluid dynamics program, I’m going to focus on a new feature Autodesk has recently unveiled called Cloud Premium.

My goal is to ensure that everyone on the call walks away with an understanding of how CDF can be used in the design process, how customers are being successful today, and ultimately how you all can apply our groundbreaking cloud technology to your own engineering challenges to solve faster, solve bigger, solve more. A little bit about myself before we get rolling. I’ve been working in the simulation field for a little over 12 years now. I started by career back in 2005 working for Blue Ridge Numerics, and Blue Ridge was a technology start-up with a mission of democratizing CFD for design engineers.

Back in 2011 Autodesk acquired Blue Ridge and added CFdesign to their growing portfolio of simulation products. And CFdesign serves as the foundation for all of Autodesk’s CFD products today. I’ve held various roles over the years ranging from tech support to application engineering to consulting services, and now I serve as a global CFD expert for Autodesk. I’m happy to be here today and to provide some insight into Autodesk’s simulation program. Regarding the webinar agenda today, we’ll start with a brief overview of our simulation tools. I want to give everyone a complete picture of our offerings, and then we’ll move on to a few CFD specific topics like cloud computing.

To help set the stage for Cloud Premium, I’m going to go over a bit of the history of our CFD product, and then we’ll get into the good stuff, and we’ll talk about the newly released technology. And then finally at the end we will wrap it up with some Q&A. To back up for just a minute, I think that when a lot of folks

hear the company name Autodesk they immediately think AutoCAD or Inventor, and while this may be correct, it’s only really a part of the picture of the company. Autodesk has built a complete portfolio of simulation products over the last 10 years, and we can group these products into two main categories you see here.
You got upfront engineering and advanced materials. These tools range from CFD and FDA solutions flow instructional mechanics on the left, all the way to advanced material simulation like plastic injection molding and composites on the right. Today we’ll be talking specifically about the first item on the slide here, flow and thermal analysis CFD. What is CFD? CFD stands for computational fluid dynamics. It sounds a lot more complicated than it is. Fluid refers to both liquids and gases, and dynamic simply refers to movement. A computer is used to perform these calculations, hence the term computational. In short, CFD uses computers to analyze fluid flow and heat transfer problems.

In real world terminology you can think of it as a virtual wind tunnel, or a virtual flow bench or a thermal test rig. There’s a large number of commercial CFD programs out there today, and the vast majority of them are designed for full-time CFD analysts. These programs are considered traditional CFD tools in that they were designed at the PhD level, and are intended to be used at the PhD level. Autodesk CFD is very clearly not a traditional CFD tool. While it solves the same equations as all of the traditional codes, Autodesk CFD is really intended for a different kind of user. Above all else, there is a sharp focus on automation and user accessibility to allow more users to leverage the benefits of CFD earlier on in product design.

The vast majority of our successful users wear multiple hats, and don’t have cycles in the day to run simulation tools full time. Autodesk CFD utilizes a design study environment, and this allows our users to analyze and compare a large number of design variance, instead of just looking at, say, one at a time, and there’s a sharp focus on automation within Autodesk CFD. And our meshing technology is really no exception here. Fully automated mesh, auto sizing and results based adaptation allow both novice and expert users to obtain accurate, repeatable results with really minimal effort. And finally, Autodesk CFD is the only upfront tool, only upfront CFD tool I should say, on the market today that provides infinite computing power through cloud access for design engineers, and I’ll be diving deeper into this topic here shortly.

You heard me say upfront a second ago. Upfront really refers to a certain point in time in the product development process. Earlier on in product development we have much more opportunity to affect change, and the associated cost of these changes is relatively low. As product development matures more and more items become set in stone, less can be changed, and the cost of any changed dramatically rises. Upfront simulation means leveraging powerful simulation tools in the design and engineering phase where they have the most value to us. From the ground up, Autodesk CFD is an upfront simulation tool.

