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How Fusion Team Can improve Factory Design Utilities Workflows

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Description

As part of the Product Design & Manufacturing Collection, Factory Design Utilities can help plan and manage production facilities consisting of a wide variety of components in an efficient model or layout. Cooperation between suppliers and customers is often crucial. Therefore, with Fusion Team, stakeholders can set up a Factory Design project, manage library assets, and trace their creation process from different AnyCAD sources. All data is versioned, can be compared in terms of changes, and can be easily and quickly communicated with the team, even if they are not CAD or data management specialists. The ability to collaborate with the data on a web-based cloud service increases the availability and traceability of the data, as well as the ability to solve problems faster and with the appropriate decision makers.

Key Learnings

  • Learn how to set up an Inventor factory project on Fusion Team, how to manage your library, and how to include third-party CAD data.
  • Learn about the capabilities for viewing, communicating, and comparing AutoCAD, Inventor, Navisworks, and third-party data.
  • Learn about the limitations you need to be aware of.
  • Learn about how to share Inventor Factory models with Vault and Autodesk Construction Cloud and the resulting opportunities.

Speaker

  • Robert Ostermann
    Robert Ostermann has been a Factory Designer at MAGNA since 2001. He has presented at multiple Autodesk University events, sharing his expertise in Factory Design. Over the past twenty years, he has extensively utilized the AEC and PDM Collection in his work. Additionally, at MAGNA Steyr Fahrzeugtechnik GmbH & Co KG, Robert is responsible for developing methods for "Digital Factory" planning.
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Transcript

ROBERT OSTERMANN: Hello and welcome to a AU 2023. It is a pleasure to have you here in this presentation. Now, my name is Robert Ostermann and am a factory designer at Magna Steyr Fahrzeugtechnik Graz, Austria.

Before we get started, I would like to mention that this is the first time I show a safe harbor statement in any of my presentations. Usually, I wouldn't do so, if I'm convinced software or certain workflows are running stably or without the risk of something going wrong, which can cause time-consuming issues. But we are absolutely in the early stages of combining factory design utilities, the desktop connector, and Fusion team in a workflow, which is why I would call this presentation the tech preview.

And even if the workflows could already improve your business, I must warn you that you should be careful in using them. Now, this presentation here is meant to help you get the best out of Fusion team as a cloud service. So we will start with an introduction to explain why Fusion team will be important as a cloud service.

Then, I would like to show you in detail how we can use the beneficial functions and what we need to be aware of. And finally, I would like to give you a short insight into what else we can do in cross-product workflows with other Autodesk and third party cloud services in terms of factory planning. Now, let's get started with the introduction.

So some of the questions I asked myself before trying to use Fusion team for factory design utilities were, do we already have the license? Yes, because factory design utilities can only be purchased as a PDM collection. And in addition, this gives you access to Fusion team.

Another question was, is it comparable to a kind of Vault data management light, which can be deployed more easily to contractors? Yes, that's true as well. And because of this, it is only necessary to install the Autodesk desktop connector.

Another question, what does the collaboration on the web service look like? So that if you follow certain rules on how to share data with Fusion team, you will get an easy-to-use and straightforward web interface, which can be used easily by everyone in the team whether CAD specialist or not.

And the last question, what is the point of it all? Now, it's the cooperation, the collaboration between you as a client and your contractors or vice versa. And to be even clearer about the advantages, the entire data of the factory planning project can be exchanged more easily, and communicated with the entire team, and accessed easily by the team to make the right decisions at the right time.

So if we talk about cloud services at Magna, we basically mean an entire process starting with planning and designing production facilities, designing the process and doing simulation, which is the part of Autodesk software, but it is also about changing and adapting building and infrastructure. And finally, it is important to understand how to integrate it all into the existing factory environment and make the right and best decisions.

Now, if you are interested in the entire process, you might also want to watch my presentation from last year's AU, in which I discuss the future of integrated factory planning, which is precisely the title of the presentation. Or you can also search for it using my name. Now, this presentation here focuses on how to use Fusion team for machinery and equipment design by using the factory design utilities and implementing third party data.

So let's continue with the major part of this presentation, how to use Fusion team to share and communicate factory planning data. Let's start with an overview of what I will show you in the next few minutes.

Besides a brief introduction about basics and capabilities, I will focus on the setup of Fusion team and what's currently best practice in combining Fusion team and the factory design utilities. And finally, I will recap the limitations I will already discuss during the presentation and what you need to be aware of.

So basically, this presentation deals with topics that you cannot read about on the Autodesk help page or any other resource. But there are some recommendations from past years which are worth watching. You can see them here on the slide and there is a clickable link directing you to the appropriate class on the AU page.

