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Expanding Capabilities with Partnerships: Autodesk Fusion and Ansys Synergy

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Description

This class will uncover the expanding capabilities of the Autodesk Fusion Electronics workspace Signal Integrity Extension, tailored for the modern demands of rapid design in connected consumer products. We'll focus on the groundbreaking partnership between Autodesk and Ansys, which is revolutionizing printed circuit board (PCB) simulation processes. Participants will learn how this collaboration enhances simulation precision and speed, enabling engineers to accelerate product development and market entry while conserving resources. Discover practical strategies and tools that you can integrate into your workflows to optimize design efficiency and effectiveness. This class is ideal for professionals seeking to use innovative PCB design complemented with simulation technologies to stay ahead in a competitive market.

Key Learnings

  • Learn about collaboration for innovation, including how strategic partnerships can foster innovation and competitive advantage.
  • Learn how to apply signal integrity capabilities during the design process, enabling effective product development.
  • Learn to interpret and validate results of simulation for PCB signal integrity, which no longer needs to be post process.

Speakers

  • Juliano Mologni
    Juliano Mologni is the Lead Electronics Product Manager at Ansys. Over 20 years of experience in computational electromagnetics, author of more than 60 peer reviewed journal and conference papers and patents related to automotive EMC. Involved in several RF and EMC projects with top Automotive, A&D, Appliances and High Tech companies. Previous experience includes being a Lead Application Engineer at ESSS, responsible for ANSYS electromagnetics initiatives in South and Central America, Systems Engineer at Delphi Automotive Systems in charge of wiring harness design and hardware engineer at WebTech Wireless. Holds a BSc degree in Telecommunication Engineering, a MSc degree in Microelectronics and his PhD thesis involves research on Automotive EMC and Signal Integrity.
  • Avatar for Edwin Robledo
    Edwin Robledo
    Embarking on my career in the communications industry, specializing in implementing fiber optics communications and data management, I transitioned into a more intricate sphere that allowed me to engage with circuit board designs through my association with the EAGLE PCB Design team. I extended my professional journey seven years ago by joining the Autodesk Fusion 360 team. Since then, I have created marketing content encapsulating various media, including blogs, videos, articles, landing pages, and webinars. This multi-faceted approach has been targeting promoting the electronic design capabilities of Autodesk Fusion, reflecting on my experience of electronic design and implementing marketing strategies that align with the industry's contemporary demands.
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Transcript

JULIANO MOLOGNI: So let's get started with our safe harbor statement. The presentations during this event may contain forward-looking statements about our outlook, future results, related assumptions, total addressable market acquisitions, products and product capabilities, and strategies. So those statements just reflect our best judgment based on the information that we have today. So just keep that in mind while we go through the presentation.

So today, our topic is "Expanding Capabilities with Partnerships: Autodesk Fusion and Ansys Synergy." So my name is Juliano Mologni. I'm a product manager here at Ansys. I'm responsible for some of our electronics products, and I also have Edwin Robledo from Autodesk. He created all the Fusion slides from Autodesk.

So we're going to cover, basically, two main topics. The first one is an overview of Fusion, which is the Autodesk cloud 3D CAD CAM/CAE software, and how Fusion Electronics works, and the reason for this partnership. Here at Ansys, we're embedding some of our access tech knowledge-- simulation tech knowledge into Fusion through an extension that we call Signal Integrity. So we're going to have two main parts. First one will be an overview of Fusion, and the second one will be an overview of the Signal Integrity extension.

So let's get started with Fusion. Autodesk Fusion is a cloud-enabled platform for design and manufacturing. So you have all the ability to create 3D models, as well as design printed circuit boards for electronics. Fusion is a web based product that can-- covers all your design requirements and create all the required files for your prototypes and manufacturing.

In Fusion, we do have an electronics. So we're going to try to highlight here the electronics part of Fusion. We have a collaborative environment, where mechanical CAD engineers can collaborate with electrical CAD engineers that are responsible for the printed circuit board design. We can make sure that PCB fits into an enclosure, right? And we already have, in Fusion, a very comprehensive library of components, and you can create your own.

We also provide, in Fusion, capabilities to simulate thermal and also some SPICE models. We have schematic design, PCB layout and routing, integration from the PCB into the 3D mechanical CAD. We also have a section for manufacturing. One of the things that we also provide in Fusion, it's the computational fluid dynamics for thermal management and cooling. And one of the focus, or the main focus of this presentation, will be the Fusion Signal Integrity extension.