You may ask what do our customers simulate with Autodesk CFD, and I’d like to rephrase it, I think a better question might be what don’t they simulate. As a general purpose tool, we find that our customers use Autodesk CFD in literally every industry across the globe. You’ve got microscopic medical devices, ceiling fans, Indy cars, stadium wind studies. The tool is really designed to be accessible to all users in all industries. All right, I have a handful of poll questions here and I’m curious to see everyone’s responses. I’ll share the poll results after everyone has a chance to chime in.First one here, in the event that your organization encounters say a flow or a thermal challenge, go ahead and pick which method best fits how that challenge would be addressed today. There’s four options. You’ve got hand calculations, building and testing. You know classic build, test, fail, built, test fail. Outsourcing, that could be outsourcing it just to solve a problem. Outsourcing it for CFD services somewhere else, or in house CFD. Go ahead and submit your answers and I’ll tally them up here in about 15 seconds or so. I’m going to pick in house CFD. All right, we’ll go ahead and take a look at those. That’s higher than I thought. That’s good. Equal votes for hand calcs, build test, outsource, and then 50% of the folks on the call do in house 50. That’s good to know.

I think more and more companies are using CFD these days, bringing it in house as the costs drop. I think Autodesk moving to a subscription based software delivery has helped that greatly. Thank you for answering that one. I’ve got another one here. Here’s the next one. This one’s a simple yes or no. Basically, does your organization use the cloud today for product development? That could be collaboration, asset storage, simulation processing. If you’re already using the cloud basically a simple yes or no here. Let me take a look at the answers here. This one’s a little surprising. I see the vast majority have reported back no. That’s very curious. I’d be interested to dig in with each one of you guys or gals about why that is or maybe help illustrate some of the benefits of cloud computing.

We’ll be chatting about a couple of those here in a second. This is my final poll question. The last one for you. If you think back over the last two years, or even maybe what you had projected for the coming year, about how many unique projects do you estimate could benefit from flow and thermal simulation? All right, we’ll tally these up here. It looks like 50% are at 1-2. The next one up there is 3-4. No one at more than 10. I actually put in a vote for more than 10, but I’m not sure my vote counts. Looks like most of it 1-2. We actually find when we look back over our data from all of our customers over a very long time span, the vast majority of our successful simulation users leverage CFD for four projects per year.

That doesn’t mean four simulations per year, but in general they’re using it for around four projects per year, and that’s using it maybe hot and heavy for a couple weeks or maybe a month or so and then putting it down for a little while. That’s really what the tool’s designed to be good at, and that’s what our data shows. Interesting. Looks like most folks out there have some projects that could benefit from upfront simulation though. All right, let’s get into cloud computing. I think it makes sense to go over some of the history of cloud computing at Autodesk to give Cloud Premium some context. When Autodesk acquired CFdesign in 2011, the CFD solving technology was fully optimized for local machine solves.

Whatever resources were available on a local machine, CFD would utilize to the fullest. You had 2 cores, 8 cores, 16 cores, it just didn’t matter. Once core counts started to reach 16 and higher we did start to see a bit of a diminishing return with additional resources, but in general CFD solving performance grew linearly with hardware. As users obtained faster hardware CFD would take advantage of it. If users say upgraded to faster clock speeds or more cores they would see solve speed benefits. However, with just one license, one CFD license, users were limited to solving one job at a time. But the only real way around this was to purchase additional licenses and additional hardware. That’s a pretty find solution for large companies, large customers who have leverage CFD to solve problems year round, but the vast majority of our customers used the tool in brief bursts when the need came up and therefore couldn’t justify those kind of costs.

In 2012 Autodesk rolled out cloud solving for CFD, and in a nutshell this enabled users to off load their CFD analysis through the AWS cloud where the job would be solved remotely. A single user with only one license of CFD could solve simultaneously for 10, 50 jobs at one time. No additional license was required, no additional hardware was required. Each job would cost 15 cloud credits, and on demand

cloud computing really became the norm for us. Our CFD users essentially had access to on demand remote work stations to solve more jobs in the same amount of time. In the past year alone, I’ve got the numbers here for you, in the past year alone 23,700 jobs were submitted and solved on the cloud via Autodesk CFD.
Our product development team gave me some conservative numbers last night regarding the total number of simulations submitted since cloud computing arrived for Autodesk CFD five-ish years ago. The number is staggering. Over 191,000 jobs since 2012. It’s ridiculous. Acquirements like expensive local hardware, heavy laptops having to go back into the office to check on the status of a lengthy overnight simulation. I’ve done that many times. They’ve all gone away. On a personal note, as a CFD power user, up until this year I’ve always managed to have both a very powerful desktop computer and a powerful and heavy laptop for travel, and I’ve recently downsized greatly to now function of a single high end Ultrabook. I can do infinitely more work from this one device than I could do with maybe five or 10 local machines previously because of the power of cloud computing.

