AU Class
AU Class
class - AU

Bridge the Construction/Manufacturing Gap with Inventor Product Templates

共享此课程
在视频、演示文稿幻灯片和讲义中搜索关键字:

说明

Construction professionals are often burdened with the repetitive work involved in creating mechanical product templates for use by design and construction. By shifting from a “creating projects” to a “creating products” mindset, business logic and fabrication rules can be used to impact and influence the construction process. In this session, we will use relevant examples and a multitude of best practice tips to show you how you can do this successfully. An actual Autodesk customer will also join this session to share insights and experiences from their journey toward smarter and more scalable, repeatable processes.

主要学习内容

  • Learn how to create a more collaborative working relationship between designers’ Revit and manufacturers’ Inventor
  • Learn how to successfully start looking at prefabrication as a product and not a project
  • Learn how to build product templates that you can reuse on every relevant project
  • See this process in action and learn Autodesk’s best practices for template building

讲师

  • Andy Akenson 的头像
    Andy Akenson
    Andy is a Distinguished Software Architect at Autodesk. His main focus is Industrialized constructing bringing our manufacturing and construction portfolio together to help change the industry. He has worked for Autodesk for 15 years working on Inventor, Forge and developing new, innovative solutions to help our customers.
Video Player is loading.
Current Time 0:00
Duration 27:08
Loaded: 0.61%
Stream Type LIVE
Remaining Time 27:08
 
1x
  • Chapters
  • descriptions off, selected
  • en (Main), selected
Transcript

ANDY AKENSON: Welcome to the session, Bridge the Construction/Manufacturing Gap with Inventor Product Templates. In this session, we're going to cover changing the construction industry by moving away from project-based mindset to products with product templates created in Inventor. I'm Andy Akenson. I'm a software architect here at Autodesk.

Over the last 14 years here at Autodesk, I've worked on the Inventor product, getting Inventor technology into the cloud and our Forge platform, helping our customers automate their workflows. And for the last year and a half, I've been working in our industrialized construction team. I've been working on helping our customers bridge the gap between construction and manufacturing and helping automate the process from end-to-end.

JUSTIN RICE: I'm Justin Rice. I'm a solution architect in the consulting organization of Autodesk, and I work with some of our largest key clients to define and implement workflows based on our latest technology. In order to ensure the workflows align with the roadmap of our technology, I need to work closely with the product development teams. Specifically, I work very closely with the team Andy is on to understand the workflows and industrialized construction that are being developed.

Prior to joining Autodesk, I spent 20 years in the field working with clients to develop design automation applications. Those applications were focused on capturing the rules and the logic behind product templates, reducing the amount of effort it took to generate those designs, improving the quality and the standardization of those designs, and finally, eliminating redundant tasks. Some of my solutions have reduced effort from weeks down to hours.

ANDY AKENSON: So why do we need to build this bridge, and what is this bridge trying to span? It all starts with our vision. We want to help accelerate the adoption of industrialized construction by connecting design and make tools and enabling a data-driven process. So if we look at what some of our fundamental customer challenges are, if we start with the architect, they're often working with early design decisions that have to be made without knowledge of manufacturing feasibility, costs, or sustainability.

The construction manager is dealing with manufacturing detail that is defined after the design decisions have been made. And the subcontractor, the data they're working with is often incomplete, missing detail, and often has to be manually recreated. Now, let's hear directly from three people in the industry that are having to deal with these challenges today.

[VIDEO PLAYBACK]

- We originally did the thing-- automated prefabrication-- and had that chunk, but it's not connecting with the other stuff.

- Yes.

- And we do our own engineering, so we should have an advantage. But we're finding all these bottlenecks. And one big value stream is the idea, but it's hard to implement without the tools, and the data, and pulling it all together.

- Right.

- What we're doing now, we're beginning to treat-- for years, we've heard, just design it and we'll figure out how to prefab it. Do whatever you want and we'll figure it out. That doesn't work, because the rules, the data, and the information comes in after the design is done and then it throws us into this monster of a work cycle.

- And that's not working.

- It's a nightmare.

- And, like, one of the things that struck me working in the design field was that there was-- especially in, like, a hard bid process, there's no feedback loop at all. Like, I'm literally sitting in an office detailing something without any ability to check with the actual people who make that thing in a meaningful way and collaborate with them around that information. So it's about it's about bringing the making into the design--

- I love that.

