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Automotive component lightweight design by advanced material and Moldflow Insight, Helius and Abaqus Co-Simulation

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Description

To archive the lightweight and optimization design for Automotive component, the advance material will be used, so the fiber orientation, the residual stress, weld line location and warpage are very important for the design improve, also the Co-Simulation (Moldflow Insight + Helius PFA + ABAQUS) is used to evaluate the strength and remove the weakness in potential. This will greatly reduce the demand for the high cost of physical prototype testing.

Key Learnings

  • Discover the workflow of the design improvement for the automotive front-end module
  • Learn about an SMC with long-fiber material case study
  • Learn about the co-simulation use for lightweight and optimization design
  • Learn how to use Helius PFA mapping Moldflow results to ABAQUS FEA

Speakers

  • Jian Zhang
    Eric Li is currently the technical specialist of Moldflow software products in Autodesk China. Graduated from Dalian Jiaotong University in 2000, Li has worked as an injection molding process engineer, a plastic product structure design engineer, a plastic mold design engineer, and a project manager. He has a wealth of practical experience in injection molding and plastic mold industry.
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Transcript

JIAN ZHANG: Hey. Hello, everyone. I'm Jian Zhang from Guangzhou Automotive. Thanks, Jimmy.

Next, I will use Chinese to begin my speech.

[NON-ENGLISH SPEECH]

PRESENTER: First, he would like to [INAUDIBLE] and the Guangzhou Automotive Corporation, located in South China and-- sorry--

JIAN ZHANG: That's OK. South China--

PRESENTER: [INAUDIBLE]

JIAN ZHANG: OK.

PRESENTER: [INAUDIBLE]

JIAN ZHANG: OK.

PRESENTER: Sorry about this, folks.

JIAN ZHANG: OK.

PRESENTER: GAC Engineering is located in Guangzhou, which is South China. And they are mainly responsible for their local-owned brand called the Trumpchi.

JIAN ZHANG: [NON-ENGLISH SPEECH]

PRESENTER: The company was established around 10 years ago. And you can see the second car model, GS4, which is one of our most popular sold car in China market.

JIAN ZHANG: [NON-ENGLISH SPEECH]

PRESENTER: Thanks to the contribution of the team during the last 10 years, they established quite a strong engineering team. There will be five engineers in the team. In Jian Zhang's team, there are two professional [INAUDIBLE] engineers and three guys, one of the [INAUDIBLE] engineer, and the other, someone who is very familiar with structural designs.

JIAN ZHANG: [NON-ENGLISH SPEECH]

PRESENTER: The reason we want to use co-simulation because in the actual, physical world, there would be [INAUDIBLE] assembling single physicals there. There will be multi-physics there. So for example, for this kind of multi-physics co-simulation, we have to consider some kind of processing defect from the other side, like processing from the injection molding and putting those kind of defects into the next step of structure stimulation.

JIAN ZHANG: [NON-ENGLISH SPEECH]

PRESENTER: So today, our topic will be focus on the mold flow and structure simulations.

JIAN ZHANG: [NON-ENGLISH SPEECH]

PRESENTER: Here, remember, that's around five years ago. There's also tools called, I think, Moldflow Structural Alliance. They can use those kind of command-- can go back to [INAUDIBLE]

JIAN ZHANG: OK.

PRESENTER: --those two commands up there [INAUDIBLE] to export those kind of processing like a [INAUDIBLE] or other influence to the next step of structure simulation.

JIAN ZHANG: Yes. [NON-ENGLISH SPEECH]

PRESENTER: With a new release tool of the Helius by Autodesk in last year, now we can have the new process flow. You can see that we can import and export the injection molding without and go into the next step of Helius and go the next step of the structure simulations, which is a much more convenient and easier than the previous tools.

JIAN ZHANG: [NON-ENGLISH SPEECH]

PRESENTER: With the lightweight concept, we'll be going deeper into the automotive [INAUDIBLE] industry. And those kind of fiber reinforced [INAUDIBLE] material will be more and more used in automotive industry. With those kind of very unisotropic material, those kind of influences should be considered into the next structure simulation.