That brings us to now where Autodesk has just release Cloud Premium, which is more or less our industry leading cloud technology on steroids. Cloud Premium is a new option in Autodesk CFD 2018. Users can now select to have their jobs solved on the traditional cloud or on Cloud Premium. Standard cloud jobs are solved on a … Just give you some details on what’s going on in the background. But standard cloud jobs are solved on a single Amazon EC2 instance with 8 physical cores and provide performance comparable to say a high end local machine. Cloud Premium jobs are different. They’re solved and distributed on 16 EC2 instances, each with 16 visible cores. The list distributed computing network allows for a much faster simulation and enables users to solve jobs previously not possible.

Cloud CFD job costs are calculated from a really wide range of variables like model size, requested durations, problem physics, etc cetera. There’s a number of things that we look at. And Cloud Premium jobs will have a multiplier 4 X. They’ll involve a 4 X multiplier over the standard cloud job cost. I’m going to jump right in and share a few examples to illustrate some performance metrics. Starting with internal flow through a plug valve, I’ve got results from Cloud Standard and Cloud Premium this year. We’ll look at this same problem with a few different mesh sizes to show what kind of real world performance gains are to be had.

At a median mesh density of say 5 million elements solve time dropped from around three hours to just under one hour. That yields a 3.1 X speed up. When we bump the mesh count up to 11 million elements, which is starting to get pretty large, the solve time drops from 8.2 hours to an hour and a half. That’s a 5.4 X speed up. Now we’re starting to see some impressive gains. With Cloud Premium, this problem was just reduced from a complete work day of time down to basically an extended lunch break. We have similar performance gains of around 400%. They’re shown when the model size is increased to 14.7 million elements, that’s a pretty big model, we go from 10 hours down to two and a half hours. And then finally we arrive at a 30 million element job.

This is a very large job. It requires an entire day of Cloud Standard simulation time for completion. Cloud Premium manages to crank this simulation out 4.5 times faster at only five hours. The next set of simulations take this performance improvement to a whole nother level entirely. External aerodynamic studies, external flow, these simulations exhibit two properties that typically result in long run times. I think anyone who’s run external flow they’ve run into these. But the first is just the sheer model size.

Often times the mesh required for an accurate solution can be very, very large. The second is just the number of iterations required for convergence. Due to the number of the complex flow structures, the wake structures, many iterations are typically required to fully resolve the flow field.

Cloud Premium really excels at both of these challenges. At a relatively small mesh size of 1.6 million elements Cloud Premium shows a 5X speed up for this race car rear wing assembly. When we bump the mesh count up to 11.3 million elements Cloud Premium hit the sort of sweet spot here and solved this problem 27 X faster than Cloud Standard. That’s 27 times faster. We go from 30.2 hours in Cloud Standard, down to 1.1 hours in Cloud Premium, and all of this performance improvement was accompanied with a slight increase with simulation accuracy as well. Jumping up to 20 million elements, showed a still amazing 10 X speed up for Cloud Premium. And when we run the numbers on jobs like this, jobs that are this large, they just become staggering.

Simulation time dropped from almost 50 hours, that’s over two days, to just five hours, and all of this with equal or superior result accuracy. The plotting these two examples here show how large model sizes previously resulted in lengthy run times of entire work days or even multiple days. They reduced to just a, reduced, excuse me, to just a few hours with Cloud Premium. It’s clear that Cloud Premium has the most benefit for simulations with large element counts. Gains are expected at most model sizes, but the true value of Cloud Premium is realized when users can reduce their simulation run times from days to just hours. In general, users can expect a four to five X speed up for most general purpose simulations.
Certain applications, like the one I just went over, external flow, they show dramatically greater performance improvements on the order of 10 X or more. And our benchmark testing has shown that Cloud Premium simulation accuracy is as good or better than Cloud Standard, and users can basically expect the same great simulation fidelity that they’re used to from Autodesk CFD. Where are we going with this? Cloud Premium is a very exciting technology for us here at Autodesk. We’re excited to roll it out to our customers, and frankly we’re excited to use it ourselves. It really wasn’t that many years ago when CFD was limited to in [inaudible 00:20:48] jobs and memory limitations and scenarios where customers weren’t sure if they were going to get their simulation work done in the desired time frame.

