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Weeding Out Sloppy Work: How to Use Automatic and Semi-Automatic Cleanup Tools to Maintain Drawing Accuracy

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说明

Maintaining drawing accuracy is critical to architecture, engineering, and construction designs. However, due to the complexity of collaboration, encountering inaccuracies is almost inevitable. Research indicates that more than 80% of customers have encountered inaccuracies within drawing elements. If not addressed, these inaccuracies could lead to additional time spent on corrections, or even costly overruns if ignored. AutoCAD software and its associated applications offer batch tools to assist customers in rectifying errors individually or in bulk. This guide will offer a detailed review of the current drawing cleanup tools, outlining their advantages and drawbacks. Additionally, we'll explore possibilities for early-stage error identification to prevent wide proliferation of inaccuracies.

主要学习内容

  • Discover a cleanup toolset to rectify various drawing inaccuracies.
  • Discover specific use cases that require extra attention due to the tool's capacity limitations.
  • N/A.

讲师

  • Kaili Zhu
    Kaili Zhu is an Experience Designer on the AutoCAD desktop team. Since earning her Master's degree in Design Science from Zhejiang University in 2021, she has contributed to the design of several key AutoCAD features, including the Sheet Set Manager for Web, Autodesk Assistant, and updates for AutoCAD for Mac. Besides, Kaili is also actively researching methods for optimizing drawing cleanup solutions in AutoCAD.
  • Nigma Liu
    Nigma Liu is the principal test developer for AutoCAD since 2008. He has involved in many AutoCAD features' development and rich experience in the industry. He was a civil engineer for a long time before entering Autodesk.
  • Jiacheng Li
    Jiacheng Li is a product manager in the AutoCAD team and primarily works on the web application. She used to be a structural engineer and has received education in civil engineering for her bachelor's degree and master's degree. Recently, she completed her MBA at the University of Virginia Darden School of Business. Since joining Autodesk, she has focused on delivering cloud-based solutions for AutoCAD to continue to empower customers with a faster and seamless way to use AutoCAD.
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Transcript

JIACHENG LI: Hello, everyone. Welcome to the class. Weeding Out Sloppy Work. How to Use Automatic and Semi-Automatic Cleanup Tools to Maintain Drawing Accuracy. Thank you for taking the time to join us today.

Click. Before we dive into the details, we want to share a safe harbor statement. If we mention anything related to roadmaps or future development plans, they are just plans, not promises. The development releases and timing of any feature or functionality may change. You should not rely on the presentation today to make purchasing decisions.

Please allow me to introduce our speakers for today's class. Hand it over to Kaili.

KAILI ZHU: Hello, everyone. My name is Kaili Zhu and I'm experienced designer from the AutoCAD team working across both Windows and Mac platforms. With a background in industrial design, I contribute to the design of features like [INAUDIBLE] Set Manager and the Autodesk Assistant and more. I want to thank you for showing interest in our topic and in the next hours Jiacheng and I will share knowledge we learn from joint clean up research. Hope this can help your future work. Thanks, and I will hand it over to Jiacheng again.

JIACHENG LI: Thank you, Kaili. My name is Jaicheng Li. I'm a product manager on the AutoCAD team. I worked as a structural engineer before and studied civil engineering for my bachelor's and master's degree. Since joining Autodesk, I have been working on various solutions for Autodesk, AutoCAD across desktop, web and mobile. I'm very excited to be here with you all today.

Here's the agenda for today's class. We will start with some joint clean up background and then share some data with you. Then Kaili will walk you through several case studies to deep dive into the joint cleanup tools in AutoCAD. Then we will conclude with some key takeaways.

Have you ever found-- I'm wondering, have you ever found yourself spending too much time cleaning up geometry in processions? Or worked with large DWG files clustered with overlapping geometry? And what about manually converting exploded blocks? That's pretty frustrating, right? If any of this sounds familiar, you are not alone. These tedious tasks can take up valuable time that could be spent on more important work.

So we've conducted a survey. In one survey with 410 participants we found out that these issues are incredibly common. Around 85% of users encountered geometry errors in their drawing. And in another survey of 281 participants over 50% of users reported performing cleanup tasks regularly, whether it's consolidating duplicate objects, updating definitions or fixing geometry imprecisions. These tasks are time consuming, but they are key parts of maintaining accurate and efficient designs.

So what are the most commonly used commands for doing cleanup? Let me share some interesting data points about how many of you are using the top drawing cleanup commands in AutoCAD within just one month.