- --versus sort of creating a design and hoping it can be made.

- [LAUGHS] Exactly.

- We have to kind of flip the script, I think.

- I love it.

- So you were asking me a question five years ago, what did I design in? I designed in fabrication in AutoCAD. Two years ago, if you would have asked me, it would have been, what are you designing? And I would have told you, we're in a Revit. Now we're doing Revit. Wow, this is great.

And I come here today, and we're designing in Inventor. And that just tells the whole story, right? Because Inventor's manufacturing. And you can't manufacture without an Inventor-like product.

[END PLAYBACK]

ANDY AKENSON: So to summarize some of the needed capabilities, the architect needs to be able to design with assemblies that are informed by what can truly be made and modified. The construction manager wants to clearly define and share what assemblies can be made and how they can be modified. And the subcontractor wants to be able to extract assemblies from the project to automatically create things like models, drawings, bills of materials, quotes, and not have the amount of rework that happens in today's project-based environment.

So if we look at the current flow of the project today, it starts with the owner informing the engineer of what products can be used, who then hand that off to the architect to consume that in their design. They then send that to the fabricator, who then sends that to the site to be installed. Now, any problems that are found in the field come all the way back to every step along the way, causing schedule delays, extra cost, and waste in the entire cycle.

Productization comes in when we start informing the design for the architect from what can actually be made. So the fabricator can expose what the inputs are so the architect's always working with fabricatable elements to help reduce issues in the field. This is where productization for construction comes in. Using a dynamic product template in Inventor, it provides that bridge between the design and make, so that we can inform design with customizations, we can automate fabrication information, we can define exactly what is made, how it is made, and defined what the allowable variations are, so we could provide things like levels of detail, or full detail for manufacturing, shop floor drawings.

This is all about providing the right information for the right people, so that a non CAD user can access the models and generate content, we can derive a wide variety of information from one single source template. And we end up with a one-to-many relationship where we can generate many unique linked instances from a source template. So if we look on the left, we've got a dynamic product template in Inventor. We can bring that into something like the large model we were in Forge, and from that, we can generate many different kinds of outputs.

JUSTIN RICE: OK, now let's take a look at productization in action. Within the consulting organization, we'll be working directly with Binksy and Snyder who is an 80-year-old mechanical contracting firm who was recognized as one of the most recognized mechanical contractors in New Jersey and Eastern Pennsylvania. Binsky delivers high-quality workmanship on projects from large traditional construction, to commercial HVAC, plumbing and emergency service. They combine state-of-the-art technology with experienced engineers to bring unparalleled client satisfaction, budget management, and scheduled delivery to projects of all sizes.

The focus of the project with Binsky will be to take their already developed bathroom battery and extend the capabilities of this product. The bathroom battery is a common building assembly, but it's complex to fabricate on-site. The number of variants depend on the number of stalls and the type of fixtures to be put into the bathroom. Are those fixtures either urinals or water closets?

By prioritizing this bathroom battery, Binsky has been able to realize a 40% reduction in costs and the ability to assemble this product 66% faster when it was been prefabricated. Moving this into more of a product and less of an on-site fabrication has enabled Binsky to transition from a traditional subcontractor into a manufacturer and really start to become part of the design team, while embedding their knowledge of the fabrication processes into the design process and ensure that fabrication knowledge informs the design of that new bathroom.

ANDY AKENSON: In this section, I'll cover what a template is, why they are important, and I'll walk through some samples of how they're actually used today. So if we look at templates in Inventor, they start with a highly-engineered configurable dynamic model. Parameter values are changed, rules are run, outputs are then generated for things like shop floor drawings, bills of materials for the supply chain, or downstream consumption for things like BIM or visualization.

If we look beyond parametric modeling with rules, Inventor supports iLogic, where iLogic enables rule-driven design that provides a simple way to capture and reuse your work. It allows the user to standardize and automate the design process. It's really built around automation, efficiency, consistency, and accuracy.

Let's see what this looks like in Inventor with a simple wall assembly. In Inventor, I have a parametric wall assembly. Contains things like top plates, king studs, bottom plates, cripples for above the door, and patterns for laying out the wall.

