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Explore your plant with digital twin

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Description

Today’s plant operations and maintenance processes require a highly experienced workforce to gather information from multiple sources while collaborating seamlessly across all stakeholders. Discover how the global operating company ANDRITZ has equipped their teams with an Information Hub which centralizes multiple data sources into an up-to-date Digital Twin of their plants. The class will highlight how 3D model data, 2D schematic diagrams, Equipment information, Documents, Maintenance tasks and even real time sensor information gets interactive linked together and provided to the stakeholders as an easy to use web application. Together with best practices how to build a sophisticated solution based on Autodesk Forge we will also share practical benefits the teams now experience by taking faster and better-informed decisions. The session will conclude with the various positive business outcomes companies can achieve by providing such a hybrid environment to their stakeholders.

Key Learnings

  • Identify the business use cases and benefits of the digital twin solution
  • Enable central access to the up-to-date plant information from various sources for all relevant stakeholders
  • Understand how to design & implement your own digital twin based on Forge technology
  • Apply a generic digital twin framework via combining with domain specific solutions for all divisions

Speakers

  • Avatar for Christian Gartner
    Christian Gartner
    Christian has been working at Andritz since 2010. He has more than 10 years experience in software development based on Autodesk products. In his current role he is responsible for the architecture within Smart Service and work closely with the various project teams.
  • Avatar for Jan Liska
    Jan Liska
    Jan has been with Autodesk for almost 20 years. At Autodesk he started as software engineer in Inventor product development. Later Jan moved to Consulting organization where he worked as Solution Architect and supported various customer projects - both small POCs as well as large enterprise projects. Jan is now working in Tandem team as Developer Advocate supporting both internal and external developers.
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Transcript

CHRISTIAN GARTNER: Hello and welcome to our class Explore Your Plant with Digital Twin. My name is Christian Gardner I'm working at ANDRITZ since 2010. That resides in more than 10 years of software development and managing software implementation projects. Started as a software developer in our PLM area in 2010. And now in my current role working as a solution architect in our Smart Service program.

JAN LISKA: My name is Jan Liska and I've worked for Autodesk since 2003. I started as a software engineer and Inventor product development and then I moved to Customer Success Organization. I am currently involved as a Solution Architect in a couple of customer projects which are utilizing our forward platform.

CHRISTIAN GARTNER: The agenda of this class. We will start with an introduction about the company and our group. Continuing with the main topic for today, our approach of a digital twin. That includes the initial situation, following with our solution in multiple phases, and a demo. Then, switch to the technical part of the class, which gives an introduction on the architecture to see how it was built. Finally, we want to show you some insights in what we learned and end with the benefits of our solution.

ANDRITZ group. Who we are. ANDRITZ is an Austrian-based company with approximately 27,000 employees. ANDRITZ is a globally leading supplier for various types of machines and plants. The headquarters in Graz, but there are over 280 production sites worldwide and also service and sales companies around the globe. From a sales perspective, ANDRITZ reached over $6 billion last year. There are only a few companies on the market with that product portfolio, which brings us to our products.

ANDRITZ has a diversified group of products which are divided into 4 business areas- pulp and paper, hydro, metals, and separation. Pulp and paper provides machines and plants for providing pulp and paper. For example, paper tissue toilet papers. Hydropower offers electromechanical equipment for hydropower plants, pumps, and turbo generators. Metals offers systems for producing several types of steel. Presses, pressed lines, a big percentage for the automotive industry. And separation means equipments like centrifuges, separators, covering screens, and all kinds of filtering systems.

Metris, ANDRITZ's digital solutions. With Metris as a brand, ANDRITZ offers a broad portfolio of intelligent digital solutions and products. And one part of Metrix is Smart Service, which is our group. Metris Smart Service is part of the global ANDRITZ digitalization initiative for enabling digital solutions to support all kinds of business processes by increasing the efficiency and benefit along various life cycles in a digital way. The target is to search, explore, and implement convenient digital products which simplify and optimize internal and external workflows and communications.