So before we go into detail concerning the setup, I would like to give you an overview about Fusion team capabilities which are important in the factory planning process. A major benefit compared to Autodesk Docs is that you can not only see the versions of a file, but also the versions of file references being used, such as this AutoCAD layout here, where a sub-reference is currently referenced as version 4 out of 6.

Now, these file dependencies can be seen for AutoCAD, Inventor, third party data references, and this is also a huge advantage compared to Autodesk Docs. The markup and common capabilities are very straightforward and useful. They are also connected to the version of the file on Fusion team. And team members can be mentioned in the comments using a [INAUDIBLE] suffix, which did here in this example.

Also, what is important to know is that Inventor data is easy to compare on Fusion team. Third party data or overall models done with Navisworks always share all data from older versions as removed, and all data from newer versions as added, which makes it difficult to really understand what's been changed. However, these functionalities are delivered within a web browser without the need to install any software for team members who want to be able to view and communicate the data.

You should also know that creating your factory planning project directly on the shared Fusion team drive is not a good idea at the moment, and not just because doing so creates some issues. The biggest problem is the current desktop connector versions aren't performant enough to work on a shared cloud drive, especially creating asset versions or referencing third party data takes too much time.

So the best way of proceeding is to do your planning project locally, with Vault as usual, and share your plannings using Fusion team so that team members can analyze and communicate the data, and the right decisions can be made faster and with traceable data.

And this is precisely what this slide says. Collect the data on premise. Analyze it and make traceable decisions on the cloud service, which takes us also to the next slide and headline. Work local and share global.

Now, to better understand the setup of a factory design project on Fusion team, let's have a closer look at the data factory model, or layout, as seen here in this example of a production line. So on the top right, you can see factory assets, the part of a factory model or layout consists of, which are generated by selecting a sketch and using so-called chained library parts.

In the middle, there's an example of a fully-detailed CATIA assembly, which is referenced, simplified, and converted into a unique factory lab report, always having a 2D and 3D representation. On the bottom right, you see a parametric library part, which will be controlled by various parameters defined by the user before or after placing in a factory model or layout. And all this data, including the original detailed designs, are then transferred to Fusion team.

So the model on the previous slide is shown here as a schematic diagram. It starts on the left side with the main bottle, the production line, and its sub-models, for example, the safety equipment such as the fences and doors. And it ends with the different types of assets created from library parts.

You can also see the indirect connection to detailed design data, which is used for unique assets. And on the right side, there is also a description of what assets are made of, or what they might include. But what's important are the numbers within the green circles. And they describe the different projects, which are set up on a Fusion team hub for a factory planning project.

Now, the intention behind these separate projects are marked here with number 1, a parametric library, which usually contains standard assets that will be used in different projects, so a separate project definition in Fusion team is obvious. Marked with number 2 is a separate project for detailed design data and may not be as obvious, but due to the fact that access permissions currently can only be set for projects, and not for folders or roles, and so this can also make sense within your project environment.

And marked here with number 3 and 4, this is basically the main project, which contains all the factory models and layouts, but also the unique library parts which are specific to a certain project. For this presentation, you will see, several times, the previously discussed projects on my proof of concept Autodesk Fusion team hub, as named here on the bottom of this slide.

And if you take a closer look at the folder structure behind this project, you will see, once again, as the numbers and the additional description on the right side explains, that access permissions can currently only be assigned to project and not to different folders. So when a project definition is set up for Inventor factory, these three projects on Fusion team can be included as the project location, and the project library, marked here on this slide with number 3 and 4, as a work group search path, marked with number 2, and as a standard library, as seen here on the right side of the slide and marked with number 1.

So some of you may ask, why do we need an Inventor factory project definition on Fusion team if the data is only exchanged or transferred to Fusion team? Now, there are a few reasons for this. Usually, using the local project definition will lead to very long, related data folders for almost all factory models and referenced third party data on Fusion team.

The Inventor project on Fusion team will help you to work around this problem. And also, transferred Inventor models may not have a visualization unless they were opened and saved directly on the Fusion team drive. And these visualizations, they are necessary for data comparison workflows, what I will show you later in this presentation.

As you may have also seen on the previous slide, there are Inventor factory project definitions for different users. The reason is that path definitions which are in sub-folders of the project location will not be replaced by the current windows user folder. This means that past definitions for work group search paths and libraries outside the project location must be manually replaced by the appropriate windows user folder and saved as a separate project definition. And here on this slide is an example showing this in detail.

So before I talk about transferring the data between the local and the cloud project, I would like to discuss the use of AutoCAD, Inventor and Navisworks in a factory planning project, starting on the right side of the slide. So, with an Inventor, several third party file formats can be referenced, which doesn't mean converted, then they can be simplified and converted to a so-called factory asset.

Assets can be Inventor parts and assemblies, will have a 2D AutoCAD representation, and may have some other asset relevant files. A factory layout and model is usually a set of an AutoCAD DWG, an Inventor IAM, and a layout data file. Now, due to geometrical complexity main models or layouts can have, at Magna we create Navisworks projects usually from NWC, Navisworks cache files, and standard AutoCAD layouts from synchronized factory DWG layouts.