JIAN ZHANG: [NON-ENGLISH SPEECH]

PRESENTER: First, I'll show you some of the fiber influence for the material property. You can see along the flow direction, which is fiber reinforced the most strongly direction. And there's kind of a very good strong and tough material.

But going to another perpendicular direction, there would be very soft but flexible directions and vice versa in the center. This will be something between along 45 directions. Sometimes [INAUDIBLE] flow direction and perpendicular direction. The difference could be 1 times and more.

JIAN ZHANG: [NON-ENGLISH SPEECH]

PRESENTER: Due to this kind of very strong, unisotropic behavior, we should consider those kind of fiber reinforced material properties very clearly into the next step of structure stimulation.

JIAN ZHANG: [NON-ENGLISH SPEECH]

PRESENTER: So, I'd first like to share the one demonstrate case. That will be a very simple part. One case is we're using single gate. Another one is using the two gates flow two directions. The difference, you can see the second case there would be a very strong weld line, which can cause the very strong turbulence of the fiber orientations.

JIAN ZHANG: [NON-ENGLISH SPEECH]

PRESENTER: There will be [INAUDIBLE] the case where load is something like this, like a hook structure. And they will be fixed in the top and the load will be loaded at the lower hook positions. And it will be tested with three cases. The first one will be without more flow, very isotropic material. Second case will be single gate direction without any weld line. So third case, there would be two gates with weld line factor inside.

JIAN ZHANG: [NON-ENGLISH SPEECH]

PRESENTER: For the case one, the next [INAUDIBLE] will he happening the centered position very uniformly, the second case. And there would be also uniformly but it's very much smaller than the first case. In the third one, they will be very concentrated in the weld line position. The value also is the most biggest one in those three cases.

JIAN ZHANG: [NON-ENGLISH SPEECH]

PRESENTER: Due to the single gate, you can see the fiber orientation around the first case very uniformly along one direction. So that can further reinforce the whole structures. That's the reason you show the [INAUDIBLE] smaller here.

JIAN ZHANG: [NON-ENGLISH SPEECH]

PRESENTER: So, we'll first show the demo case, which is not realistic. But later on, we will share some cases which is used already in the engineering field.

JIAN ZHANG: [NON-ENGLISH SPEECH]

PRESENTER: So this is the part called the tray battery. Tray, this is for battery, support the whole structure on the hold inside of the car. And in the actual test, we found a failure. Like, you can see the highlight position here.

JIAN ZHANG: [NON-ENGLISH SPEECH]

PRESENTER: Due to the failure in the test, we do some several kind of simulation to find the root cause. You can see there's tests with four cases, which is the load condition inside of the vehicle. Watch it bounce down, bounce up, turning direction, and the brake. And after the calculation, they found the maximum stress will be happening in the bounce up load cases.

JIAN ZHANG: [NON-ENGLISH SPEECH]

PRESENTER: After the very traditional [INAUDIBLE] simulation, which is isotropic, they found that the maximum stress around 62.4 megapascal, which is much lower than the fracture, around 78 around, which it should not be failed. This is a traditional series [INAUDIBLE] tell us the result.

JIAN ZHANG: [NON-ENGLISH SPEECH]

PRESENTER: You can see this dimension and structure of the whole part, and which is-- also, [INAUDIBLE] injector is one hot gate. The material will be polypropylene with 40% long glass fiber reinforced material.

JIAN ZHANG: [NON-ENGLISH SPEECH]

PRESENTER: This is 40% long glass fiber enforced material. They will be very strong unisotropic property inside. So that's the reason they want to consider those kind of fiber effect, reinforced effect, into next co-simulation steps.

JIAN ZHANG: [NON-ENGLISH SPEECH]

PRESENTER: Due to the [INAUDIBLE] concern of the isotropic, they put the moldflow-- result and also they tested the material with three directions and combined the three directions into one material fiber and map into the [INAUDIBLE] important for simulation, [INAUDIBLE] the cases, and testing the vehicle conditions.