It also has an associated drawing to show things like step placement, overall width and height, and door position. The assembly is constructed with model parameters as well as user parameters for things like the stud spacing, or the stock, or the overall wall width and height. We can also get a hold of the bill of materials so that we can manage the materials for this wall.

In Inventor, we have the capability of adding iLogic rules and a form. Here, I'll show changing the stock size, make the width 12 inches. Let's change the wall width, the wall height, and we'll modify the door. You notice as we make these changes we don't just stretch the wall, but we also reposition the studs based on the rules. The drawing also gets the parts list updated, and when I update the sheet, you can also see the layout gets updated for the dimensions.

Now, if we go back to the bill of materials, you'll see it's been updated based on our wall changes. Let's take a look at the iLogic rule. We have configure rule.

Any time a parameter changes, this rule is run. So we have things like the stud spacing, the stock, the door distance, how far the door can actually be positioned, and how this studs, and cripples, and jack studs are actually laid out. These are all tied to Inventor parameters. Any time those parameters change, these rules run.

See, we also have rules in the drawing, so that when the drawing updates, we can get the intents from the drawing elements and we can relay out the dimensions. So here, you'll see us getting the dimensions for all of the various aspects of the wall, and then relaying those out based on the pattern. All of this code will be available in the handout for you after the class.

Now let's look at a more complex assembly. I have a balcony that's made up of parts and subassemblies for things like the decking, the handrails, and the glass panels. Here, we'll see the parameters, the number of user parameters that drive the model parameters, but the main are the width and the depth, and a more complex bill of materials. So this is for the entire part and subassemblies for the balcony.

We have an iLogic form. And as we change the width and depth of the balcony, you'll be able to see things like the glass panels change as well as the decking configuration. Things like this would be hard to do in parametric modeling, but with rules, it's pretty straightforward. So here, you'll see my rule, so that every time my parameters change, I can do things like changing the deck count, I can do my glass panel layout, I can reset the handrail, and I can set some extents to make sure that the balcony never goes over 5,000 millimeters. And here, you'll see the bill of materials update as I made those changes to me my balcony bigger.

Now I can also do things like setting a model state for a BIM so that I can simplify it for consumption in Revit. Here, you'll see I've done some replacement as well as suppression, and I also have some rules around setting the level of detail for export into BIM. Now that I've shown you what can be done in desktop adventure today, let's take a look at what can be done beyond the desktop in Forge Autodesk cloud-based offering.

Going to forge.autodesk.com brings you to our cloud-based developer platform. This platform has all sorts of materials to help you glue together our desktop and cloud-based offerings into single coherent workflows. If we look down, we have specific services around things like viewing, access to the construction cloud, and design automation API. We also have a sample configurator.

So I've uploaded my configurable wall product template from Inventor. You can see here I've surfaced the user parameters so I can do things like changing the stock size, changing the stud spacing, and changing the wall itself, all within a web page. This is the Forge Embedded Large Model Viewer.

And then once I've made these parameter changes, I can update the model, it goes through the design automation API and returns an updated model. I can then extract the bill of materials for the updated model as well as get drawings. See here, this reflects my changes. I can export a PDF.

And I can download things. I can even download a Revit family and open up that configured Revit family in Revit. This allows us to connect the Inventor template directly into Revit through Forge. Resources, including sample code to build a solution like I just showed are available on forge.autodesk.com.

Leveraging Forge, Inventor, and Revit, I want to show you what can be done tomorrow to seamlessly connect the industrialized construction workflows, starting with these highly-engineered product templates in Inventor. Using the Large Model Viewer in Forge in design automation, I'm able to extract all of the assembly and walls in this Revit model in a web browser, and then able to map the Revit elements to the Inventor product template parameters and generate outputs for every selected Revit element in the building.

I can then go to construction cloud and see things like the bill of materials for each Revit element, updated models for downstream consumption, again, for every Revit element, be able to see the specific Inventor variant that was generated for those parameters. I can see it both here in the Forge viewer, as well as take that Inventor assembly downstream for manufacturing. Can also generate all of the production drawings for every element in that Revit model.

And here, for this Revit element, you'll see we've generated two sheets of drawings. You can see we were able to automate, at scale, 319 Revit elements in under half an hour, in a process that would have been both error prone as well as set the project back by days, if not weeks or months. The key to bridging the gap between construction and manufacturing using Inventor product templates will be shown in this example how we can provide a product template that is directly consumable in Revit. This will lead to the Revit designer being able to access all of the input parameters as well as being able to execute the rules so that everything that the Revit designer consumes is fabricatable.