Additionally, we save Navisworks projects as NWD Navisworks document files and import them to Fusion team, because these files can be visualized and communicated. An example can be seen here on this slide. On the left, we have a standard AutoCAD assembly to make sure no factory layout data synchronization takes place. And on the right, we have a Navisworks project or document containing NWCs from different sub-models.

So let's have a look at the best practice for transferring Inventor data with third party file references. Now basically, to work efficiently on Fusion team, your file structure should be identical to that of the local project and you should install the desktop connector for transferring your local data to the Fusion team cloud drive. Then, start by copying all files and folders that contain any third party data or references used in the main model.

And after our reference data has been synchronized, copy the Inventor main model and simplifications to the appropriate folder on Fusion team and use the previously defined Fusion team project, and not-- and this is important-- not the local project when prompted by the desktop connector. Now, what happens when we use the project definition of the local project to transfer the models?

The desktop connector will correctly analyze all file references of the main model in the local project, which can also be checked by the desktop connector reference explorer. But when we transfer the data to the Fusion team project, the desktop connector will create a related data structure for the folders marked here with the numbers 2, 3, and 4. And this is what happens with file references that are in parallel or parent folder structures.

Now, before moving on to the next slide, I would like to point out that it's not possible to share Magna data with you, but I have created user-friendly practice files and uploaded them to the AU site, so that you can follow specific videos here and test the workflows described in this presentation.

Now, as mentioned earlier, this example contains data that you can download from the AU site. It is an Inventor file with CATIA references in parallel folders, and contains a simplified model state. You can use the desktop connector reference explorer to analyze the data structure. And further, this example data allows you to test what happens if the local Inventor project definition is used to transfer the data to Fusion team, and for which data a related data structure is created.

And this can be compared with what happens if you follow the best practice described earlier, and first copy all the references, which are the files in the main and sub-component folders labeled here with the number 3, 4, and 5 on this slide, and then transfer the main model labeled with the number 1, using the Inventor project definition on Fusion team to transfer the local data.

So as mentioned earlier, this example contains data that you can download from the AU site. In this case, it is an Inventor model that contains CATIA references. And important is that all the files are in child folders and labeled here with the numbers 3, 4, and 5. And the data also contains a simplified model state, labeled here with the number 2.

With this sample data, you can test what happens if the local Inventor project definition is used to transfer the main model labeled with the number 1 to Fusion team. You can also use the desktop connector reference explorer to analyze the data structure after all data has been transferred to Fusion team.

So now let's have a look at the best practice for transferring Inventor data with factory assets. First, copy all the asset files and folders from the local project to the appropriate folder on Fusion team. You can also search and sort by modification date and copy the missing assets only.

After all asset data has been synchronized, copy the AutoCAD factory layout and the layout data file to the appropriate folder on Fusion team. And finally, copy the Inventor factory model and use the Fusion team project defined earlier, and not the local project, when prompted by the desktop connector.

So actually, the problem is the same as before because generated factory assets are never in child folders. Also, when using the Fusion team project, the factory model, the IAM file, and the layout, the DWG file, may not be copied at the same time. This video shows the workflow described on the previous slide, using the test data provided on the AU side.

First, all generated asset data labeled with the numbers 4 and 5 is copied to the Fusion team drive using the Inventor project definition on Fusion team. Then the DWG file and the layout data files are copied and labeled here with number 2. And finally, the main model, the factory model is transferred.

But once again, there is a related data folder structure here. And the reason for this is that the transferred DWG file has a reference in a parallel folder, which is marked here on the slide with the number 3. Now, what you can do to better understand the trends for data is use the desktop connector file explorer every time before you transfer data to Fusion team.

Now, with DWG references in the parent-- in the parent or parallel folder, there is no workaround using an Inventor project definition on Fusion team. The only solution for AutoCAD DWGs is to ensure that there is a master file that contains all file references in child folders or that there are no references in parallel or parent folders before the data is transferred to Fusion team.

Finally, let's have a look at the best practice for transferring factory asset libraries. First, within the local project environment, make a copy of all the assets and folders you want to transfer. Next, paste the folder where the copies are located into the Inventor project definition on Fusion team.

After enabling the Inventor project for Fusion team, use the move feature of the factory design utilities in the asset browser to transfer the local asset copies to the library folder defined on Fusion team. Now, this operation is necessary because it is the only way to resolve the file associations in the assets Inventor files.

Also, creating a copy beforehand doesn't remove the local library. So transferring factory assets from Fusion team to a local project, this can be done in the same way without creating a copy of the assets to be transferred. In this case, all the assets must be synchronized and then the assets are moved and only the local copies are transferred.