So in this next slide, what we have here is a video that shows how we have, in Fusion, a case-- a 3D case. This is an air quality sensor. And you can see here the 3D CAD. What we can do is to make sure that we have this CAD, and we want to design a printed circuit board. And we want to couple them together to make sure that the PCB will fit in there.

So on the electronics part of Fusion, in here, you have the schematic. And you have all of your components. The first thing that we can do is bring that 3D geometry and couple that into our schematic and PCB design. So here, in this particular case, what we are seeing here is the 3D outline into this board where we have all the components. You can autoroute the traces. You can manually design the traces. And you can see here that the design of the PCB really fits into the 3D enclosure.

You can manipulate your components. You can see that the traces updates in real time. And you can also go to our library and create components. We have all the IPC rules in here, and you can use one of the components that is already available in the library. But you can easily create any component so you can use in your design.

Here, in this case, we brought the PCB, and we are creating the full 3D model of the electronics CAD, electrical CAD, and your mechanical CAD. Here, you can see that in the mechanical CAD, for some reason, if you need to manipulate or move a component, that reflects on the PCB design. So the mechanical engineering can affect the PCB design, if that's required.

In the end, what you can do is perform some of the simulations. One of the capabilities that we have in Fusion is the computational fluid dynamics you see here. You can see temperature because of-- your electronics will heat. So you want to run some thermal management analysis. And you can also see how this prototype will be manufactured.

Focusing more on the Signal Integrity extension, that's some of the Ansys technology that is embedded into Fusion electronics that enables PCB designers to get some insight with respect to the signal integrity or the electrical signals in your printed circuit board. At the Autodesk Fusion, you don't have a comprehensive technology for Signal Integrity as we have here at Ansys.

And the idea is not to bring that-- everything that we have at Ansys, bring that into Fusion. What we want to do is to provide some basic information that enables all the PCB designers to take quick decisions, right? And, of course, if they need to sign off their design, they can send all this information to Ansys and run a full comprehensive signal integrity analysis.

So the whole idea is that this technology does not replace the dedicated signal integrity experts that most of the companies today, they have, right? The whole idea is basically to use the 80-20 rule, is to provide some feedback early in the design cycle to avoid most of the common signal integrity problems that you can have in your PCB design. Of course, if you need some more sophisticated analysis, you can send all that information back to Ansys and run any kind of simulation-- thermal, electromagnetic, or even mechanical.

So let's focus more now on the background and the technical details of this Fusion Signal Integrity extension. So before we get started, let's talk about Signal Integrity, right? So you have your phone. You have your TV. All of that images and sound that you see on the screen, there are actually electrical signals that are traveling on your printed circuit board, right?

And we need to make sure that the design of your printed circuit board does not affect those signals because you want to see a very high-quality image. You want to communicate wirelessly with someone. You want to hear your song, your music without any noise, right? So signal integrity is all about maintaining the quality of the signal. What we do is that today, we have those digital signals that you can see here. And if you overlap all those-- what we call bits, you can get that eye diagram that you see on the right-hand side.

What's the most important metric in this particular case is that those electronics needs to understand what's the 0 and what's the 1 because we're transmitting digital signals. So that eye must be as wide and open as possible.

The biggest problem is that, depending on how you're designing your electronics, your printed circuit board-- the width of the traces, vias, and if you're using connectors and cables, that can affect the signal. So for example, here we have a signal that is being transmitted from point A. And you can see the signal is very clear, right? Those rectangles splits. As the signal propagates through the print circuit board's connectors, you see that there are some distortions, right? And what we want to do is to avoid that. And the design of the PCB really affects the signal integrity itself.

Here, we have in this example on the left-hand side a transmitter where we have that eye diagram. It's a very open eye. As the signal travels through this, what we call serial channel, it will see some bands on the traces, vias. And every time that you see that-- what we call an impedance discontinuity, part of the signal can be reflected back. Part of the signal can radiate, creating what we call electromagnetic interference. That's also undesirable. And part of the signal, of course, travels through the channel until it reaches the receiver.