JIAN ZHANG: [NON-ENGLISH SPEECH]

PRESENTER: OK, I think for this process flow, I think the moldflow simulation is easy and mapping is also easy because software, they can help you to do it. It's quite easy. Most of the difficult here will be to measure the material along the three directions-- like, perpendicular, along fiber, and also 45 degree. So in most of cases, they get the material property from material supplier and fit it into the final MET [INAUDIBLE] file.

JIAN ZHANG: [NON-ENGLISH SPEECH]

PRESENTER: I think the mature probably would have been mostly influenced the final result of the accuracy. And those kind of tests-- during the test of the specimen, they found the specimen size, direction, and what kind of method you produce the specimen will strongly influence the final result, which is also very, very important for the simulation you get the right material property

JIAN ZHANG: [NON-ENGLISH SPEECH]

PRESENTER: And they also visited to the moldflow lab in [INAUDIBLE] in the east of the US, United States. And this kind of a visit gave us very strong confidence about the material property measurement. And also with [INAUDIBLE] help, we know that in further development of the moldflow, they will measure more and more and more and more accuracy of the high quality material.

JIAN ZHANG: [NON-ENGLISH SPEECH]

PRESENTER: He will not describe too much about detail, how they measure it. But in [INAUDIBLE], this will be very difficult. Then also, you should get much more support from moldflow side.

JIAN ZHANG: [NON-ENGLISH SPEECH]

PRESENTER: Afterwards, the mapping of the fiber orientation, they found the maximum stress increased to 90 around megapascal, which has already exceeded the fracture stress.

JIAN ZHANG: [NON-ENGLISH SPEECH]

PRESENTER: Now it's already in line with the actual test results.

JIAN ZHANG: [NON-ENGLISH SPEECH]

PRESENTER: In the traditional [INAUDIBLE], which is isotropic, you cannot notice these kind of problems. So that's what we found on the fiber orientation. It really has a big influence on the final structure result.

JIAN ZHANG: [NON-ENGLISH SPEECH]

PRESENTER: They also found the root cause of the orientation caused the failure and because the gate [INAUDIBLE] location has the same line with these corners, which is the shortest wave of the flow past, flow front. When the flow front flows into this area, there will be bifurcated flow, which has caused the fiber orientation not to very strongly align. And this is, of course, the stress concentration reason here.

JIAN ZHANG: [NON-ENGLISH SPEECH]

PRESENTER: So we'll go back to show the [INAUDIBLE] vehicle condition load cases. The battery tray is on the side of the battery on the bottom. And there, we want a strong bracket. And the link was two steel beams. And those kind of vibrations would cause the structure-- this kind of stress concentration there.

JIAN ZHANG: [NON-ENGLISH SPEECH]

PRESENTER: The corner brace is already-- a structure point of view, this is a weak point. And also from fiber orientation, this is also not a weak point. Those two weak points happen together because of failures.

JIAN ZHANG: [NON-ENGLISH SPEECH]

PRESENTER: After finding the root cause, you have to find a solution. There can be two parallel ways. One is to find the structure weak point there. We can modify the design to reduce the stress concentration.

But according to the-- normally after the production, it will be very difficult to change design. There would be a long process and you need to do a lot of tests to do it. Normally, it's not allowed for the timing consumer conditions.

JIAN ZHANG: [NON-ENGLISH SPEECH]

PRESENTER: Alternative solution would be to change fiber orientation along the direction we need. So we wanted the fiber orientation along these kind of directions. So we need to change the molding tools and change the gate location to along the fiber [INAUDIBLE] direction we need.

JIAN ZHANG: [NON-ENGLISH SPEECH]

PRESENTER: So we offsetted the gate location from center to a little bit side to change orientations.

JIAN ZHANG: [NON-ENGLISH SPEECH]

PRESENTER: And the flow pattern changed. And also, the orientation changed here.

JIAN ZHANG: [NON-ENGLISH SPEECH]

PRESENTER: After they changed the location and do the co-simulation again, they find the stress reduced to the value which is lower than the fracture stress.

JIAN ZHANG: [NON-ENGLISH SPEECH]

PRESENTER: After the physical change of [INAUDIBLE] and the retest again, the failure never did happen again.

