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Digital Transformation of Data from a Disjointed Legacy System into the Cloud

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说明

Gain insight into how the technology can help transform the traditional organisational system to become modern, productive, and cost-effective by utilising product customisations and configurations that fit the specific organisation's needs. We will show how Upchain answered the call for transforming messy data and legacy systems into a synergy of custom-tailored processes that all work on unified digital transformation. We will show how this process was implemented within ATS Automation Tooling Systems, a company that designs and builds custom factory automation systems.

主要学习内容

  • Gain insight into how Upchain can bring order to data for an organisation with dozens of legacy systems.
  • Learn how digital transformation helped organisation to move out of traditional, disjointed PLM into a modern and cloud based
  • Discover what practices you can use for utilising mechanical and electrical designs in one system.
  • Which ATS Corporation products and facilities are leveraging the Autodesk Upchain product.

讲师

  • Andreja Schneider
    Andreja Schneider is a Product Management Engineer at Autodesk working on PDM / PLM product portfolio. She has over 11 years of experience in the Industry and works closely with Autodesk customers, partners and internal stakeholders on Upchain product consulting and development strategy. Before moving into Product manager role, she worked as BA, QA and Product Owner.
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Transcript

ANDREJA SCHNEIDER: Hello, and welcome to today's session where we are going to talk about the digital transformation of data from disjointed legacy systems into cloud. This is going to be an Upchain customer case study. My name is Andreja Schneider. I'm from Autodesk. And with me, I have Colin Henderson from ATS company.

And with that, let's move to the safe harbor statement. Please take a few moments and read through the safe harbor statement. The most important part is that this is AU content, and it is proprietary. Please do not copy, post, or distribute without the express permission.

Let's move into introduction and agenda. So as I said, my name is Andreja Schneider. I'm a product manager in Upchain within Autodesk. And with me, I have Colin Henderson. He's a manager at engineering business systems within the IT within the ATS corporation.

Let's go through summary and objectives of today's lesson. In order to scale their business, an organization consisting of dozens of legacy systems was able to digitally transform out of traditional PLM system and into a modern and cloud-based one. We are going to show you how they accomplish this with the help of Upchain. We're also going to show the processes that the organization used in order to achieve this.

Now, let's go through today's agenda. So after the introduction, we are going to talk about what company ATS was looking for. And then we are going to tell you what was achieved. Also, we are going to speak about elements included in the process. And in the end, we will show some ATS project examples. And we will finish off with the summary.

So moving into introduction. So first of all, we are going to talk about Upchain. So Upchain is a cloud-based SaaS solution for PDM, which enables delivering of data and process management capabilities that enable manufacturers to digitally transform product development and collaborate seamlessly across the value chain. It is used by engineers, by designers, by project managers, and any extended teams to ensure everyone works from a central source of truth for the product data. Some of the elements that Upchain product include are managing projects, bill of material, business processes, multi-CAD support, customizable and business-oriented workflows.

So what can you do with Upchain? With the ability to connect, our users can use design from multiple CAD tools and bring them all into one collaborative plan. With modifying, companies can have different teams all working on the same build material while keeping and tracking revisions and history, thus enabling concurrent engineering. Organizations can use adjustable and configurable processes and implement additional product revision and quality control. And with the ability to inform, system can notify the stakeholders as they are getting involved into the process.

Let us show you some of the more notable Upchain customer examples. So you can see that we have customers from different industries ranging from automotive to industrial machinery to consumer electronics and even education and fitness technology. Now, to go into details for one of our larger customers the ATS company. Colin, handing over to you.

COLIN HENDERSON: So ATS is an industry-leading automation solutions provider. And I like to say to people who ask, we make things that make things. So we make the machines that other companies use to make their product.

We've got a wide breadth of custom automation experience. We've been doing this as an organization for quite some time. So we've built up our experience here with custom repeat and the value-added products around those machines. And we service a wide breadth of industries with our machines here.

Next slide. So since our initial founding in 1978 by-- started out as a small company inside his garage. It has grown into this international automation company with 40 years of total experience. 20 countries, 60 facilities, 80 offices, and over 6,500 employees around the globe now.

