AU Class
AU Class
class - AU

Discrete Event Simulation and Its Role in Integrated Factory Modeling

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

An integrated factory model is a great tool for space planning in literally any discipline. However, success is not measured only by the ability to fit a process into a site, but also by understanding its capabilities. By employing discrete event simulation, we can make sure that the changes planned or the new process being implemented will be able to handle current throughput needs and develop an ROI. In addition, we can model for the future, and make sure we can meet the peaks and valleys of production as required. In this session, we’ll provide the ability to measure and predict throughput and manufacturing efficiency in your layout model—in AutoCAD software. See how applying these methodologies and workflows can help your organization make better decisions faster in regards to literally any process. See how your process will perform based on your criteria—and get solid, actionable data to reduce risk and maximize profits.

主要学习内容

  • Learn about the benefits of discrete event simulation for manufacturing and AEC customers.
  • See how an ROI can be developed from data gathered.
  • Learn how to provide strong metrics to support a business case.
  • Learn how to provide both 2D and 3D-animated process models using AutoCAD, Inventor, and Autodesk Forge—with one button click.

讲师

  • MICHAEL jolicoeur 的头像
    MICHAEL jolicoeur
    I have been an agent of change in manufacturing process for over 25 years - utilizing technology to improve manufacturing customer's processes - helping make them more competitive and more profitable. I worked at Autodesk for over 22 years and specialized in manufacturing workflows - including expertise in Inventor, AutoCAD, and in particular the Factory Design Utilities.
Video Player is loading.
Current Time 0:00
Duration 27:20
Loaded: 0.60%
Stream Type LIVE
Remaining Time 27:20
 
1x
  • Chapters
  • descriptions off, selected
  • en (Main), selected
Transcript

MIKE JOLICOEUR: Hello, everyone. I'd like to welcome you to the discrete event simulation and its role in IFM or integrated factory modeling. My name is Mike Jolicoeur. I am a director of the Autodesk relationships for ProModel, which is a division of BigBear.ai.

So let's go through the class goals for the next 90 minutes. So just to make sure that you're in the right room, the class ID is IM501235, and here's the goals of what we're hoping to go through.

First, we want to make sure that you understand the benefits of discrete event simulation for manufacturing and AEC customers. We want to see how an ROI or Return on Investment can be developed from the data that is gathered from the simulation.

We want to be able to provide strong metrics to support a business case and also provide both 2D and 3D-animated process models utilizing AutoCAD, Inventor, and Forge with one button click.

So Autodesk tools provide a great foundation for building a digital twin and familiar tools that you've probably used for layout today. ProModel provides the ability to turn your CAD layout documentation into a powerful tool for throughput simulation, helping customers get the best return on investment for their process changes and in turn reducing costs of manufacturing of their products.

The Autodesk toolset provided in the product design and manufacturing suite does a great job of streamlining the layout process for space plane. The factory design utilities make it easy to transition to 3D and reap the benefits it provides, but the tool set lacks in regards to process planning.

That's where ProModel enters the picture. We provide the ability to test and evaluate design ideas and allow users to make the best decisions based on their criteria for success right inside the AutoCAD you use today for spatial layout.

In every project, large or small, there are three contributors to the design. Technical building equipment represents the connective tissue between the building and the production line. The building may represent either a new greenfield site or more commonly retrofitting to a brownfield site, or a combination of both of these. So hugely important in regards to successful installation of a new production area, this is not our topic really for today.

We are focused today on the production planning leg of the workflow. Spatial consideration is very important, but equally important, if not more important, is the performance of the process. Being that it is right sized for our production goals. That it delivers the correct amount of products for the lowest cost, and that it is agile in nature, allowing new products to be added without upsetting the balance of what is currently being produced.

A valuable tool for validation discrete event simulation is really nothing new. It's been around in one form or another since Henry Ford role Model Ts off the line. In fact, ProModel has been delivering PC-based simulation solutions for over 30 years to thousands of customers worldwide.

Discrete event simulation inside of AutoCAD, however, is new. The ProModel consulting team will tell you, over 95% of projects they delivered started with an AutoCAD layout. A lot of effort had to be expended to utilize a drawing in the ProModel environment, and for that matter in any other discrete event simulation tool that's out there.

So for that reason, ProModel and Autodesk teamed up to provide an easy-to-use efficient tool set that runs inside of the AutoCAD used today for layout. This new tool set helps build the foundation of an integrated factory model that is much more than a drawing that represents basically. The CAD model now becomes a powerful enterprise decision making tool.

So what exactly is process simulation? And what does it do? Well, the short version of it is it's a digital environment for experimentation, for validating ideas, or for improving your process either in existing production situations or completely new design ideas. It allows no risk experimentation with the process design ideas inside of the AutoCAD you use already today.

It's an easy to understand environment that ties your CAD layout to your process timing data and allows design idea iteration to get to the best answer. The data is the yin and yang of the process design.

If throughput can be achieved but it won't fit into the space allotted, that's no good. And if the layout fits great into the allotted space but it can't deliver the required products in the specified amount of time, it's also useless. So we have to have both to have really good and successful layout.

So ProModel provides time-based systems analysis. It mimics the operation of existing or future process for the purpose of understanding and improving that system. This also allows the ability to compress time. That is, we can simulate a year's worth of production in minutes and be able to see where the problems are.