JIAN ZHANG: [NON-ENGLISH SPEECH]

PRESENTER: The case is to show you [INAUDIBLE] previously, there will be a case which is not that good because they found the problem. And they used co-simulation to change it, which of course [INAUDIBLE] cost and time consuming. But actually, the simulation, the value of submission, would be predicted failure. And we solved the problem in the very early stage. Then, the next case we'll show you, the case something like early-- solve the problem in the early stage.

JIAN ZHANG: [NON-ENGLISH SPEECH]

PRESENTER: The second case will show what the front end model [INAUDIBLE] on the front end module would be on the [INAUDIBLE] of the part, [INAUDIBLE] the whole cooling package, including the radiator, fan assemblies, and also they will take the load from the locker and headlight.

JIAN ZHANG: [NON-ENGLISH SPEECH]

PRESENTER: Module-based design concept is more and more [INAUDIBLE] into the automotive industry in there because they can deliver the package from the tier one to the OEM. That will be easier for assembly. And those kinds of front end modules were made by plastic material. This actually is very crucial to the strength and the stiffness requirement. But with the design freedom of the plastic material, they can make those kind of module-based design.

JIAN ZHANG: [NON-ENGLISH SPEECH]

PRESENTER: The dimension of the front end of the module is quite big. It's one meter long. They were 600 meters high.

JIAN ZHANG: [NON-ENGLISH SPEECH]

PRESENTER: We're using the six hot gate injection and the material will be polypropylene plus 3% long glass fiber reinforced.

JIAN ZHANG: [NON-ENGLISH SPEECH]

PRESENTER: Because we wanted one of the criteria inside would be stiffness along the [INAUDIBLE] direction, because the whole-- they have the locker stiffness direction requirement. After simulation, they found the stiffness-- they simulated around 600 around meters, Newtons per millimeter, which is already over this target of around 500. Because of the [INAUDIBLE] design concept in the automotive industry, they don't want to [INAUDIBLE] have a high stiffness and they're over-designed. They want to reduce the stiffness by kind of changing design.

JIAN ZHANG: [NON-ENGLISH SPEECH]

PRESENTER: In a normal simulation, and we compared with a test, the normal isotopic way predicted stiffness normally is lower than the actual test result.

JIAN ZHANG: [NON-ENGLISH SPEECH]

PRESENTER: So, they want to use co-simulation to [INAUDIBLE] not something roughly, but something accurately, which is the right stiffness for the part which it actually would be.

JIAN ZHANG: [NON-ENGLISH SPEECH]

PRESENTER: The process will be exactly the same as the previous case. But first of all, we're using moldflow to get the fiber orientations.

JIAN ZHANG: [NON-ENGLISH SPEECH]

PRESENTER: Besides the Helius, there also are other tools available in the market to do the co-simulations. So they want to compare and do the benchmark test to see that difference would be [INAUDIBLE] software.

JIAN ZHANG: [NON-ENGLISH SPEECH]

PRESENTER: Then after they get the fit in those kinds of software, they found there would be some difference between the actual curve and the test curve.

JIAN ZHANG: [NON-ENGLISH SPEECH]

PRESENTER: Which is, if you're using the-- normally, the software, they cannot take the curve input. They have to fit into the material parameters and regenerated curve. So [INAUDIBLE] would be some difference here you can also see the picture there would be some difference there

JIAN ZHANG: [NON-ENGLISH SPEECH]

PRESENTER: With the isotropic material, they found a stiffness of 600 around. But if you're going to another isotropic software, they [INAUDIBLE] the simulation with [INAUDIBLE] 560 around Newtons per millimeters. The target is 500 here.

JIAN ZHANG: [NON-ENGLISH SPEECH]

PRESENTER: With this kind of method, they should find the simulation results actually will be lower, much lower than the isometric. With this small gap, they don't have strong confidence to reduce the thickness to make some further light [INAUDIBLE] design.

JIAN ZHANG: [NON-ENGLISH SPEECH]

PRESENTER: And with Helius, we also do with those kind of material fitting inside of the interface of the software because [INAUDIBLE] fitting and actual curve there.