ANDREJA SCHNEIDER: So what was the ATS challenge? They had their own legacy system that had a high maintenance cost. There are a company that supports many industries, so we're looking for a tool that would be flexible enough to match their many different processes adjusted for specific industry regulations. Request for change was also driven by their need to enforce the modern PLM and to improve their processes in data organizing and maintaining, all of that with a tool that can support and improve their legacy data.

So what was it is looking for? They wanted the cloud-driven solution with high-level control of systems and processes, which would support their organizational business needs. Also, it would help them reduce the dependency and costs in maintaining their own infrastructure.

The solution to their need had to be collaborative in nature and able to support their worldwide organizational units while also keeping their data secure, allowing for data to flow where needed and when needed. While keeping up with their many processes and being able to support them, the solution would also need to be able to improve the quality of legacy data while ensuring the new data comply with their regulatory data standards.

So what was achieved? Instead having the on-prem solution, which requires heavy maintenance costs, Upchain offered a hosted and externally managed solution for ATS data and processes. Options configurable processes were able to adjust ATS's specific type of business units, all that within one shareable system where data can flow back and forth with adjusted permission control level.

ATS did not need to clean up their data first in order to bring the data into the Upchain system as it would be the case with other solutions. But instead, Upchain offered for importing of legacy data as is. And when data was reused, it would be adjusted and corrected into the process. With that process, ATS was able to achieve a higher level of standardizing their data than compared to before.

What was the outcome? So having one central data system, ATS business units or divisions were able to work together more effectively in real-time across continents. Now, divisions in Europe would collaborate and contribute to the same project or assembly lines as the one in North America, giving ATS flexibility to work on even larger scale projects or even parallel lines projects with a different config settings. Their biggest programs today include assemblies that are larger than 100,000 components. Colin, would you please explain to the audience what program in your organization means and consists of?

COLIN HENDERSON: For us, a program would be a collection of projects. So a program may comprise of multiple builds of the same type of line, or it may be a collection of projects where we're building several lines working together to achieve a final product.

ANDREJA SCHNEIDER: Yeah. So showing you here just a glimpse of one of the large building material data set that we store in Upchain. And imagine the complexity of such a large bill of material, the effort it takes, the alignment of many teams and divisions to simultaneously work on bill of material of 100,000 components. And with this, we are moving into process highlights.

We would like to dive into Upchain's processes and explain the three-step process that ATS is using. First, starting with the design. Their engineering create the required design and building material data. They have the flexibility to either create the data from scratch or to reuse many legacy data, which they would use as is. Or can create new versions of and integrate into their design.

After the design is done, it is being sent for review and verification using a change request, which uses both combination of automated and manual checking processes and routes the data and build material design to the appropriate management, which is belonging to specific part of the organization. And after design is approved and released with the change request, engineers order required bill material amounts and participate in ordering process by instructing the procurement team when is expected such order arrives in the warehouse for the assembly. Let's go into more details into each of these processes.

So here, we are starting with multi-CAD support. And here, we'll be demonstrating how ATS is importing the data into the system. Also, how system recognizes the different data attributes and creates appropriate item types.

ATS is also using options item numbering and revision control schema for their users to differentiate between legacy and data changed in the system. Upchain is also offering both version control on the BOM or item level, but also on a file or CBOM level. A file may or may not be associated with an item in the BOM. And from ATS's standpoint, bill of material level has greater importance over the CBOM or the file level.

So in this video, you can see how an engineer is importing the design into the Upchain using a plugin, where Upchain can link the top assembly to a specific bill of material item created in advance under associate project. And thus enabling the import of the design directly into specific instructed project. This can be used for data organizing means or for security, where only team members can access the data.

The attributes on the files are being read and checked, and appropriate item types within the structure are being created in the system. Engineer has the means to review the data while it is being imported and data is locked for the user while they are making changes. In the plugin, user has many available information to review the data before committing the changes. And anything that is done and saved in the plugin, it is also being reflected in the web app. That's for the other engineers, engineering managers, or project managers to review.