The top use command is the Join command. That was used for 692,000 times. The Purge command came into the second, hit, 664,000 users. And then Overkill command. That one was used for the 48,000 times. These numbers show just how often you are relying on these tools to clean up and optimize your joints, highlighting how essential they are to your workflows.

I hope these resonates with you on how essential it is to use the right tool to save time and maintain an error free drawing environment. Now, I will hand it over to Kaili. She will walk us through the detailed case studies on optimizing the available tools in AutoCAD products.

KAILI ZHU: Thanks, Jaicheng. Next, I will spend about 30 minutes to introduce seven popular cleanup tools that we can use to improve work efficiency. I hope this tutorial can provide you with a comprehensive understanding of AutoCAD existing cleanup capability.

So following the drafting timeline, I will focus on introducing tools marked in black. They are Flatten, Overkill, Drawing, Bconvert, Map Clean, Annotation Monitor, and Purge. The other tools marked in white will be mentioned as supplementary features throughout the introduction. Each tool sharing includes its primary users, system requirements, design goals, and common scenarios. Besides, I will mention key considerations to keep in mind when we use these tools.

The first tool is Flatten. It is an express tool available in AutoCAD, AutoCAD for Mac and all AutoCAD vertical products. As a tool designed to project 3D objects onto a 2D plan while preserving original properties, flatten can help us clean the terrain data provided by surveyors or generate 2D objects from 3D for further design. Next, I will show a demo of how we use flatten to convert a drawing with 3D solids to a 2D floor plan.

This is a floor plan opened in AutoCAD 2025. In the isometric view, you can see many walls with height. However, since we need to work on the 2D floor plan, so all entities should lie precisely on the xy plane. To ensure this, start by setting the current view to either the top view or bottom view. This is crucial because flatten will always project entities on the current view. After that, launch Flatten.

Specify the whole floor plan and choose the option to remove hidden lines. Depending on the complexity of the drawing, you may need to wait for the flatten process to complete. And finally, we will get a clean 2D floor plan.

In the practice, you can see Flatten treats different kinds of objects in different ways. It can fully return the functionality of text and the hatch, but it doesn't retain original blocks. Instead, it creates a new block and appends a flat suffix to the new block name. Regarding to table dimension and emulator, Flatten cannot identify them, so they are flattening results consist of lines and text.

Additionally, Flatten doesn't work on ADC objects. That means it cannot remove elevation from elements like simple 3D surfaces. For a better performance I recommend using Flatten on a small selection of objects multiple times. Otherwise, the process may take a long time and could even cause the product to crash.

To convert 3D objects, there is a workaround we can use too. Click Select to modify objects by type. For example, we can select all 3D solids on a specific layer, then set their elevations to 0 in the Properties palette. This approach is less error prone but can take longer to complete.

Next I will introduce Overkill. Different from Flatten, which works on 3D objects, Overkill is designed to remove 2D overlapping objects of the same type. It can help to clean up unnecessary layers introduced by insert actions or the previous Flatten result. The Overkill result will benefit following drafting since it reduces the chance of snapping to the wrong object.

As a feature that has been public for many years, Overkill is available in most AutoCAD products except web and mobile. Now I will show a demo of how we use Overkill to batch remove overlapping lines in the floor plan.

This is the floor plan of an office building. Although the floor plan appears perfect at first glance, it actually contains overlapping lines that were unintentionally introduced during drafting and should not be there. For example, the balcony section is drawn on an aquamarine layer. When selecting its lines we notice that the number of selected lines does not match our expectations. To identify overlapping linework, firstly we should set the system variable selection cycling to value to selection cycling can help us identify the position of the overlapping lines.

To remove the underlying lines we first launch Overkill and then specify the objects to clean. Overkill offers a rich set of options, but careful attention should be paid to the tolerance setting as it treats parallel lines as overlapping depending on the value. Although the balcony consists of many parallel lines, we don't plan to remove any, so the tolerance value should be zero.

Overkill also has an ignore section allowing users to remove overlapping lines across different layers, line types and more. However, since we are focusing on cleaning a single layer, I will uncheck all the ignore properties. Once confirmed, click OK and overkill can complete the cleanup almost in real time. This is-- [AUDIO OUT]

Although Overkill can handle some edge cases with designated options in the dialog, we still need to be aware of some edge cases that Overkill can handle and some constraints of this tool. Firstly, Overkill can handle some edge cases with the self overlap polyline. It can remove overlapping segments of a polyline by checking the option, optimize segments within polyline.