JIAN ZHANG: [NON-ENGLISH SPEECH]

PRESENTER: They find the software is really smart and easy to use. They use the fitting of the material and everything [INAUDIBLE] handled by the software itself.

JIAN ZHANG: [NON-ENGLISH SPEECH]

PRESENTER: The other software, you will need a lot of manual input to modify some factors, parameters, to fit the material curve, which is not convenient for them.

JIAN ZHANG: [NON-ENGLISH SPEECH]

PRESENTER: In Helius, you just need to put everything [INAUDIBLE] from a [INAUDIBLE] input, whereas the stress-strain curve and the angle, degree inside, there will be everything handed by it.

JIAN ZHANG: [NON-ENGLISH SPEECH]

PRESENTER: They will show you three different results. One's isotropic and also isotropic by other software and also isotopic from Helius.

JIAN ZHANG: [NON-ENGLISH SPEECH]

PRESENTER: Using the Helius, they found the result is even smaller, which is very close to the target.

JIAN ZHANG: [NON-ENGLISH SPEECH]

JIAN ZHANG: The final decision is not to change the design or it's a light weight-- a more aggressive light weight design because they found due to the variation of the actual product-- so they found this kind of small gap. It's only enough to ensure this kind of variation. So they don't want to make it more aggressive.

JIAN ZHANG: [NON-ENGLISH SPEECH]

PRESENTER: So, they like to produce it and make it [INAUDIBLE] and test it in the [INAUDIBLE] to find the real difference.

JIAN ZHANG: [NON-ENGLISH SPEECH]

PRESENTER: They found experimental result [INAUDIBLE] 540. So we can [INAUDIBLE] the result and the comparison here.

JIAN ZHANG: [NON-ENGLISH SPEECH]

PRESENTER: With the help of the unisotropic software, they found the results will basically will be very close, much closer than the isotropic result. And the difference will be within 5%.

JIAN ZHANG: [NON-ENGLISH SPEECH]

PRESENTER: So, due to kind of effect [INAUDIBLE] here, so we have to say that the influence of the fiber reinforced [INAUDIBLE] shouldn't be considered into simulation. So co-simulation wouldn't be the solution for it.

JIAN ZHANG: [NON-ENGLISH SPEECH]

PRESENTER: Today, what we show here is only the fiber orientation influenced to the final structure result. But in the future, with [INAUDIBLE], there will be much more influence into like a temperature or whatever you want in putting the next step of the co-simulation stage.

JIAN ZHANG: [NON-ENGLISH SPEECH]

PRESENTER: The influence will be the assembly deformation and also the residual stress from the moldflow simulation. And also there's the weld line fact.

JIAN ZHANG: [NON-ENGLISH SPEECH]

PRESENTER: I think some of you maybe already lessened the cost yesterday. They already introduced about the Helius, a new feature for the weld line fact calculation.

JIAN ZHANG: [NON-ENGLISH SPEECH]

PRESENTER: But here, we would like to appreciate the effort from Autodesk here, and get the voice from customers.

JIAN ZHANG: [NON-ENGLISH SPEECH]

PRESENTER: In the future, there is low pressure injection and those kind of RTM copper fiber reinforced over fiber material would be next step of the co-simulation.

JIAN ZHANG: [NON-ENGLISH SPEECH]

PRESENTER: So we'd like to keep working and it will improve continuously for those kind of simulations with a lot of [INAUDIBLE]. And also, we would like to get more support from Autodesk to make it better.

JIAN ZHANG: [NON-ENGLISH SPEECH]

PRESENTER: Thank you.

JIAN ZHANG: [INAUDIBLE]

PRESENTER: Anyone have a question?

AUDIENCE: [INAUDIBLE]

PRESENTER: Simulation [INAUDIBLE].

AUDIENCE: Dynamic to full, [INAUDIBLE]

PRESENTER: This one?

AUDIENCE: Oh yes. Who [INAUDIBLE]

JIAN ZHANG: [INAUDIBLE]

AUDIENCE: In my eyes, [INAUDIBLE] very, very, very [INAUDIBLE]

JIAN ZHANG: [NON-ENGLISH SPEECH]

PRESENTER: The first, I think I would like to say the design of the runner here is not based on the flow balance. I think flow balance is one reason we consider including this case. But another, much more important reason, would be the weld line positions.