So what we want to avoid is what we see here, that closing eye and that signal degrading in its quality. And there are many physical challenges that we see that affects signal integrity. One of them is the attenuation due to the dielectric and conductor materials. Your electronics, your printed circuit board, you have a stack up, which is usually a dielectric, usually FR4. Or it could be a mag 6 for backplane service. It could be reflections due to those 3D geometries, like vias.

So you have one trace that it's one layer of your printed circuit board, it needs to go to a different layer-- depends on how you design your vias that connects those layers. Part of the signal can be reflected back, as you can see in this animation in the middle of the screen.

We also have dispersion of the electromagnetic energy to the dielectrics and non-ideal conductors. So your copper is non-ideal, right? We have skin depth. You have copper roughness, etching effects, manufacturing tolerances that can also affect the signal.

And we also have crosstalk due to signals that are nearby, right? So if you have more signals that are close to the traces, that is transmitting the digital signal, you're going to have some electromagnetic interference, some crosstalk.

So one of the main things that all the PCB designers, they need to keep in mind, is to design those traces to keep a specific characteristic impedance, usually 50 ohms for single-ended nets and 100 ohms for differential nets. Characteristic impedance is one way that you can characterize transmission lines. So basically, what you have is one piece of copper, one net, one trace of copper. Then you have a dielectric, and you should have a return path-- a plane, right?

And if you create a cut on that, a cross-section cut, you see what we have here in this picture on the left-hand side. What's very important is that you can analytically calculate-- based on the width of the traces, the height of the dielectric, the height of your layers, the type of the material that you're using as a dielectric, you can compute this characteristic impedance. You can see here the equation, right-- the analytical equation. So again, usually 50 ohms for single-ended nets, 100 ohms for differential pairs.

Here's one example on how the thickness of your dielectric, your stackup, can change the characteristic impedance. Usually when you are going to use a specific microcontroller, an IC, the vendors, they provide some evaluation boards, the [INAUDIBLE]. And usually people just replicate that into their boards.

However, if you're using a different stackup-- meaning the same layout, but a different thickness for dielectrics or different material for your dielectrics-- that can change the characteristic impedance. You see here that as we change the thickness of the dielectric, the characteristic impedance here, this red plot, changes. Now it's 34, right?

You see that the eye is very closed. As we increase the thickness for a specific thickness, you see that we got 50 ohms. That is what we want and the maximum eye height. So the maximum-- or the better, the best signal integrity in this case.

And why do we have to keep 50 ohms? Usually the transmittal and receiver, they are 50 ohms. So your trace needs to be 50 ohms. If you have, for some reason, something on your trace that changes that impedance, you're going to have something-- what you see here on the bottom animation. On the top, you see a perfectly 50 ohm transmission line, a net that is sending a signal.

You see on the right-hand side the pulse. So the amplitude of the green pulse, on the output is 953 millivolts. So there's a little bit of attenuation, but it's there. In red is the reflection that you see on the input port. And down on the bottom, we did something just to change the impedance in the middle of the trace. We changed the width of the trace. And you see that now the signal sees a 32 ohms impedance.

And when the signal see that difference in impedance, part of the signal is reflected back, as you can see on the animation. And also on the plot on the right-hand side, you see that the green pulse decreases even more because part of the energy is reflected back, as you can see on the red plot. So what you want to do is try to avoid this. You want to avoid those impedance discontinuities.

So we saw that we can analytically calculate the characteristic impedance for all of these cross-sections. But if you take a look at your PCB, just a single net, the yellow one that you can see here, you can have many, many cross-sections. So in this case, we have 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 cross-section. So you have to do this for all of these 10 cross-sections. And you can't use the same equation because, each of these cross sections, they change.

Sometimes you have another trace nearby. Sometimes you don't have the reference plane. Sometimes you have two traces, right? So do these manually. It's not only error prone-- so you can make some mistakes-- but it's also take a long time.

So that's the reason we have the Signal Integrity extension. So with the click of a button, you can get, almost near time, the impedance for all of these cross-sections of your net. So in this particular case, we click the button, and you can see here the impedance for all the segments. And you can color plot that in your layout. So we grayed out all the other nets, and you can see that the color bar is showing the impedance on that trace.

We also compute resistance, capacitance, inductance per unit length for all of these segments. So instead of trying to do that math equation manually for all of these cross-sections for your entire board, which can take a long time, you can just click a button, select your net, click the button, and get all the results.