It can also consolidate partially overlapping lines similar to a joint action by checking the option, combine collinear objects that partially overlap and the option combine collinear objects when aligned end to end. Secondly, Overkill has limitations in identifying overlapping objects. It cannot handle overlaps across different object types. For example, a polyline beneath a line cannot be removed by Overkill.

Another limitation has something to do with the tolerance setting. It is designed to identify parallel lines that doesn't account for angle deviations. As a result, Overkill cannot remove two lines that looks overlapping, but actually has a 0.5 degree angle between them.

The third tool I will introduce is Drawing. Like Overkill, drawing is an established tool available in nearly all AutoCAD products except mobile. It is used to connect to separate objects that meet end to end, even if they are on different layers. Drawing is useful for cleaning up line objects from PDF import or combining a set of lines into a single continuous polyline.

Next, let's look at a demo on how we further clean up the Overkill result by converting lines in the Overkill floor plan in polylines. Let's continue with the balcony section. After running a thorough Overkill on all the balcony objects, we reduced the line work to 130 lines. To further optimize we can convert all connected lines into polylines. To do this, first we should launch Drawing and then select the entire balcony line work. After confirming the selection, 124 lines are successfully converted to polylines, while six remain excluded for some reason.

The balcony now consists of 22 objects. If we take a closer look, we can find that Drawing does not resolve the line overshot at the connection point. To fix this, we launch p edit. Choose the multiple option and select both polylines. We then use the Drawing option and specify the tolerance by selecting the start point and the endpoint of the overshot. This can connect the vertical polyline to the horizontal polyline successfully.

There are several things we need to pay attention to when using Drawing. Firstly, Drawing only works on line objects that connect end to end. Unlike overkill, it doesn't have a tolerance setting. Secondly, the joint result preserves the original object type as much as possible. For example, two collinear lines will merge into a single line, while a line collinear with a polyline will convert into a polyline.

An event similar to Overkill, which returns only the topmost object, the joint operation adopts the properties of the topmost object for all. Finally, as mentioned in the demo, p edit is a workaround for joining line objects, but it first converts all selection to polylines, so the p edit added result will always be a polyline.

Now let's introduce a new member of the cleanup family, Bconvert. This tool can convert identical instances throughout the drawing into blocks whenever needed, and offers full support for Windows product. Next, I will show a demo of how Bconvert detects and repairs exploded blocks in the floor plan.

Let's shift our focus from the balcony section to the workspace layout. This area includes duplicate desks, meeting rooms, plans and other elements drafted as blocks. To find and clean any exploded blocks we can use the block converter tool to locate them by type. For example, to find exploded chairs, we first launch Bconvert and specify an existing chair block as the reference. Bconvert will then search the entire drawing for instances that match the chair reference.

After the search completes, it highlights all detected instances on the canvas. After we confirm all the selected instances, a block convert dialog will appear guiding users on how to convert the detected objects. You can convert them to an existing block in the current drawing, a block from the library, or create a new block. Since a block chain already exists, we select the option to convert the detected instances to the existing chair block and on the same layer, which is layer 0. As a final step, we need to manually adjust the block position to align with the instance representation.

Once completed block convert automatically adjusts the diverse orientations of the instances. We can repeat the process with plans, tables, et cetera. Let's take some time to delve a bit deeper into this feature. By design Bconvert scans the entire drawing to match the selection and identifies identical instances, whether they are blocks or non-blocks. We can add or remove instances to the initial step of the process. The Bconvert dialogue includes a suggested block section. It is powered by AI and can recommend existing blocks based on their similarity to the selection.

AutoCAD 2025 has another feature to deal with exploded blocks and detect. It is under Tech Review, meaning that the feature is still updating. Different from the Bconvert, Detect only searches for non-block instances that can be converted into blocks. So with a single detect action, multiple new block candidates may be identified. It is also powered by an AI model and currently it works best with architectural objects. For both Bconvert and Detect, badly drawn instances may be excluded from the detection due to its dramatic difference from other identical instances.

OK, after discussing so many cleanup tools on geometry objects, I will introduce something different. The Annotation Monitor. It is designed to search for dimensions that lost connection with its origin. While we can know if a dimension is associated by checking the Properties palette or hovering over a specific dimension, Annotation Monitor allows us to see exactly how many disassociative dimensions exist and their locations at all.