AUDIENCE: [INAUDIBLE]

JIAN ZHANG: [NON-ENGLISH SPEECH]

AUDIENCE: [INAUDIBLE] [INAUDIBLE] second can be [INAUDIBLE]

AUDIENCE:

JIAN ZHANG: [NON-ENGLISH SPEECH]

AUDIENCE: Oh, no, no. [INAUDIBLE] complexities [INAUDIBLE] So, usually this kind of [INAUDIBLE] speed of [INAUDIBLE] the situation. [INAUDIBLE]

JIAN ZHANG: Take a [INAUDIBLE] maybe it's not the final speed. This is a-- you got [INAUDIBLE]

PRESENTER: [INAUDIBLE] I would like to say, 2.53 seconds, they can feel the [INAUDIBLE]. They really need a big [INAUDIBLE] and a big injection machine. This is the actual case I would like to see.

For normally, the injector would be three to four seconds. It's possible. And you should have inject it faster. Otherwise, there will be cold material inside. So this is the philosophy inside. We made it before.

AUDIENCE: Today, [INAUDIBLE] a view of the factory. [INAUDIBLE]

PRESENTER: I think that even bigger part, even bigger than this.

AUDIENCE: Yes, I know. I know. I have a [INAUDIBLE] that the more that [INAUDIBLE] size of the [INAUDIBLE]

PRESENTER: Yeah.

AUDIENCE: So, usually that [INAUDIBLE] is ignition time. And [INAUDIBLE] said that [INAUDIBLE] ventilation is a [INAUDIBLE] problem cannot make a [INAUDIBLE] gas for every air inside a [INAUDIBLE]. So, using as a [INAUDIBLE] low speed [INAUDIBLE] five second [INAUDIBLE]

PRESENTER: [INAUDIBLE] is having that--

AUDIENCE: [INAUDIBLE]

JIAN ZHANG: [INAUDIBLE]

PRESENTER: Hm?

JIAN ZHANG: [INAUDIBLE]

PRESENTER: He said the actual cases for this one is four seconds-- four seconds.

AUDIENCE: Yeah, why [INAUDIBLE] using four seconds [INAUDIBLE]

PRESENTER: I would like to say that for [INAUDIBLE] co-simulation-wise, there will be some [INAUDIBLE] that's fiber orientation will be most important reasons. But it doesn't matter using this speed. They will change them a little bit but will not strongly influence the fiber orientations. It's not-- very [INAUDIBLE]

AUDIENCE: Look I have a [INAUDIBLE] the speed [INAUDIBLE] flow [INAUDIBLE] is a different flow.

PRESENTER: Yes.

AUDIENCE: Flow [INAUDIBLE] is a very big change of the [INAUDIBLE] Understood?

PRESENTER: I understood.

JIAN ZHANG: Yes.

AUDIENCE: So I ask you your [INAUDIBLE] using a [INAUDIBLE] the time to [INAUDIBLE] at that time [INAUDIBLE]

PRESENTER: Basically, I would like to say concern is right, and using the correct time and from the tubing and get the right temperature of [INAUDIBLE]. But in this case, they do everything in the early stage before the [INAUDIBLE] building.

AUDIENCE: Yeah, OK. Just verification [INAUDIBLE]

PRESENTER: It definitely can be changed the parameter and reflect what actually the condition, what it would be. But in the early stage-- and also the first case for them. So it would be a little bit difficult to consider, like, not everyone experienced as you to design those kind of features like extra flow [INAUDIBLE] site.

This is how I would like to see. Thank you. Any other questions?

PRESENTER: [INAUDIBLE] first, I want to thank our guests. They came from very far to do this presentation, so I want to thank them for coming all the way here. So thank you very much.

PRESENTER: Thank you.

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We use Tealium 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. Tealium Privacy Policy
Upsellit
We use Upsellit 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. Upsellit Privacy Policy
CJ Affiliates
We use CJ Affiliates 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. CJ Affiliates Privacy Policy
Commission Factory
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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