One thing that I want to mention is that we use an Ansys physics-based solver inside Fusion to provide that kind of information. We use a Method of Moments multi-conductor transmission line coupled to a parallel plate solver, which means that we take into account, without any simplifications, your entire layout, including your materials properties, electromagnetic properties.

So you have permittivity. You have lost tangents. We take that into account. We take the thickness and the design itself. So we consider all of that to compute impedance RLCGs. And you can see here, we can compute electric field, magnetic fields, and things like this that can provide some insight into the signal integrity of your design.

This is how you use the Signal Integrity extension. Basically, you can insert a target impedance-- let's say 45, could be usually 50 ohms. You can specify a tolerance, specify the net, the signal, and click Analyze. And there you go. In a few milliseconds, maybe a few seconds, you get this result. So here, we're showing that all of the impedance in all of these segments on your trace. So this is very powerful and it's extremely fast in Fusion.

Now, if you want to, you can also export that information to NCIS to get more in-depth insight. But let's see how this is going to work. So in Fusion, you can analyze signal and get a plot like this, right? So you can see there are some red-- means there's a difference in impedance on that particular region in the middle of your PCB. That's the top layer.

If we enable the visibility of the bottom layer, the layer right below this, you can see that there's a slot on the ground plane, on the reference plane. And that is changing the impedance. And that's something that we don't want, right? So you can fix that right away in Fusion, or you can send that information to Ansys. So with a click of a button, now you have this Ansys Electronics desktop where you can use one of our tools.

In our particular case, in here, we're going to use HFSS to use full-wave 3D solvers with adaptive mesh refinement to compute everything that you're seeing here. What you're seeing is an animation of electric field, both in magnitude and also the vectors.

So with HFSS, you can get a very full and accurate signal integrity, electromagnetic compatibility, power, integrity, thermal and mechanical simulations in the environment with this workflow. So again, in Fusion, you can identify those regions. You can fix that. In this case, you see here that we identified in Fusion, well, there's a slot, a hole in the ground plane. That's not what I want. So I can fix that.

But if you want to see-- quantify the fields, you can go to Ansys, like what you're seeing here. So the original design with the hole, you can see the near fields. They have a red hotspot. And that's something that we don't want. That hole, that slot, is actually radiating field. So you're going to have likely an EMI problem, as well. The eye diagram is a little bit closed, right?

Now, you fix the hole, right? There's no more hole, no more gap. You can see that there are no more red near field spots, hotspots. And also the eye diagram is much better. So with this technology in Autodesk, the PCB designers can, in a matter of a few seconds, identify issues and fix them, while they're still designing the PCB. If they want to quantify that, they can send it to Ansys, and they can quantify this.

So this is one validation that we have with measurements for this particular case. We have a signal traveling in a trace. And when you have this slot on the ground plane, you can see here the trace is traveling through the trace. You can see now there's a bunch of reflection. We don't want that.

On the top right-hand side, you see measurements and simulation near field. You can see the simulation matches extremely well, the near fields. And then the left side, you see the radiated emissions test at a 1-meter distance. You can see the simulation results in red and the blue simulation-- the blue plot from measurements. You can see there's a very good agreement, especially on the fundamental and harmonics. There's a little bit difference on the noise floor, of course, because of calibration, and noise, and lab environments. But the results there match very well, I would say.

And another thing that we can do for the Signal Integrity extension is to compute crosstalk. Crosstalk is something that we have for all of these printed circuit boards today. Usually when you have one of these components, one of these traces, and they have a signal that we're not interested in to evaluate right now, we have this-- that would be called aggressor, right?

So we have an aggressor where we have a signal propagating through a trace, and you might have some victim traces. So that could couple through electromagnetic fields. You can see here magnetic streamlines, magnetic field streamlines, and also electric field vectors. So, as you can see, if the aggressor and victim, they're close to each other, you're going to have lots of crosstalk. You've separate them, you're going to decrease that crosstalk. We compute this by computing-- by calculating capacitive coupling, inductive. We compute the RLCG on your entire cross-section.

Usually crosstalk is very-- is something that you can identify with an oscilloscope in time domain. So here on the top, you'll see a signal without crosstalk. And on the bottom, the signal with crosstalk. This is a 1 megahertz clock. And you have some crosstalk from some net that is really close by in the PCB.

So let's provide a demo here, one example where we can use the Signal Integrity extension again in Fusion to try to identify crosstalk issues. And you can send that information again to Ansys, if you want to quantify that.