Annotation Monitor enables us to correct inaccurate dimensions that may arise from version 4 back or the object explode. Next is a demo on how we fix dimensions with Annotation Monitor.

If dimensions have already been added to the drawing, such as this change dimensions for the exterior walls, it's important to verify whether they are linked to regions known as associative dimensions or only associative dimensions will automatically update when regions are modified. Annotation Monitor is turned on by the toggle on the status bar. When it works, all these associative dimensions are marked with a yellow badge beside them. By clicking the badge, we get access to the tile associated action. This allows us to reassociate the dimension by specifying the origin one by one.

Here we need to notice some system variables in AutoCAD. Besides the UR access on the status bar, we can also turn on the tool by setting system variable Annotation Monitor to visual variable one. When drafting new dimensions, we should pay attention to the value of system variable dimension associate. If it's either zero or one, new dimensions are by default, not associative.

Last but not least, users sometimes override the values of associative dimensions for convenience, which the annotation dimension cannot detect. However, there's an express tool called Dimension Associate that can revert this associative dimension values.

When talking about cleanup tools, we must mention Purge. As you know, Purge can remove unused data and styles to reduce the file size. It is available in almost all AutoCAD products except mobile. When working with frequent insert or copy paste, unnecessary layers, blocks and styles can easily accumulate in your drawing, and the Purge can help to clean up this data.

The following demo will show how we utilize the Purge dialogue to clean items. When we experience poor performance and notice an excessive number of definitions in the drawing, such as hundreds of block definitions, layers, textiles and dimension styles, removing unused definitions can help. Start by launching the Purge command. It will display all purgable items in the initial dialog. These items are categorized by type with individual definitions listed under each category.

Before confirming, we should deselect any definitions planned for use in the future but are not currently needed, and make sure to confirm each item to be purged in Option is unchecked, otherwise we will be flooded with hundreds of dialog boxes asking if we want to delete some item. Once everything is set, click Purge. Check the items to remove unnecessary data.

Sometimes a single Purge won't remove everything as definitions may reference each other. By checking the option, Purge nested items, we can eliminate the repetitive purge steps. To maximize data removal we may continue purging until no purgeable items are left.

Next, reveal the non-purgeable items. Various reasons can prevent an item from being purged. We can learn about this through the messages in the right panel. For example, the chair block has 33 instances after we use Bconvert so it won't be purgable. We can investigate its instances by clicking the Select object control. If we do one or two purge the chair block, erasing all its instances, it's necessary before running Purge again.

But that's not what I wanted to do here. Press enter to return to the Purge dialog and we can continue reviewing the other definition instances. When we-- [AUDIO OUT]

The Purge dialog shown in demo doesn't list all purgeable items. The following are popular ones. DGN linetype. It is covered in the option, Orphaned data. Registered application. It is not accessible through the Purge dialog and should be removed with the command version. Invisible AC object. The invisible AutoCAD Architecture and Civil 3D custom objects can be removed by command PURGEAECDATA.

External reference. Purge cannot clean external reference, but some third party tools can. We need to clean up the respectively if necessary. With Purge I also want to delve deeper on its Purge nested items option. Assume a drawing has a using the style field label. You can view its usage in the dialog right panel. And this [INAUDIBLE] style uses a block named label.

If we remove all emulator references, the view label style, it would become purgeable and appear in the purgeable items tab when we run Purge again. But the blog label is still in the non-purgeable items tab because it is still referenced by the emulator style. Tracking the option Purge nested items can remove both view, label, style and label block at one time. So it is possible that one Purge operation cleans items from both purgeable items tab and non-purgeable items tab.

Now comes the last tool in my introduction. Do you remember the line overshoot issue that Join cannot handle in my previous demo? This is where Mapclean comes into play. Basically, Mapclean is only available in Civil 3D and maps 3D. It is designed to simplify line objects in map data by resolving minor linework issues that are not often too subtle to detect visually. In the following demo, we will see how Mapclean can be used to correct linework errors in a sample floor plan.

In the Join demo, we use the p edit to create a line overshoot issue. However, in Civil 3D and map 3D there is a specialized tool called Mapclean designed to handle similar intersection errors. I've marked the intersection arrows with red circles throughout the drawing. To fix these arrows we start by launching Mapclean. A dialog box then appears prompting us to specify the objects to fix.

Let's select the lines that contribute to this great region and press Enter. With Mapclean, we can also limit the fix to specific layers, but in this case, the All option will suffice. Next, we move on to specify the types of arrows we want Mapclean to search for by transforming them from the left panel to the right. Since our focus is on removing line overshoot, we will first select break crossing objects and then erase dangling objects.