Moment attribute and structural changes can be further done in the web app without the need to change the CBOM files. New material structures are fully reusable between the projects. And because of revision control and various information, it also offers history information tracking.

Now, moving into adjustable business processes. So after the design has been finished, it is sent to change request process for approval. ATS change request workflow uses many level of controls and checks for appropriate attributes of submitted items based on business unit association, project association, CAD data association, and many more. In case any of the data being checked by the workflow is not correct, it will stop and create a task with requested detail, also for the appropriate person to correct the data.

When all checks pass and data is conforming by the business rules set in the workflow, appropriated designated persons are notified about the design changes and requested to approve the design. After this is approved, the system is making the necessary data changes in order to release the design and create additional metadata. For example, like populating driving attributes and curly codes or creating translations.

Now, just for comparison on complexity of ATS change requests workflow, here's an Upchain's out-of-the-box workflow with just 10 steps. It encompasses the basic processes for approval and release of the BOM. And now, this is the ATS change request workflow, which contains over 100 steps, out of which some need to go through several iterations in case design and data need to be corrected.

Going back to Upchain demo within the web app. Here, we are showing that after design changes have been made, an engineer triggers the change request process or the CR. The CR workflow makes the necessary data and attribute checks. And in case anything is missing or not conforming to the custom rule set, the system creates a task for responsible person and can also send a notification email about the work that is required. Task is filled with details that need to be corrected or with instructions for the reviewer to check the submitted data set before the approval.

Approver can review the data by downloading it right from the web. And if necessary, reject the design. The engineer would update the design data after receiving a task for it and submit to a review process, all that within the same CR workflow process.

After the approval has been given, data is updated and marked as released, together with all supporting metadata. Such release the design is now locked for further editing. And if required, an engineer would create a new revision of an item to start next iteration of the design.

After release is done, engineer would proceed with requisition process, which contains mechanisms that prevent over-ordering of assembly components. All that with a goal to minimize the ordering expense cost and scheduling mechanisms which signal to procurement department when it's required that particular component arrives into the warehouse. Thus enabling component delivered at the right time so that assembling process would not be halted until a particular component arrives.

After required components have been identified, the requisition is being reviewed and approved by required management team based on the total cost basis. And after approval was given, bill of material and requisition data is being extracted out of the option and sent to ERP system over an API connector. This short example of a requisition order we are showing how a release assembly is being ordered over several requisition processes.

Upchain is checking the assembly bill of material quantities and uses that information to calculate the maximum allowed amount for order of selected components within a requisition, thus preventing over-orders, which, in case if this mechanism would not exist, could cause for additional cost for the company. After workflow is initiated, a responsible approver will get this task for review, also with the work instruction detail. And after the approval, the system records the previous ordered bill of material quantities. So when a new requisition is initiated, previous orders are taken into account.

At that time, previous maximum ordered quantities can only be returned and only if needed, and other not yet ordered or fully ordered components can be requisitioned. After each requisition, information about the order is transmitted to ATS's ERP system over APIs. The Upchain system stores the information about previous requisition, as well as previous change requests if this information is ever needed for a review.

In this last part of Upchain's three-step process that ATS is using, we are now moving into next section, which will show us examples of ATS products and facilities that they are leveraging Upchain system. Colin, moving to you.

COLIN HENDERSON: So I just wanted to highlight a couple of our larger business segments that are making use of Upchain here, life sciences being one of those. And we service several technologies there, basically in the business of helping people. And we've built machines that produce products for medical devices, diagnostic, pharmaceutical, and pharmacies and laboratories.

One of our other major segments here would be the industrial automation. And they serve a wide breadth of different types of industries there as well. One of the more notable ones was probably the electric vehicle or EV mobility automation. I highlight that one just because the amount of activity lately in that area, but also nuclear automation, speciality automation. So special businesses and consumer products fit in this business segment. Next slide.

I just want to highlight that EV or electric vehicle area. This is a point case that really was enabled by Upchain, where we've added on several manufacturing facilities just to support this program running through. And this program runs across I can't count how many different business units are contributing to both the engineering and manufacturing of these machines.