So imagine that you were not using the Signal Integrity extension. You have to design your PCB, manufacture a prototype. And then when you go to the test, technician is going to say, hey, you have a crosstalk problem in this connector. This 1 megahertz clock. I probed the oscilloscope, and there's lots of crosstalk, lots of noise. Can you fix this?

Well, in the Signal Integrity extension, you can, just with the click of a button, plot what you call crosstalk coupling coefficient that will show you all segments that are creating some coupling. So here in this case, we have that 1 megahertz clock net. And you can see in white some of the segments that are coupling to that specific segment of these nets.

In some areas where you have some anti-pads on the vias, it's red because the coupling is much higher when you don't have a reference plane. So the keyer, instead of coming back to the source through the plane, is going actually back through all of these nets because it doesn't have a reference point.

So let's try to, first, do something obvious. Let's start changing the space between those segments. You can see here in this white area, that's something that we might want to change. So if you take a look at how the distance affects the crosstalk, here, we're separating those two traces a little bit. And as you can see, as we place them far apart, you can see that the crosstalk reduces. And that's something that we want to do. We want to reduce crosstalk. But there might be other things that we can look at in here and try to adjust your design instead of just separating traces.

One thing that you can do in Fusion is to filter this coupling. So you can filter areas with high coupling, right? So here, you can just drag that color bar. And you can see that there are two areas of very high coupling in red, right? If you zoom in into one of these areas, you see that they're red. And the reason for that is that they don't have a reference plane beneath them or on the top of them.

So again, the signal is returning through the source, through the path that has less impedance. And that's going to be the other traces. And you want to avoid that. So we can simulate this. You can send that signal. And as you can see, when that signal reaches that area without the reference plane, again, you see that bad things happen. You see lots of reflections. You see the signal going everywhere. And you don't want that, right?

So one thing that you can do on the revision, one, you can add some reference plane in there-- you know, add a via to connect to the ground, connect to all of the rest of your reference plane. And you can see there are two n And that's the reason we can't close the entire gap. But if somehow you can manage to reroute those two nets, and that's how-- added in here, you can actually close that gap. And you see on the revision 2, that small red region, it's gone. So it's a much better layout.

So if you compare the original design, on the top, you see lots of crosstalk. If you compare it to the revision 2, you see that the noise, it's very minor here. It's almost no noise you see in that signal. And that's what you want to do. So again, with the signal integrity extension, you can compute not only impedance RLGCs, but also crosstalk coefficient that can shows the PCB designer if they're going to have some issues and where to fix them. And that's extremely powerful. It doesn't require any PhD or expertise in signal integrity.

And let's see some validation of crosstalk. So again, that same technology that is embedded into Fusion 360 through the Signal Integrity extension is the same technology that we have been using in Ansys for decades now. And most of the companies around the world is using this same technology to mitigate signal integrity, power integrity, and EMC issues in their design.

And we do have validation that it was proposed in one of the IEEE conferences. It's called IEEE Electrical Performance of Electronics Packaging Systems. They provide some benchmarks-- you know, measurements. And then we simulate, and we see how they compare.

And those measurements, it's from a package. It was provided by IBM Watson Research center, right? They have a 50 picoseconds rise time. It's a step function on the aggressor. And we're measuring the near end and the far end crosstalk on the victims. So here is a close up of the nets that they were measuring here on the lab. You can see some of the pictures, and we're simulating.

So the crosstalk simulations, here we have measured on the left side, simulated on the right-hand side. You can see both for near end and far end, they match extremely well. If you overlay those results-- so here's the far end noise measurements. As you can see, there's some noise in the measurements.

And the simulated results, they match extremely well. So that same technology that it was validating in this benchmark, and have been using validated on hundreds, thousands of other cases, It's the same technology, the same physics-based server technology that we have in Fusion with the Signal Integrity extension.

So the main key takeaways in here is that with electronics design, Autodesk Fusion, you have the simulation enabling the PCB designers to take wise decisions, smart decisions. So they can design a better layout, trying to improve their signal integrity, and also increase their chances if they're going to have, EMC compliance test in the future. So this Fusion Signal Integrity extension which, again, uses our Ansys technologies provides-- without any signal, integrity expertise, provide those PCB designers with the tool that can show them where they need to fix their layout in their PCBs in order to improve their designs.