This means that the assets will still remain in the cloud on Fusion team. This video also shows the workflow described on the previous slide, using the best data provided. The first step is to copy the local factory library to a local factory library transfer folder. You can then use the project definition in Fusion team, including the local deployment folder.

And after this, you can transfer the local library in the local transfer folder to Fusion team using the asset browser's move function. If you examine one of these library parts on Fusion team, you will see that all file links within the lab report have been resolved to the correct file location on Fusion team.

So next, I want to explain how to comment, track, and visualize changes on Fusion team. Now, to comment on and communicate an overall model such as a production line, it makes sense to create Navisworks documents and NWD files for relevant changes, and push them to Fusion team. It also makes sense to comment only on NWD files, as their creation is faster and you can better control the delivery of relevant versions for major changes.

And also remember, comments are stored within the version. You can mention team members. And it is more efficient to work in multiple browser windows, rather than constantly switching between model and sub-model views.

It can also be good practice to set milestones for relevant versions or major changes, which can also help to better understand which versions are relevant for comparison. And also remember to use the view cube function to set a proper view orientation if needed. And I would also recommend disabling the zoom towards pivot point option and reversing the mouse zoom direction, if necessary, to improve the overall navigation experience.

Now, the context menu and the pivot function could be very helpful to set a reasonable rotation center when navigating within a model. Now, the best way to understand changes in the colored mode is to compare versions of Inventor models. This feature is on the versions tab and doesn't work well for Navisworks files and AutoCAD files.

In the changes menu, there are also some functions, which are not obvious, for hiding properties, transformations, and shape changes, which can be very helpful, as well. And also note that there is a side-by-side mode to understand and see design changes.

The video here shows an overall Navisworks model and its file versions, and communication to indicate some required changes. To test this behavior exactly as shown here in the video, download the test files. In the class handout, you will find step by step instruction on how to create the different versions for the examples shown here in this video.

You can then test the comparison tool by comparing the different factory .NWD versions on Fusion team. If you want to do the same for the Inventor sample assembly, you will also find step-by-step instructions in the class handout. You should also consider to set milestones for the relevant versions to be compared on Fusion team.

And due to an error, which makes Fusion team consider that IAMs are empty, it may be necessary to open and re-save the Inventor assembly directly on the Fusion team drive. And finally, try playing around with the features of the comparison tool, as shown here in the video.

Check out how to track changes and also try to create some new comments and understand how they relate to the versions they are created in. Now, to conclude this chapter, here's a brief overview of workflows that are currently causing challenges or do not work well. It is important to understand that I have created Autodesk support cases for all of these issues and expect these behaviors will improve in the near future.

If you would like information about a specific issue and whether there is a solution or not, you are welcome to contact me on LinkedIn. Now, to conclude this presentation, I would like to share some insights into Autodesk data exchanges, the Autodesk Construction Cloud, and sin2, a service that can be connected to the ACC, and Yeah, let's get started with Data Exchange and Autodesk Construction Cloud.

So this video shows what could be possible with Autodesk Data Exchange technology if Inventor factory and Revit are combined in a design workflow. It starts here with multiple data exchanges of Inventor factory models already referenced in the Revit project. You can see the performance in 3D and 2D and see what might be possible in the plan view, for example, adding annotations or set color filters and so on.

You can also see a [INAUDIBLE] for what I have used a logic and dynamo to transfer various properties from Inventor to Revit. In the next part of the video, I designed some cable routes and pipings in the context of these data exchanges, and transfer the results to ACC where I analyzed some collisions that I may have seen before but overlooked for some reason while working in Revit, an issue that is created on the model coordination of the ACC, describing what needs to be changed to make the overall design meet our requirements, defining who is responsible for this and specifying when the issue should be resolved.

In the next step, you can see how the design change is done in Inventor by adjusting some values of the use parametric factory asset. These changes are then updated using the Data Exchange connector, which generates a new Data Exchange version in the project on the Autodesk Construction Cloud.

Then back in Revit, a new version of the reference Data Exchange is available and the model can be updated. And finally, the design solution can be checked on the Autodesk Construction Cloud and the problem can be marked as in a review or as resolved.

So the final video of this presentation shows a point cloud on sin2 and an Inventor factory model connected directly from the Autodesk Construction Cloud as a Navisworks cache file, and how it can be compared to the point cloud. Differences between the planning model and the reality can be easily analyzed and also documented in a web browser.

Now, it is important to understand that the entire Inventor data does not need to be transferred to the ACC, which, by the way, is not a good idea. So just one Navisworks cache file is necessary and sufficient to complete this workflow.

So with this explanation, I hope you enjoyed this presentation and learned something new, some new workflows with Fusion team and Inventor factory design utilities. Thank you also for watching and listening to this presentation. I wish you a nice day and good luck in using Autodesk software. Bye bye.

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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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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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