Going back to our balcony assembly in Inventor, I now can publish this to the construction cloud. I can publish my levels of detail. And then I can also create a marketplace or product catalog based on those templates that are published. I can change the parameters, add them to my cart. Now that I have my cart, I can go to Revit and place those balconies in my building.

I'll insert the two balconies that I have, based on the BIM level of detail in my product template, and I'll insert those directly in Revit, and be able to see that in my model. You can see it brought over the right level of detail as well as the right configuration for each of these rooms. Now, I have some other rooms that are smaller and I don't yet have them in my cart.

I can go directly in Revit and make the balcony smaller. Again, select the BIM level of detail and insert that directly in the building. And you can see here, not only did I get the right size, but I got the right panel layout. So I've now inserted something that is directly fabricatable, and I can even go and submit a bid directly for these components.

Now we can deliver a completely connected workflow. So if we look at the gaps between the engineer designing the product template and the installer on the site, we have the owner who influences which products can be used in the project, we have the engineer designing the fully configurable, highly engineered product template. They publish that template to Forge. It can then inform the design, whether that's in something like a product catalog for a non CAD user or a designer directly in Revit.

They can then pass that on to make, for people like the sales engineer, the production manager, the fabricators, working in tools like Forge Large Model Viewer, with their back end tools like SAP, they can do configuration directly in a website, or they can take it to Fusion for fabrication. And then, they can take that directly to the installer in the construction cloud.

So now, there's a direct path back if the installer finds issues that can inform make, it can inform the design, it can inform the product template, or it can even inform the owner to know which products to go with in future projects. And hopefully this shows the power of bridging that gap between construction and manufacturing by moving the fabrication and manufacturing inputs into the design process so that not just the Revit designer, but everyone along the entire chain has access to both a single source of truth and any of the derivatives that come from that.

JUSTIN RICE: All right. Now let's take a look at this connected workflow in action on the Binsky modular carrier. So here, I have an iLogic model of the Binsky modular carrier. I want to go ahead and bring up this form.

And I can start changing the configuration of this model. So I can switch to having no water closet here in the fixture four, I can eliminate, I can switch the water closet and fixture in the fixture two position. You can see right now this is a back-to-back configuration because I've got a water closet in fixture two and in fixture five to a urinal. And so that'll swap out those two components.

Once I have completed my highly-engineered design, I can then zip up that model, take the zip file, upload it to the configurator, select the correct top level assembly, which will be my modular carrier assembly, and upload. That will create a new project in the configurator, allowing me to drive those same parameters in the configurator that I was driving in the iLogic model in Inventor.

All right, so you can now see that that model has been uploaded. You can see the cloud credits that were consumed. And now, I can go in and start driving those same parameters.

So I can quickly switch out and say, I don't want a fixture in location one, or four, and I also want to remove the fixture in position three. And then I'll switch the waste direction to coming out the right side. Click update. Those parameters are then pushed into the model and the iLogic rules are ran based on that set of inputs.

All right. So you can now see my new configuration. In this configuration, I can then go look at the bill of material. Here, I can see all the components that have been included in the assembly. This specific project did not have any drawings, but I can also then go and look at the downloads.

So I could download a zip of the entire assembly. Could also download an RFA. This is going to kick off another process, exporting a file from Inventor, pushing that file into Revit, and making a RFI directly from the Revit worker. And finally, I'm going to take a look at this modular carrier inserted into a Revit project.

So here, you can see a Revit project of this chap modular carrier has been uploaded into BIM 360. So I'm going to go ahead and look at this full assembly in the Large Model Viewer. And I'm going to go to a front view. If I zoom in, I can see instances of that modular carrier have been inserted in this assembly, where they belong within the bathroom, with respect to the entire larger MEP design.

ANDY AKENSON: Now, a quick recap to show how we're bridging the gap between construction and manufacturing. Let's bring it back to our vision, where we really do want to help accelerate the adoption of industrialized construction by connecting design and make tools and enabling a data-driven process. What we've shown, that by starting with a highly-engineered product template Inventor, connecting that to Forge, exposing the manufacturing parameters, you can insert that directly in Revit, connecting the workflows all the way from owner, to installer on-site, and providing feedback all the way through the process, closing the gap between construction and manufacturing. Now looking forward to answering any questions you may have on the topics we covered here today. Thank you so much for your time, and I hope you have a great Autodesk University.