So with that, I'd like to conclude my presentation. Thank you very much for your time. And if you have any questions, please reach out to me any time. I'll be more than happy to answer any of the questions. So thank you very much.

______
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We use Commission Factory to collect data about your behavior on our sites. This may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. We use this data to measure our site performance and evaluate the ease of your online experience, so we can enhance our features. We also use advanced analytics methods to optimize your experience with email, customer support, and sales. Commission Factory Privacy Policy
Google Analytics (Strictly Necessary)
We use Google Analytics (Strictly Necessary) to collect data about your behavior on our sites. This may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, your IP address or device ID, and your Autodesk ID. We use this data to measure our site performance and evaluate the ease of your online experience, so we can enhance our features. We also use advanced analytics methods to optimize your experience with email, customer support, and sales. Google Analytics (Strictly Necessary) Privacy Policy
Typepad Stats
We use Typepad Stats to collect data about your behaviour on our sites. This may include pages you’ve visited. We use this data to measure our site performance and evaluate the ease of your online experience, so we can enhance our platform to provide the most relevant content. This allows us to enhance your overall user experience. Typepad Stats Privacy Policy
Geo Targetly
We use Geo Targetly to direct website visitors to the most appropriate web page and/or serve tailored content based on their location. Geo Targetly uses the IP address of a website visitor to determine the approximate location of the visitor’s device. This helps ensure that the visitor views content in their (most likely) local language.Geo Targetly Privacy Policy
SpeedCurve
We use SpeedCurve to monitor and measure the performance of your website experience by measuring web page load times as well as the responsiveness of subsequent elements such as images, scripts, and text.SpeedCurve Privacy Policy
Qualified
Qualified is the Autodesk Live Chat agent platform. This platform provides services to allow our customers to communicate in real-time with Autodesk support. We may collect unique ID for specific browser sessions during a chat. Qualified Privacy Policy

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Improve your experience – allows us to show you what is relevant to you

Google Optimize
We use Google Optimize to test new features on our sites and customize your experience of these features. To do this, we collect behavioral data while you’re on our sites. This data may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, your IP address or device ID, your Autodesk ID, and others. You may experience a different version of our sites based on feature testing, or view personalized content based on your visitor attributes. Google Optimize Privacy Policy
ClickTale
We use ClickTale to better understand where you may encounter difficulties with our sites. We use session recording to help us see how you interact with our sites, including any elements on our pages. Your Personally Identifiable Information is masked and is not collected. ClickTale Privacy Policy
OneSignal
We use OneSignal to deploy digital advertising on sites supported by OneSignal. Ads are based on both OneSignal data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that OneSignal has collected from you. We use the data that we provide to OneSignal to better customize your digital advertising experience and present you with more relevant ads. OneSignal Privacy Policy
Optimizely
We use Optimizely to test new features on our sites and customize your experience of these features. To do this, we collect behavioral data while you’re on our sites. This data may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, your IP address or device ID, your Autodesk ID, and others. You may experience a different version of our sites based on feature testing, or view personalized content based on your visitor attributes. Optimizely Privacy Policy
Amplitude
We use Amplitude to test new features on our sites and customize your experience of these features. To do this, we collect behavioral data while you’re on our sites. This data may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, your IP address or device ID, your Autodesk ID, and others. You may experience a different version of our sites based on feature testing, or view personalized content based on your visitor attributes. Amplitude Privacy Policy
Snowplow
We use Snowplow to collect data about your behavior on our sites. This may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, your IP address or device ID, and your Autodesk ID. We use this data to measure our site performance and evaluate the ease of your online experience, so we can enhance our features. We also use advanced analytics methods to optimize your experience with email, customer support, and sales. Snowplow Privacy Policy
UserVoice
We use UserVoice to collect data about your behaviour on our sites. This may include pages you’ve visited. We use this data to measure our site performance and evaluate the ease of your online experience, so we can enhance our platform to provide the most relevant content. This allows us to enhance your overall user experience. UserVoice Privacy Policy
Clearbit
Clearbit allows real-time data enrichment to provide a personalized and relevant experience to our customers. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID.Clearbit Privacy Policy
YouTube
YouTube is a video sharing platform which allows users to view and share embedded videos on our websites. YouTube provides viewership metrics on video performance. YouTube Privacy Policy

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Customize your advertising – permits us to offer targeted advertising to you