And these are some of our larger bills of materials that are being built by users across the globe. And this is enabled by our Upchain implementation here, where all these users are able to interact and see the contributions by others. And then produce that production successfully to support our customers.

ANDREJA SCHNEIDER: Thank you, Colin. And with this, we move into summary. So today, we've learned about Upchain capabilities, and how ATS, a company with dozens of legacy systems, were looking for a tool that would enable them to transform digitally. Upchain was able to adapt their many processes and support their organization to scale by providing means to keep the data in one central system, which addresses their data gaps and fixes them. We also heard of three-step process that ATS is using to ensure their data is organized and standardized based on required business parameters and also secure. Thank you for listening.

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我们通过 Google Optimize 测试站点上的新功能并自定义您对这些功能的体验。为此,我们将收集与您在站点中的活动相关的数据。此数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID、您的 Autodesk ID 等。根据功能测试,您可能会体验不同版本的站点;或者,根据访问者属性,您可能会查看个性化内容。. Google Optimize 隐私政策
ClickTale
我们通过 ClickTale 更好地了解您可能会在站点的哪些方面遇到困难。我们通过会话记录来帮助了解您与站点的交互方式,包括页面上的各种元素。将隐藏可能会识别个人身份的信息,而不会收集此信息。. ClickTale 隐私政策
OneSignal
我们通过 OneSignal 在 OneSignal 提供支持的站点上投放数字广告。根据 OneSignal 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 OneSignal 收集的与您相关的数据相整合。我们利用发送给 OneSignal 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. OneSignal 隐私政策
Optimizely
我们通过 Optimizely 测试站点上的新功能并自定义您对这些功能的体验。为此,我们将收集与您在站点中的活动相关的数据。此数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID、您的 Autodesk ID 等。根据功能测试,您可能会体验不同版本的站点;或者,根据访问者属性,您可能会查看个性化内容。. Optimizely 隐私政策
Amplitude
我们通过 Amplitude 测试站点上的新功能并自定义您对这些功能的体验。为此,我们将收集与您在站点中的活动相关的数据。此数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID、您的 Autodesk ID 等。根据功能测试,您可能会体验不同版本的站点;或者,根据访问者属性,您可能会查看个性化内容。. Amplitude 隐私政策
Snowplow
我们通过 Snowplow 收集与您在我们站点中的活动相关的数据。这可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID、您的 Autodesk ID。我们使用此数据来衡量我们站点的性能并评估联机体验的难易程度,以便我们改进相关功能。此外,我们还将使用高级分析方法来优化电子邮件体验、客户支持体验和销售体验。. Snowplow 隐私政策
UserVoice
我们通过 UserVoice 收集与您在我们站点中的活动相关的数据。这可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID、您的 Autodesk ID。我们使用此数据来衡量我们站点的性能并评估联机体验的难易程度,以便我们改进相关功能。此外,我们还将使用高级分析方法来优化电子邮件体验、客户支持体验和销售体验。. UserVoice 隐私政策
Clearbit
Clearbit 允许实时数据扩充,为客户提供个性化且相关的体验。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。Clearbit 隐私政策
YouTube
YouTube 是一个视频共享平台,允许用户在我们的网站上查看和共享嵌入视频。YouTube 提供关于视频性能的观看指标。 YouTube 隐私政策