Cloud solving technology is really removed all of those barriers. One of the key advantages to Cloud Premium, one of the advantages that it holds over local solving is that the hardware and software can evolve in real time. This technology has been available for, I’ll give you an example, this technology has been available for customer usage for only a few weeks now, and we’ve already rolled out several performance improvements where we found gains to be had. As the software evolves, as new technologies are added, as more functionality makes it way into Cloud Premium, users will have access to all of this with their current subscription to Autodesk CFD.

As hardware evolves and the cloud network speeds are improved we do expect dramatically improved performance even over what I’ve shared here today. Since that solver technology resolves in the cloud no client updates are necessary to take full advantage of it. In summary, Cloud Premium and Autodesk CFD is the first in product high performance computing cloud solution period. With Cloud Premium users have on demand access to 16 cloud machines each with 16 cores, that’s 256 cores total, all working together to solve a single simulation. And users can expect to see performance gains of at least 400%, and they’ll be able to simulation jobs far larger than what is currently possible on a single local machine or in Cloud Standard.

With that, I’d like to open it up for some Q&A. It looks like we have a number of questions submitted already.

Q: First up, how do I know how many credits I have?

The number of credits you have, the number of cloud credits available to each user, you can find them in your simulation job manager. You can also find them in your Autodesk account. I think it’s manage.autodesk.com. That’ll show you how many credits you have available. If you get low you can always purchase more at any time. Between the simulation job manager and your Autodesk account it will give you an idea of how many credits you have to solve.

Q: What is the number of time steps required to reach convergence, or why is that different between Cloud Standard and Cloud Premium case?

Great question. Probably refers to some of those metrics that I shared most specifically with the race car rear wing assembly. What we did with our … Not we, because I didn’t do it. But what our product development team did was they took out the best of the best from our Cloud Standard solver and rewrote that for a massively parallel architecture. That’s distributing this load over many, many works and many cores on each one of those workers. It is truly a new solver. It is a different solver. It’s solving the same equation that we solved previously, but it is a different approach and a different solver.

The number of iterations required will be different than say when you’re comparing Cloud Standard to Cloud Premium. What we’re finding though, especially for some of those challenging problems in Cloud Standard or a traditional local solve where it might take many hundreds or even thousands of iterations to reach a nice convergence, Cloud Premium is really ideally suited for those problems because it can solve them in a fraction of the number of iterations. It is a different solver. You will likely see different solver iteration counts in your convergence plot. But as far as the equations we’re solving and the level of fidelity and accuracy that is as good or better.

Q: How long does my data stay on the cloud?

Good question. The data that we send up for the cloud, it’s model specific data contains basically your mesh and set up conditions and it’s very similar to what we would solve on your local machine. We don’t send a CAB model up, but we do send your simulation mesh and the associated boundary conditions and all good stuff. As soon as the job is complete it comes right back down to your analysis. In fact, this is a unique way that Cloud Premium works, but when you solve a job in Cloud Premium, as soon as you hit solve, it’ll actually spool up all 16 of those machines. It usually takes around four to six minutes.

You’ll get a little notification in your output window that says, “Spooling jobs takes X number of minutes.” And then as soon as that job is done all of the data sent back to your local machines, and those instances, those AWS instances, are then shut down. All data is removed from them as soon as the job is completed.

Q: How many jobs can I solve at the same time, and can I shut my machine down while solving on the cloud?

To the first one, “How many jobs can I solve at the same time?” That is infinite. There’s probably … I don’t know if we’ve run into a limit with the number of AWS instances that we can spool up at a given time. But most users I think have launched more than one job at a time. But I think the most that I’ve done is around 30. I definitely haven’t hit a limit yet. As far as I know there’s no limit to how many you can solve assuming you have enough cloud credits to support the request.