We are currently having six projects where we are working on. Two of them are the engineering-construction-service platform, and the Metris digital plant documentation, which we will cover in the next slides.

Let's start with a short introduction in the engineering-construction-service platform, because it's one of the core elements of our digital twin solution. Within this project, all of these BIM 360's used this as a central tool to access and collaborate on the latest engineering data and documents along the different phases of a project. In addition, relevant site processes, like design deviations, are handled with BIM 360.

ANDRITZ has three main engineering disciplines, mechanical engineering, plant engineering, and process engineering. In these disciplines, different design tools are used. Connecting these tools with BIM 360 allows all stakeholders to work on the same documents on the latest state. So summarized, all the relevant engineering documents should be accessible from BIM 360.

But now coming to the main topic for today, Metris digital plant documentation. We started. We identified some problems faced by plant owners along their digitalization journey. First the handover. Enormous quantities of paper-based documents are handed over as part of the project delivery. Storing and protecting this huge amount of paper-based document over time, is challenging.

Brings us to the challenges. How to access, navigate, extract, and even worse, how to maintain the as-build status of the plan across paper and electronic formats. Furthermore, associate and integrate all information within one system.

According to a Siemens paper, industries spent up to 10% of their revenue and 25% of their labor costs on document production and management costs. New users, which are not familiar with the plant layout and supplier documentation, cannot locate specific information within 15 minutes. And users spent 20% of their working week locating documents for other users and answering general questions.

Our answer to this, and many other challenges is Metris digital plant documentation. The goal was to provide a digital version of a plant with all relevant information connected within one application.

JAN LISKA: The main features of the solution is the ability to display a relationship between 3D model of the plant and associated P&ID diagram. The user can select element in the diagram, and application will automatically highlight the same element in the 3D video. The application also displays associated metadata for each element. This information is not part of the design data, but we read them from the external systems. The solution provides the ability to apply color coding on the 3D model based on associated data.

For example, users can use this functionality to easily find all pipes based on the type of the media. And it also provides possibility to get related documents, such as technical specification, operation manual, and so on. These documents are managed using document management system.

CHRISTIAN GARTNER: The first version, with the features Jan explained, is in production since last year. The typically user scenarios are providing an ANDRITZ-branded digital twin for engineering documents, and use it as a final customer documentation instead of handing over paper for this.

Now it's time for a demo to show you the application.

PRESENTER: Welcome to the live demo of the digital plant documentation. The digital plant app is a web application which you can reach via digitalplant.andritz.com. So lets directly start.

Here we are on the login page. If you have already an account you just click on terms of use and then on login. Otherwise click on support to request one. So let's start. First, I have to enter my username. This application is connected to our ANDRITZ ID, which means you can use your ANDRITZ credentials to log in. And because I'm using here a company PC, I will be automatically redirected without entering the password. Good.

You're on the project overview selection election, where we first have to select a project. Let's select an Nettingsdorf project, then a planned island, and finally the model. The other parts here I will show you later. Now let's focus on this [? ready ?] model first. Let's keep this for now.

And here we are on the main page of the application. On top, there is the project selection. When clicking here we can change the model plant island and the project. And here in the center, there is the viewer to display 3D models and 2D drawings. We use here the same technology as in the spare parts catalog. The advantage of the newer is that it works in a modern browser without installing any software. So you can use it on a tablet, smartphone, as well as on a PC.

[? Rift ?] as you can here browse through this 3D model, zoom in, select objects, hide it, further look into this 3D model, and so on. There are options to measure, explode the model, you can also open the model browser to go through the tree, and so on. Good.

I will show you the main functionality of this application based on one specific use case. Let's assume we have an issue with our plant here, and we need to investigate it. We know that the issue is on a specific valve. So we need to check the attributes of that valve and have a look into the user manual. And there are different ways how to find out that information.

Let's start with the first one based on this 3D model. If we would know the exact name of the valve, we can directly enter it here to find it. But we just know it's part of the high pressure piping. So you can select here "high pressure piping," isolate it so that only high pressure piping is shown. And then you see we see only the piping elements. Which makes it easier to identify our valve. So let's zoom in. Here I already see that is the valve I'm looking for. So let's select it. And open this panel here.