The tolerance of erase dangling objects defines the maximum object length to be considered for removal. If we don't know the exact length, we can specify it by selecting a start and endpoint on the canvas. I will add some buffer to the tolerance instead of measuring the exact length of the overshoot segments in case the removal fails.

Back in the Mapclean dialog there are two modes, Automatic and Interactive. While the automatic modes quickly resolve arrows, the interactive mode allows us to reveal each detected arrows carefully. So I will choose the Interactive mode. We then click the Finish button. Then a new dialog will appear listing all detected arrows by type. By activating each instance, we can either fix, remove or mark it before moving on to the next one.

Since I don't want to break the great lines into smaller segments, I will only fix intersections at the edges and remove the others. The canvas will guide us through each arrow.

Once we've reviewed all the instances, we can click Close to accept the changes. Now, the grid no longer has any line overshoot. Mapclean can be a powerful tool when we know how to apply the correct cleanup actions to a selection. Therefore, understanding what each cleanup action does is essential.

There are 11 types of geometry errors available in the Mapclean action port and I will walk you through each one. Delete Duplicate. It erase duplicate linear objects, points, blocks, text and m text while keeping the topmost one. Erase Shot Objects. It can erase open line objects whose length is within the tolerance. And Break Crossing Objects. Its break line objects at their intersections, regardless of their type.

Extend Undershoot can snap open line objects to another line object within the tolerance radius. By default, it breaks the snap to line by default. Append Intersection. It extends to open line objects that would intersect if extended along their natural path to their projected intersection point. And the Snap Clustered Nodes. It snaps multiple nodes that are near the same location within a specified tolerance radius distance to a single location. As you can see, the last three actions can handle some line undershoot issues.

Continue from the previous slide. Dissolve Pseudo Nodes. Convert open line objects that connect end to end, linking two objects into a single polyline. Erase Dangling Object can erase open line objects with at least one endpoint that is not shared by another line object. It works best to following the action break crossing objects. Simplify Object. It can remove all interior nodes that fall within the specified tolerance [INAUDIBLE].

Zero-Length Object [INAUDIBLE] erase open line objects whose start point and endpoint are at the same location or whose endpoint is missing. By the way, Purge also has this ability. And the last one Weed Polylines. It can remove or add vertices based on distance reading factor or angle weeding factor. It makes sure vertices spread evenly in the polyline.

With so many cleanup actions, Mapclean respects the order and tolerance defined by the user. For example, in the demo, we specified the sequence as first breaking crossing objects and then erasing dangling objects. On a small scale of selection, sometimes scanning the entire drawing can be challenging as it will be complex to determine an effective sequence of cleanup actions.

Another interesting fact is that the Remove option available in the Interactive mode. It only works in the current session. So next time you run Mapclean and following the same cleanup settings, the remove the arrow will still be detected. OK, this slide wraps up my introduction to the cleanup tools. I hope the presentation didn't make you feel boring, and you've learned something new to help with your work. Next I will hand it back to Jaicheng. She will wrap up our class contents.

JIACHENG LI: Great. Thank you so much, Kaili. So as Kaili mentioned, you can see on the left hand side, we have introduced all the tools you will need for your join cleanup. So here are some takeaways to keep in mind while you're using the tools.

First, know how and know which tools to use and when. It's essential to ensure you're selecting the most effective tools for the tasks at hand to streamline your workflow. Second, understand the limitations of each tool. Being aware of what a tool can and cannot do will help you avoid unexpected results and keep your work on track.

Lastly, correct arrows promptly. Addressing mistakes early on prevents bigger, more costly problems down the road. With these strategies, I hope you can optimize your efficiency and improve the quality of your work.

So that wraps us up our content. Next, I want to share with you a great opportunity to join AutoCAD inside the factory event, which is new this year. So in this virtual event, you get a chance to explore new features. So be the first to experience the new features before it's released in its beta version.

And then you get a chance to also meet directly meet with the product team, including product managers, designers, and developers, so that you can get all your answer, all your questions answered. Lastly, your feedback is really important to us. We want to make sure we hear your voices so that you can share your ideas and help us shape the future of AutoCAD. So if you're interested in this opportunity, please scan the QR code and sign up. So we will notify you shortly. Thank you so much.

KAILI ZHU: Thank you.

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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

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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

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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。