The second one there, “Can I shut my machine down while solving on the cloud?” Absolutely. Very similar to what happens on a local solve, let’s say you have an analysis. You’re going to get it off on your laptop of your local work station, you can actually close the interface at any time. The interface and the solver are separate entities. They communicate with each other, but they’re not necessary. You don’t have to have the interface up for the solver to do it’s work. It’s just like that in the cloud too. It works the same way with Cloud Standard and Cloud Premium.

Once that job’s submitted you could close your interface down. You could close your lid on your laptop. You could pull the plug. You can turn off your network card. It just doesn’t matter. Once you reconnect your laptop to the internet it will reconnect to the job. If the job’s done it’ll download. If it’s not done it’ll download interim results and as soon as the job completes then the rest of the data will be sent back. You can fully remove your local work station or laptop from the cloud solve. That’s super handy because if you launch a job at 4:55 and you rush home to make dinner or to get dinner or whatever, then you plug your computer back in at 7:30 or eight o’clock then you can check your jobs from really location as long as you have an interact location, or internet access.

Q: Could you comment a little bit about the pricing in general?

Yeah, sure. The pricing tiers, we introduce pricing tiers recently in CFD 2018. Previously, all jobs would cost 15 credits in Cloud Standard. This year there’s a multi tier … There’s a calculation that basically determines which tier you’re in. Basically tier one is 10 credits. Almost all of the jobs that are submitted on the cloud are 10 credit jobs. There’s a medium tier of 30 credits, and then an upper tier of 100 credits, and that’s for Cloud Standard. When you launch a Cloud Premium job there’s a 4 X multiplier on the 10, 30 and 100 credit tiers.

Q: What’s the speed of post processing results on the cloud and sending graphics as well as other information to the local machine?

It’s exactly the same as Cloud Standard. The only thing that changes to the user is that it’s when you hit the solve button and there’s a pull down for whether you want to solve locally, whether you want to solve on Cloud Standard or Cloud Premium. That’s the only difference to the user, the extra option in the pull down step. Everything else is the same. Model set up is the same. Results interaction is the same. If you’re familiar with CFD already, it’ll preform exactly the same way as it did previously.

Q: Do I need to download any other software to use this?

You do not. You do have to have the latest update for CFD 2018, which should be available through your Autodesk download manager. You can always get it on I think it’s on your manage.autodesk.com website. The 2018.1 release grants access to Cloud Premium.

Q: Who has access to my data, and what data is up there?

You have access to your data. We do not. The data that we … We have statistical data. We have log files that contain information about where the machine originated, where it’s solving, information about whether the solve was successful or whether it failed. If a job fails in the cloud we do not charge you for those cloud credits. That’s the sort of data that we gather. But the data, it’s accessible only to you in your local account.

Q: Can a user choose any number of cores, say between 8-256 when using Cloud Premium?

Currently no. That’s a good question. Currently the number of cores that we’re using in Cloud Premium is 256. We recognize that there might be some problems that are more optimal for say 512 cores. There might be some problems that are more optimal for 64 or 128. But as of right now we’re sticking with 256 cores for all Cloud Premium jobs. And what we’re finding is that jobs that are very small, say a million elements, under a million elements, things that would solve relatively quickly on a local machine, they’re not ideally suited to be solved on Cloud Premium.

For one, it’s four times more expensive for probably no performance gains. And two, when you spread out a small job over that many cores, that many systems, it just doesn’t function well with so much communication between all the machines that you don’t really get any performance gain. What we’re finding is that 256 cores is a nice sweet spot for medium to large to very large problems right now.

The Self-taught design system

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Just where will artificial intelligence fit in with CAD software? Here’s a look at where developments stand now, and a preview of what might be coming.

Jean Thilmany, Contributing Editor

Artificial intelligence has a place in the future of computer-aided design technology, but right now, the role AI will play isn’t clear. That’s the view of Jon Hirschtick, chief executive officer of Onshape, which makes cloud-based CAD software. While some CAD makers are delving into AI functionality, the marriage of AI and design software is in the early stages, he says.