And here we see all relevant properties of that valve. For example, the manufacturer, type, dimensions, and so on. In addition, all linked documents to that valve are shown here and can be directly downloaded. So let's download the supplier manual. It takes a few seconds because it's a 250 page document. There it is. Well let's open it. The US operation manual of that valve.

So that helps us to really check the details of the valve and investigating our issue. So let's close this here. And of course, if we would select a different path or visit the properties and delete document changes. This is one way, how identified above. Let's close this here. So back to the whole model.

The second way is identify our valve based on P&ID drawings. For that, I open the project selection. Based on a plant island I can select the process area, let's select steam system and then the main steam P&ID. Now, a second window is opened where the P&ID is shown. So we have now on the left side this 3D model, and on the right side the P&ID. based on the screen resolution we can also change the view orientation or switch to view mode so that only 2D, 3D, pro version.

Because we want to now focus on the P&ID, let's switch to P&ID mode only. And open our property panel again. Now we can check the P&ID. Click here on an object and check our attributes. That's the wrong one. That's what we are looking for. And also here, based on the selection on the P&ID, we see the properties on the right side and the linked documents. So same functionality as we have in the 3D model.

In addition, what we also can do, we have a link between the selection in 2D and 3D. So it means if I open now the 3D view again and select, here on the right side, an object, that one is automatically highlighted in 3D. So let's select another object, for example this one, and you see the selection in 3D changes automatically. So that helps us in our use case now, to identify the valve based on the P&ID.

And now, we can check the surroundings of that valve in 3D. For that we switch back to 3D. Show all objects. And then we can really check where the valve is installed. And that could help us when we need to do some maintenance, to see the location of that valve and the surroundings. For example, here the pipes, the other valves, and so on. Good. That was the second way, how to identify our valve.

And last but not least, I want to show you color-coded views. So based on this redeemable, we can select the theme. A theme consists of a set of rules which defines how the objects of our 3D models are colored. So let's select here the coloring media. It takes a few seconds until the calculation is done. In the meantime, we can open the properties panel, go to theme, and here we see the legend. So we see we selected coloring media, and HP feedwater, for example, is now dark blue, exhaust system is colored yellow, and so on. Let's zoom in a bit. And here we see it already. We have here yellow elements, we have light blue, which is LP feedwater, and we have here also dark blue element, which is HP feedwater. And that theme here, where the color is based on the media, could also help to identify our valve because we know every HP feedwater relevant object is in the color dark blue. If it's related to exhaust system, it's in yellow.

This color-coded view can be used for coloring based on media, it can also be used for color objects based on their status, for example an installation status or an operation status. This was based on the media, this is just an example. So let's go back to the different color. All right. That's it.

CHRISTIAN GARTNER: I hope that gave you an insight into the application, but our development has not stopped. Now we are extending the solution from a digital plant documentation to a digital plant twin. The first version contains mainly static information. Extending it to a digital plant twin offers an integrated overview of the plant condition while giving access to domain-specific expertise from connected systems. That allows operators to have an aggregated overview of the relevant information and to navigate to these systems for further analysis directly from digital plant.

JAN LISKA: In the second version of the solution, we implemented the additional functionality. Ability to display sensors on top of the 3D model and P&ID diagram, for each sensor you read data from the distributed control system. You also can display graphs of the values for the last 24 hours. In addition to metadata and documents, you also expose information from other systems, such as asset management, or spare parts catalog. The application can be used as a dashboard to check on a condition, or the plan in real time.

Now let's talk about the architecture of the solution. The solution is built from several components. We developed a generic framework which works across multiple domains. It uses Autodesk Docs as a common data environment for engineering documents. Autodesk Docs allows us to organize design data and flexible folder structure. It also provides possibility to control permissions. Only authorized users can have access to the data. As a data hub provides unified access to information stored in multiple external systems, and a message broker is designed to provide notification between multiple components of the solution. We have the Web UI, which integrates [INAUDIBLE] plays a key role in the visualization of both 2D drawings and 3D models.