Adobe Analytics
We use Adobe Analytics to collect data about your behavior on our sites. This may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, your IP address or device ID, and your Autodesk ID. We use this data to measure our site performance and evaluate the ease of your online experience, so we can enhance our features. We also use advanced analytics methods to optimize your experience with email, customer support, and sales. Adobe Analytics Privacy Policy
Google Analytics (Web Analytics)
We use Google Analytics (Web Analytics) to collect data about your behavior on our sites. This may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. We use this data to measure our site performance and evaluate the ease of your online experience, so we can enhance our features. We also use advanced analytics methods to optimize your experience with email, customer support, and sales. Google Analytics (Web Analytics) Privacy Policy
AdWords
We use AdWords to deploy digital advertising on sites supported by AdWords. Ads are based on both AdWords data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that AdWords has collected from you. We use the data that we provide to AdWords to better customize your digital advertising experience and present you with more relevant ads. AdWords Privacy Policy
Marketo
We use Marketo to send you more timely and relevant email content. To do this, we collect data about your online behavior and your interaction with the emails we send. Data collected may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, your IP address or device ID, email open rates, links clicked, and others. We may combine this data with data collected from other sources to offer you improved sales or customer service experiences, as well as more relevant content based on advanced analytics processing. Marketo Privacy Policy
Doubleclick
We use Doubleclick to deploy digital advertising on sites supported by Doubleclick. Ads are based on both Doubleclick data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that Doubleclick has collected from you. We use the data that we provide to Doubleclick to better customize your digital advertising experience and present you with more relevant ads. Doubleclick Privacy Policy
HubSpot
We use HubSpot to send you more timely and relevant email content. To do this, we collect data about your online behavior and your interaction with the emails we send. Data collected may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, your IP address or device ID, email open rates, links clicked, and others. HubSpot Privacy Policy
Twitter
We use Twitter to deploy digital advertising on sites supported by Twitter. Ads are based on both Twitter data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that Twitter has collected from you. We use the data that we provide to Twitter to better customize your digital advertising experience and present you with more relevant ads. Twitter Privacy Policy
Facebook
We use Facebook to deploy digital advertising on sites supported by Facebook. Ads are based on both Facebook data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that Facebook has collected from you. We use the data that we provide to Facebook to better customize your digital advertising experience and present you with more relevant ads. Facebook Privacy Policy
LinkedIn
We use LinkedIn to deploy digital advertising on sites supported by LinkedIn. Ads are based on both LinkedIn data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that LinkedIn has collected from you. We use the data that we provide to LinkedIn to better customize your digital advertising experience and present you with more relevant ads. LinkedIn Privacy Policy
Yahoo! Japan
We use Yahoo! Japan to deploy digital advertising on sites supported by Yahoo! Japan. Ads are based on both Yahoo! Japan data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that Yahoo! Japan has collected from you. We use the data that we provide to Yahoo! Japan to better customize your digital advertising experience and present you with more relevant ads. Yahoo! Japan Privacy Policy
Naver
We use Naver to deploy digital advertising on sites supported by Naver. Ads are based on both Naver data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that Naver has collected from you. We use the data that we provide to Naver to better customize your digital advertising experience and present you with more relevant ads. Naver Privacy Policy
Quantcast
We use Quantcast to deploy digital advertising on sites supported by Quantcast. Ads are based on both Quantcast data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that Quantcast has collected from you. We use the data that we provide to Quantcast to better customize your digital advertising experience and present you with more relevant ads. Quantcast Privacy Policy
Call Tracking
We use Call Tracking to provide customized phone numbers for our campaigns. This gives you faster access to our agents and helps us more accurately evaluate our performance. We may collect data about your behavior on our sites based on the phone number provided. Call Tracking Privacy Policy
Wunderkind
We use Wunderkind to deploy digital advertising on sites supported by Wunderkind. Ads are based on both Wunderkind data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that Wunderkind has collected from you. We use the data that we provide to Wunderkind to better customize your digital advertising experience and present you with more relevant ads. Wunderkind Privacy Policy
ADC Media
We use ADC Media to deploy digital advertising on sites supported by ADC Media. Ads are based on both ADC Media data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that ADC Media has collected from you. We use the data that we provide to ADC Media to better customize your digital advertising experience and present you with more relevant ads. ADC Media Privacy Policy
AgrantSEM