“AI has great potential, but so far no one has illustrated how it will unfold,”

Hirschtick says in reference to CAD vendors. “I’m not saying developers are not working on ideas.”

CAD makers would be wise to consider how AI may fit into their software’s growth and expansion. AI should be a $16 billion industry by 2022, according to a projection from research firm Markets and Markets.

AI across industries

First, definitions are in order. Many terms have been bandied about of late, particularly in reference to Industry 4.0, which goes by a number of names, including smart factory and connected factory. Technologies like artificial intelligence, machine learning, big data, Internet of things (IOT), and deep learning will come together to help realize Industry 4.0.

Nvidia installed its Drive PX 2 AI supercomputing platform into a signature- green, self-driving racecar that will compete in the Roborace Champsionship, a global autonomous motorsports competition. Image credit Nvidia.

All these technologies are related in that they build upon each other, says Will Ramsey, director of marketing at Nvidia, which designs graphics processing units. The company developed GPU-based deep learning, which uses artificial intelligence to approach problems like cancer detection, weather prediction, and self-driving vehicles. Here’s how Ramsey defines pertinent terms:

“AI is a broad field focused on using computers to do things that require human-level intelligence. It’s been around since the1950s but was little used because it was limited in practical applications.”

“Machine learning enables AI by providing the algorithms that make the machines smarter and thus give AI a way to actually become more intelligent as time goes on.”

Machine learning is what Ramsey calls an approach to AI, meaning a way to use AI for practical applications. The approach uses statistical techniques to construct a model from observed data. It relies on inputs, or what Ramsey calls “extractors” set by the humans programming these machines.

“It’s like the bag-of-word analysis that made spam filters possible,” Ramsey says.

The filters could search for certain words (determined by humans) within messages, then flag those messages as unwanted spam.

Machine learning algorithms can sift through and find insights in large data sets. Combine AI and machine learning and the algorithms become more able to recognize patterns and specific issues, such as—when it comes to something like speech recognition software—accents.

But where does the data used by machine-learning algorithms come from?

Earlier this year, Nvidia revealed a self-driving car powered by its new AI supercomputer, Xavier, which learns to drive by observing a human driver. Nvidia installed the AI in an autonomous Lincoln vehicle to demonstrate its capabilities. Nvidia Drive PX is an open, artificial intelligence-driven, computing system that can be used as the technology platform for automated and autonomous vehicles. Nvidia developed its own self-driving vehicle to showcase the system.
Image credit Nvidia.

“Now with social media, sensors, the internet of things, we have all these data,” Ramsey says. “And we have the challenge of understanding and extracting insights from it.”

His company uses what it calls deep learning, a method that automatically extracts and makes sense of all that information, and continues to learn from it or “learns to think.”

“Using deep learning, the fastest growing segment of AI, computers are now able to learn and recognize patterns from data that were considered too complex for expert written software,” Ramsey says.

What about design?

Hirschtick believes CAD programs will make use of AI, but in a more limited way in the near future, by using information the designer has entered to offer suggestions about design parameters and inputs.

Future programs might offer to the design default values for a shape based on the objects that person has designed in the past. AI would essentially learn what types of products the designer mostly works on and the inputs he or she has regularly used for those products. The suggested values may appear on the user’s screen in a dialog box, Hirschtick says.

“Or AI could offer something like: ‘Gee, I noticed you’ve done pattern of activity several times in a row, do you want that or was that a mistake?’”

And AI could make engineers’ search for needed and necessary parts easier. Hirschtick envisions a program, much like that which appears for Amazon shoppers, in which engineers could type in information about a part they’re searching for “and the program says ‘a lot of times people looking for that part also look at this one,’” he says.

Today’s wind turbines, like this one installed in Traverse City, Mich., can be outfitted with a myriad of sensors and actuators that will return real-time turbine operating information through the Internet of Things. Image credit: bengarrison

In the future, CAD software users may also ask speech technology software, rather than the CAD-company’s tech-support operators, questions about the software and instantly receive a pertinent, helpful response. The natural-language-processing programs that drive these responses learn how best to answer user questions thanks to machine learning technology.