Data visualization extension is used to visualize the sensors on top of the P&ID diagrams and 3D models. And we also developed custom extensions to add extra functionality on top of the viewer, such as cross highlighting, and the color coding. We deployed the whole solution in the cloud. We are using Microsoft Azure as our infrastructure.

Let's look into data flow inside our solution. Design data, such novice first models and diagrams, are uploaded into Autodesk Docs. The data are automatically published in the viewable format, which is used by the web user interface. The web user interface provides user experience to view both 2D drawings and 3D models. It also connects a data hub to get information for currently selected element.

CHRISTIAN GARTNER: Yes, a data hub acts as a central data and access layer for all asset data, independent of domain specific solutions. It combines all different representations of an asset, like maintenance information, documents, and any other relevant information, and grows during the lifetime of an asset. This data hub can be used from every system, which need to access asset relevant information and [INAUDIBLE] via a standard interface.

Now, let's jump to our next demo to show how sensor data are integrated into the system. Within this demo, a synthetic data set is used because we are not allowed to share real customer data here. If the user has their permission, he can select operation data as part of the project selection. Then, on every equipment where sensors are connected to, dots are shown. User can hover over these dots to see some basic information and select the sensor. Then in this pop up, the latest value is shown. And in addition, a history of the data.

The interval can be configured project-wise. In this case, the latest value is updated every 10 seconds and the trend, every minute. In addition, here in the bottom, a link can be displayed which enables the user to directly jump to the operating system. Here in development, the dummy system is mentioned. But if on the project, a real operation system is connected, then the user can directly click on it and jump to the operation system for further analysis.

These sensors are available on 2D as well as on 3D. All right.

Lessons learned. One of the most important prerequisites for such solutions is to have a good data quality. Mostly all data are available in digital form today but often not connected. As an example, a pump. The pump is visualized in different drawings in a 3D model. Schematic drawings. There are user manuals for the pump but with the name or the idea of the pump, it's not easily possible to get all related entities. And post-processing of that existing data is very time consuming and costly. Data has to be worked through again. And in addition, that's usually done from people other than those who generated the data. Which takes more time.

Our engineering teams did a good job. Better, a great job to optimize the process and include it in the standard design process. For example, adding metadata and linking with assets, or link schematic drawings with 3D models, directly in the design tools. For that they create plug-ins for the design tools to support that process. The screenshot on the right side shows a tool to map equipment from process engineering with the representations in 3D, directly in the plant design tool. That results in a huge benefit, also in the engineering itself and subsequent processes.

JAN LISKA: So how did we develop the solution? We used a [INAUDIBLE] methodology for the development of the solution. We had 2 main development cycles. As Christian said, focus of the version 1 was mainly on the static data. In version 2, we added support for the dynamic data related to the sensors. For each cycle we had multiple sprints and implemented new function with the incremental based on the priorities.

During development we were also listening to users and incorporated their feedback. We are also in close contact with the Autodesk product development, and work with them to make sure that our needs are covered. This was mainly the case of the data visualization extension. One principle we tried to follow was to avoid domain specific solution. Install base people generic layer is the standard interfaces.

CHRISTIAN GARTNER: It's seamless access to plan data. Anytime and anywhere. So digital plant is a web application and can be used from any device with a browser and internet access. Prevent faults and shorten down times. There is no need anymore to search through several ring binders looking for circuit diagrams, part lists, and manuals. Finding instead of searching, by identifying components directly in the 3D model.

As an example, not all users are familiar with schematic drawings to identify the right components while searching through several documents. With digital plant, the user can identify the right equipment directly in the 3D model, while being in front of the physical equipment in the middle of the plant.

Direct and central access to all relevant asset information and documents in one place. And better and faster overview of plant condition also provides time savings for several user groups.

Finally, we want to say that we are starting here a journey that will evolve over time and open us the door to a world of solutions. With that, we are at the end of our presentation. Thank you for listening. We hope you learned something.

Downloads

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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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