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定制您的广告 – 允许我们为您提供针对性的广告

Adobe Analytics
我们通过 Adobe Analytics 收集与您在我们站点中的活动相关的数据。这可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID、您的 Autodesk ID。我们使用此数据来衡量我们站点的性能并评估联机体验的难易程度,以便我们改进相关功能。此外,我们还将使用高级分析方法来优化电子邮件体验、客户支持体验和销售体验。. Adobe Analytics 隐私政策
Google Analytics (Web Analytics)
我们通过 Google Analytics (Web Analytics) 收集与您在我们站点中的活动相关的数据。这可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。我们使用此数据来衡量我们站点的性能并评估联机体验的难易程度,以便我们改进相关功能。此外,我们还将使用高级分析方法来优化电子邮件体验、客户支持体验和销售体验。. Google Analytics (Web Analytics) 隐私政策
AdWords
我们通过 AdWords 在 AdWords 提供支持的站点上投放数字广告。根据 AdWords 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 AdWords 收集的与您相关的数据相整合。我们利用发送给 AdWords 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. AdWords 隐私政策
Marketo
我们通过 Marketo 更及时地向您发送相关电子邮件内容。为此,我们收集与以下各项相关的数据:您的网络活动,您对我们所发送电子邮件的响应。收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID、电子邮件打开率、单击的链接等。我们可能会将此数据与从其他信息源收集的数据相整合,以根据高级分析处理方法向您提供改进的销售体验或客户服务体验以及更相关的内容。. Marketo 隐私政策
Doubleclick
我们通过 Doubleclick 在 Doubleclick 提供支持的站点上投放数字广告。根据 Doubleclick 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 Doubleclick 收集的与您相关的数据相整合。我们利用发送给 Doubleclick 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. Doubleclick 隐私政策
HubSpot
我们通过 HubSpot 更及时地向您发送相关电子邮件内容。为此,我们收集与以下各项相关的数据:您的网络活动,您对我们所发送电子邮件的响应。收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID、电子邮件打开率、单击的链接等。. HubSpot 隐私政策
Twitter
我们通过 Twitter 在 Twitter 提供支持的站点上投放数字广告。根据 Twitter 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 Twitter 收集的与您相关的数据相整合。我们利用发送给 Twitter 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. Twitter 隐私政策
Facebook
我们通过 Facebook 在 Facebook 提供支持的站点上投放数字广告。根据 Facebook 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 Facebook 收集的与您相关的数据相整合。我们利用发送给 Facebook 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. Facebook 隐私政策
LinkedIn
我们通过 LinkedIn 在 LinkedIn 提供支持的站点上投放数字广告。根据 LinkedIn 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 LinkedIn 收集的与您相关的数据相整合。我们利用发送给 LinkedIn 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. LinkedIn 隐私政策
Yahoo! Japan
我们通过 Yahoo! Japan 在 Yahoo! Japan 提供支持的站点上投放数字广告。根据 Yahoo! Japan 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 Yahoo! Japan 收集的与您相关的数据相整合。我们利用发送给 Yahoo! Japan 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. Yahoo! Japan 隐私政策
Naver
我们通过 Naver 在 Naver 提供支持的站点上投放数字广告。根据 Naver 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 Naver 收集的与您相关的数据相整合。我们利用发送给 Naver 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. Naver 隐私政策
Quantcast
我们通过 Quantcast 在 Quantcast 提供支持的站点上投放数字广告。根据 Quantcast 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 Quantcast 收集的与您相关的数据相整合。我们利用发送给 Quantcast 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. Quantcast 隐私政策
Call Tracking
我们通过 Call Tracking 为推广活动提供专属的电话号码。从而,使您可以更快地联系我们的支持人员并帮助我们更精确地评估我们的表现。我们可能会通过提供的电话号码收集与您在站点中的活动相关的数据。. Call Tracking 隐私政策
Wunderkind
我们通过 Wunderkind 在 Wunderkind 提供支持的站点上投放数字广告。根据 Wunderkind 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 Wunderkind 收集的与您相关的数据相整合。我们利用发送给 Wunderkind 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. Wunderkind 隐私政策
ADC Media
我们通过 ADC Media 在 ADC Media 提供支持的站点上投放数字广告。根据 ADC Media 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 ADC Media 收集的与您相关的数据相整合。我们利用发送给 ADC Media 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. ADC Media 隐私政策
AgrantSEM
我们通过 AgrantSEM 在 AgrantSEM 提供支持的站点上投放数字广告。根据 AgrantSEM 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 AgrantSEM 收集的与您相关的数据相整合。我们利用发送给 AgrantSEM 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. AgrantSEM 隐私政策