______
icon-svg-close-thick

Cookie 首选项

您的隐私对我们非常重要,为您提供出色的体验是我们的责任。为了帮助自定义信息和构建应用程序,我们会收集有关您如何使用此站点的数据。

我们是否可以收集并使用您的数据?

详细了解我们使用的第三方服务以及我们的隐私声明

绝对必要 – 我们的网站正常运行并为您提供服务所必需的

通过这些 Cookie,我们可以记录您的偏好或登录信息,响应您的请求或完成购物车中物品或服务的订购。

改善您的体验 – 使我们能够为您展示与您相关的内容

通过这些 Cookie,我们可以提供增强的功能和个性化服务。可能由我们或第三方提供商进行设置,我们会利用其服务为您提供定制的信息和体验。如果您不允许使用这些 Cookie,可能会无法使用某些或全部服务。

定制您的广告 – 允许我们为您提供针对性的广告

这些 Cookie 会根据您的活动和兴趣收集有关您的数据,以便向您显示相关广告并跟踪其效果。通过收集这些数据,我们可以更有针对性地向您显示与您的兴趣相关的广告。如果您不允许使用这些 Cookie,您看到的广告将缺乏针对性。

icon-svg-close-thick

第三方服务

详细了解每个类别中我们所用的第三方服务,以及我们如何使用所收集的与您的网络活动相关的数据。

icon-svg-hide-thick

icon-svg-show-thick

绝对必要 – 我们的网站正常运行并为您提供服务所必需的

Qualtrics
我们通过 Qualtrics 借助调查或联机表单获得您的反馈。您可能会被随机选定参与某项调查,或者您可以主动向我们提供反馈。填写调查之前,我们将收集数据以更好地了解您所执行的操作。这有助于我们解决您可能遇到的问题。. Qualtrics 隐私政策
Akamai mPulse
我们通过 Akamai mPulse 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。. Akamai mPulse 隐私政策
Digital River
我们通过 Digital River 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。. Digital River 隐私政策
Dynatrace
我们通过 Dynatrace 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。. Dynatrace 隐私政策
Khoros
我们通过 Khoros 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。. Khoros 隐私政策
Launch Darkly
我们通过 Launch Darkly 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。. Launch Darkly 隐私政策
New Relic
我们通过 New Relic 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。. New Relic 隐私政策
Salesforce Live Agent
我们通过 Salesforce Live Agent 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。. Salesforce Live Agent 隐私政策
Wistia
我们通过 Wistia 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。. Wistia 隐私政策
Tealium
我们通过 Tealium 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。. Tealium 隐私政策
Upsellit
我们通过 Upsellit 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。. Upsellit 隐私政策
CJ Affiliates
我们通过 CJ Affiliates 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。. CJ Affiliates 隐私政策
Commission Factory
我们通过 Commission Factory 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。. Commission Factory 隐私政策
Google Analytics (Strictly Necessary)
我们通过 Google Analytics (Strictly Necessary) 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。. Google Analytics (Strictly Necessary) 隐私政策
Typepad Stats
我们通过 Typepad Stats 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。. Typepad Stats 隐私政策
Geo Targetly
我们使用 Geo Targetly 将网站访问者引导至最合适的网页并/或根据他们的位置提供量身定制的内容。 Geo Targetly 使用网站访问者的 IP 地址确定访问者设备的大致位置。 这有助于确保访问者以其(最有可能的)本地语言浏览内容。Geo Targetly 隐私政策
SpeedCurve
我们使用 SpeedCurve 来监控和衡量您的网站体验的性能,具体因素为网页加载时间以及后续元素(如图像、脚本和文本)的响应能力。SpeedCurve 隐私政策
Qualified
Qualified is the Autodesk Live Chat agent platform. This platform provides services to allow our customers to communicate in real-time with Autodesk support. We may collect unique ID for specific browser sessions during a chat. Qualified Privacy Policy

icon-svg-hide-thick

icon-svg-show-thick

改善您的体验 – 使我们能够为您展示与您相关的内容

Google Optimize
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

icon-svg-hide-thick

icon-svg-show-thick

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。