We use AgrantSEM to deploy digital advertising on sites supported by AgrantSEM. Ads are based on both AgrantSEM data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that AgrantSEM has collected from you. We use the data that we provide to AgrantSEM to better customize your digital advertising experience and present you with more relevant ads. AgrantSEM Privacy Policy
Bidtellect
We use Bidtellect to deploy digital advertising on sites supported by Bidtellect. Ads are based on both Bidtellect data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that Bidtellect has collected from you. We use the data that we provide to Bidtellect to better customize your digital advertising experience and present you with more relevant ads. Bidtellect Privacy Policy
Bing
We use Bing to deploy digital advertising on sites supported by Bing. Ads are based on both Bing data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that Bing has collected from you. We use the data that we provide to Bing to better customize your digital advertising experience and present you with more relevant ads. Bing Privacy Policy
G2Crowd
We use G2Crowd to deploy digital advertising on sites supported by G2Crowd. Ads are based on both G2Crowd data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that G2Crowd has collected from you. We use the data that we provide to G2Crowd to better customize your digital advertising experience and present you with more relevant ads. G2Crowd Privacy Policy
NMPI Display
We use NMPI Display to deploy digital advertising on sites supported by NMPI Display. Ads are based on both NMPI Display data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that NMPI Display has collected from you. We use the data that we provide to NMPI Display to better customize your digital advertising experience and present you with more relevant ads. NMPI Display Privacy Policy
VK
We use VK to deploy digital advertising on sites supported by VK. Ads are based on both VK data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that VK has collected from you. We use the data that we provide to VK to better customize your digital advertising experience and present you with more relevant ads. VK Privacy Policy
Adobe Target
We use Adobe Target to test new features on our sites and customize your experience of these features. To do this, we collect behavioral data while you’re on our sites. This data may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, your IP address or device ID, your Autodesk ID, and others. You may experience a different version of our sites based on feature testing, or view personalized content based on your visitor attributes. Adobe Target Privacy Policy
Google Analytics (Advertising)
We use Google Analytics (Advertising) to deploy digital advertising on sites supported by Google Analytics (Advertising). Ads are based on both Google Analytics (Advertising) data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that Google Analytics (Advertising) has collected from you. We use the data that we provide to Google Analytics (Advertising) to better customize your digital advertising experience and present you with more relevant ads. Google Analytics (Advertising) Privacy Policy
Trendkite
We use Trendkite to deploy digital advertising on sites supported by Trendkite. Ads are based on both Trendkite data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that Trendkite has collected from you. We use the data that we provide to Trendkite to better customize your digital advertising experience and present you with more relevant ads. Trendkite Privacy Policy
Hotjar
We use Hotjar to deploy digital advertising on sites supported by Hotjar. Ads are based on both Hotjar data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that Hotjar has collected from you. We use the data that we provide to Hotjar to better customize your digital advertising experience and present you with more relevant ads. Hotjar Privacy Policy
6 Sense
We use 6 Sense to deploy digital advertising on sites supported by 6 Sense. Ads are based on both 6 Sense data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that 6 Sense has collected from you. We use the data that we provide to 6 Sense to better customize your digital advertising experience and present you with more relevant ads. 6 Sense Privacy Policy
Terminus
We use Terminus to deploy digital advertising on sites supported by Terminus. Ads are based on both Terminus data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that Terminus has collected from you. We use the data that we provide to Terminus to better customize your digital advertising experience and present you with more relevant ads. Terminus Privacy Policy
StackAdapt
We use StackAdapt to deploy digital advertising on sites supported by StackAdapt. Ads are based on both StackAdapt data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that StackAdapt has collected from you. We use the data that we provide to StackAdapt to better customize your digital advertising experience and present you with more relevant ads. StackAdapt Privacy Policy
The Trade Desk
We use The Trade Desk to deploy digital advertising on sites supported by The Trade Desk. Ads are based on both The Trade Desk data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that The Trade Desk has collected from you. We use the data that we provide to The Trade Desk to better customize your digital advertising experience and present you with more relevant ads. The Trade Desk Privacy Policy
RollWorks
We use RollWorks to deploy digital advertising on sites supported by RollWorks. Ads are based on both RollWorks data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that RollWorks has collected from you. We use the data that we provide to RollWorks to better customize your digital advertising experience and present you with more relevant ads. RollWorks Privacy Policy

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