Bidtellect
我们通过 Bidtellect 在 Bidtellect 提供支持的站点上投放数字广告。根据 Bidtellect 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 Bidtellect 收集的与您相关的数据相整合。我们利用发送给 Bidtellect 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. Bidtellect 隐私政策
Bing
我们通过 Bing 在 Bing 提供支持的站点上投放数字广告。根据 Bing 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 Bing 收集的与您相关的数据相整合。我们利用发送给 Bing 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. Bing 隐私政策
G2Crowd
我们通过 G2Crowd 在 G2Crowd 提供支持的站点上投放数字广告。根据 G2Crowd 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 G2Crowd 收集的与您相关的数据相整合。我们利用发送给 G2Crowd 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. G2Crowd 隐私政策
NMPI Display
我们通过 NMPI Display 在 NMPI Display 提供支持的站点上投放数字广告。根据 NMPI Display 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 NMPI Display 收集的与您相关的数据相整合。我们利用发送给 NMPI Display 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. NMPI Display 隐私政策
VK
我们通过 VK 在 VK 提供支持的站点上投放数字广告。根据 VK 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 VK 收集的与您相关的数据相整合。我们利用发送给 VK 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. VK 隐私政策
Adobe Target
我们通过 Adobe Target 测试站点上的新功能并自定义您对这些功能的体验。为此,我们将收集与您在站点中的活动相关的数据。此数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID、您的 Autodesk ID 等。根据功能测试,您可能会体验不同版本的站点;或者,根据访问者属性,您可能会查看个性化内容。. Adobe Target 隐私政策
Google Analytics (Advertising)
我们通过 Google Analytics (Advertising) 在 Google Analytics (Advertising) 提供支持的站点上投放数字广告。根据 Google Analytics (Advertising) 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 Google Analytics (Advertising) 收集的与您相关的数据相整合。我们利用发送给 Google Analytics (Advertising) 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. Google Analytics (Advertising) 隐私政策
Trendkite
我们通过 Trendkite 在 Trendkite 提供支持的站点上投放数字广告。根据 Trendkite 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 Trendkite 收集的与您相关的数据相整合。我们利用发送给 Trendkite 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. Trendkite 隐私政策
Hotjar
我们通过 Hotjar 在 Hotjar 提供支持的站点上投放数字广告。根据 Hotjar 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 Hotjar 收集的与您相关的数据相整合。我们利用发送给 Hotjar 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. Hotjar 隐私政策
6 Sense
我们通过 6 Sense 在 6 Sense 提供支持的站点上投放数字广告。根据 6 Sense 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 6 Sense 收集的与您相关的数据相整合。我们利用发送给 6 Sense 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. 6 Sense 隐私政策
Terminus
我们通过 Terminus 在 Terminus 提供支持的站点上投放数字广告。根据 Terminus 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 Terminus 收集的与您相关的数据相整合。我们利用发送给 Terminus 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. Terminus 隐私政策
StackAdapt
我们通过 StackAdapt 在 StackAdapt 提供支持的站点上投放数字广告。根据 StackAdapt 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 StackAdapt 收集的与您相关的数据相整合。我们利用发送给 StackAdapt 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. StackAdapt 隐私政策
The Trade Desk
我们通过 The Trade Desk 在 The Trade Desk 提供支持的站点上投放数字广告。根据 The Trade Desk 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 The Trade Desk 收集的与您相关的数据相整合。我们利用发送给 The Trade Desk 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. The Trade Desk 隐私政策
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

是否确定要简化联机体验?

我们希望您能够从我们这里获得良好体验。对于上一屏幕中的类别,如果选择“是”,我们将收集并使用您的数据以自定义您的体验并为您构建更好的应用程序。您可以访问我们的“隐私声明”,根据需要更改您的设置。

个性化您的体验,选择由您来做。

我们重视隐私权。我们收集的数据可以帮助我们了解您对我们产品的使用情况、您可能感兴趣的信息以及我们可以在哪些方面做出改善以使您与 Autodesk 的沟通更为顺畅。

我们是否可以收集并使用您的数据,从而为您打造个性化的体验?

通过管理您在此站点的隐私设置来了解个性化体验的好处,或访问我们的隐私声明详细了解您的可用选项。