Such speech technology software could aid fast-growing CAD companies that would otherwise need to train a slew of customer-support employees quickly.

Currently, those AI possibilities remain unrealized, says Hirschtick. “Right now no one has demonstrated any particularly compelling idea with AI.”

Making manufacturing inroads

Other CAD vendors may beg to disagree.

Autodesk is already moving to use AI for customer support, teaming with IBM to create Otto, a digital concierge that uses IBM Watson technology to manage customer and partner inquiries, says Gregg Spratto, vice president of operations at Autodesk. “Watson’s natural-language-processing and deep-learning technologies help Otto understand the intent of customer questions.”

To offer Otto initial “training,” as it were, the Autodesk team fed historical data from chat logs, use cases, and forum posts into the program to ensure it could understand and respond to a wide range of customer queries.

Then, as the project expands, Otto will use machine learning to handle increasingly complex customer requests and will scale up as call-volume grows.

Also, last October, Autodesk announced plans to embed an AI modeling engine into its IoT cloud platform, Fusion Connect. The Eureqa engine is from Nutonian, recently acquired by DataRobot.

With the AI engine on board, the IoT platform will be able to predict product failures or design flaws based on how a product or device is presently functioning in the real world, says Bryan Kester, director of IoT at Autodesk

The pairing is natural, as IoT offers continual feedback on how products are performing in the field, in real time. IoT makes use of sensors and actuators attached to a product that send back continuous information on how the product is operating, moment-by-moment, in the field.

Fusion Connect helps gather information from that network of sensors and actuators as well as upon RFID, Wi-Fi, and a range of other communications and monitoring technologies, Kester says.

The information is then analyzed and output in a format useful to engineers, who can use it to find where improvements can be made to existing product designs and to determine how new products could be designed better designed. All this based on present, real-world operation, he adds.

Similarly, PTC plans this year to link its Creo computer-aided design system, to the company’s ThingWorx IoT development platform. Developers use the platform to build and deploy enterprise-level IoT applications, says Paul Sagar, vice president of product management at PTC.

Though it’s not an AI application, after the ThingWorx and Creo interface is complete, engineers will be able to instrument their CAD model with virtual sensors that act in the same manner as the real-world counterparts do; that is, they monitor and report back about particular features of part or system operation.

These virtual sensors can offer more insight into model behavior than the what-if questioning and virtual experimentation engineers now use to explore model performance, Sagar says. The sensors can help answer questions like: is the virtual system running hot in a certain area? Is airflow too high or too low?

Fusion Connect Internet of Things software from Autodesk can help connect factory applications across a number of industrial machines and make sense of information returned from the connected machines. Image credit: Autodesk

With those questions answered, designers can redesign and repeat the process until they’ve optimized the model to meet—perhaps even exceed–specifications, Sagar continues.

AI aids 3D lookup

Introduced last summer, Autodesk’s Design Graph is another machine learning system that helps users manage 3D content, offering Google search-like functionality for 3D models, says Mike Haley, who leads the machine intelligence group at Autodesk.

“Machine learning and artificial intelligence are starting to make the first inroads into daily life, but to our knowledge this is its very first application for industrial design and mechanical engineering,” Haley says.

Design Graph algorithms extract large amounts of 3D design data from an engineering company’s designs. It then creates a catalog by categorizing each component and design using a classification and relationship system. Designers and engineers search across all of their files for a part type, such as a bolt or a bike seat, with the tool returning dozens or hundreds of pertinent options.

So how does machine learning come into play?

The system teaches computers to identify and understand designs based on their inherent characteristics–their shape and structure–rather than by tags or metadata, Haley says.

After all, whoever designed the part originally could label it any of dozens of ways, using full words or abbreviations. Metadata created by people, unless carefully managed, tends to be unreliable, Haley says. With Design Graph, the computer uses its own observations about the 3D geometry contained in every 3D model.

So while some AI capabilities already exist within CAD systems, look for more to come. After all, product design plays a key role in the connected factory and the IoT systems of the future. Without design, there’d be no need for a factory—no matter how connected–to make the products and nothing for IoT to monitor.

Autodesk
Autodesk.com

Nvidia
Nvidia.com

PTC
Ptc.com

Onshape
Onshape.com