Many times production issues in regards to throughput don't reveal themselves right away, and it can be challenging to find them without these tools as there are many interdependencies to track, which ProModel does for you.

So we also consider real world factors, one being variability and task times. We can account for variability and averages over multiple runs of a line to get the most accurate representation interdependent events. So we can figure out and identify where bottlenecks occur and figure out what is really causing them, not just what you think is causing them.

Resource availability, a major contributor to process problems. And it's nearly impossible to determine using spreadsheets. And it's easily understood in this environment. Also calendar factors, things like holidays, shift changes. Planned and unplanned downtime can be factored in, as well as maintenance timing studies and manpower needs, for example.

Broken down, there are three steps we follow for analysis. We first visualize the process. This is diagramming, modeling, and reporting what you see and the flow on the screen in process animation. We also then analyze the results.

So how do I increase service levels, determine resource requirements, or reduce costs, decide on the dials or levers that we're going to use or settings, in other words, and run scenarios so we can try different things and get different results? And then lastly, we optimize. This allows us to experiment, test, and explore in a risk-free environment. And it quantifies our successful KPIs and what we're looking forward to get out of the simulation.

So visualize. Let's go a little deeper on that. Within the AutoCAD environment, we can see the process run based on the criteria we set, conveyor system bottlenecks, process chokepoints, and spatial problems identified right in the AutoCAD environment.

Analyzing, so from here, we get configurable dashboards that allow us to measure against the key performance indicators that we deem most important, be that the takt time, part cost, or labor and resource utilization, or all of the above.

The chart tools are directly tied into the model so as design ideas are explored, the data dashboard updates as well. From the data provided by analysis, we can now experiment with the process via scenarios, pulling levers in the model to see how it behaves with different criteria being applied to that model. The dashboards allow us to then compare the scenarios against each other to help implement the best case that will offer the correct throughput at the best cost.

So the tools in the factory design utilities excel in helping customers avoid excessive cost and risk and changeover. That is making sure everything will physically fit into the space allotted and that the equipment interface is physically as well. This helps avoid change orders on installation which can drive project costs up substantially and also puts startup at risk.

What it does not show or does not do is allow planners to see how this plan change will affect the cost of the products being manufactured or the ability to confirm that the design will meet the required throughput to meet demand both in current state and in the future.

That's where ProModel comes in. We allow those that plan change, be it for new products, process improvement, or automation, or bringing acquired companies into the corporate fold, to fully understand if the process that is being designed will meet the production needs and be cost effective, either lowering the cost of manufacturing or allowing more manufacturing agility.

The combination of these tool sets allow customers to build out facilities digital twins that can be used over and over again to test ideas before committing any capital to the projects. The Autodesk ProModel solution reduces cost and risk not only for installation of the new process but operational risk for producing the product throughout its lifecycle.

We'll give you a brief overview of the user interface. A straightforward, easy to use, navigatable interface makes the tool easy for new users to master really fast. And experienced users also have the ability to apply macros, logic, and other advanced tools easily to further refine the simulation outcomes.

A tab is added to the AutoCAD ribbon containing all of the command structure necessary to create a simulation. Browser panels provide detailed information and interactive feedback in regards to the simulation being studied.

So let's see the products in action. Our first example is validation of an engine assembly line. Our criteria-- excuse me-- our criteria for success is listed here. We need an average throughput to be able to be met, but in addition, we need to be able to meet demand spikes as required.

Furthermore, we need to make sure that this fits into the space allotted and understand how the feeder products get to this line. This represents the intended flow of the line, timings and numbers based on past experience.

Note also that each of the times here are deterministic. That is, they have an absolute number. They don't have any variability in them. As humans are doing the work here for assembly, the chances of repeatability of timing is pretty low. That's why ProModel allows users to include process time variability into the model, increasing accuracy.

We find that when we build a model based on the existing flow that the customer gave us, we are typically within 5% of what the customer was seeing in the real world.

So as shown here, the AutoCAD layout can now be used to analyze our manufacturing design idea. The browser interface reflects the flow of the product through the line as seen here. We can see live how products will flow through the line. This will help designers complete tasks like rightsizing the line side AGV feed robots, as well as see where a potential bottleneck may be.

We can also gain a better understanding on how workers are traveling and help remove nonvalue added work and travel, as well as making sure we are properly staffed for the line.

Because we're using AutoCAD as the base and the CAD drawing is the scale, we can get distance travel for, part, material handling or workers, which are linked. Meaning that if we make a change to the drawing, the distance is update accordingly, reducing the chance for costly errors.

We can also apply scenarios which have different speeds and settings for the line and see what works best for our needs. Conveyor speeds, process speeds, manpower and staffing, all of these can be tested in the scenario manager. From here we get not only the dashboard output but the ability to show the simulation in 3D.

By clicking the Inventor button in the factory design utilities ribbon, the 3D representation is generated, making it easier to communicate our design intent with others. This can also be animated in 3D using ProModel's 3D simulation viewer, literally one button click. The easiest in the industry.

Using CAD visuals and the configurable output viewer, we can see where the problem lies. The station where heads are bolted on to the engine. Panning, zooming, and rotating the view while running are all supported in the viewer, allowing us to focus in as required.

Current design has the operator torqued in each bolt separately, which is time consuming not to mention error prone. We propose adding a multi spindle digital torque nut runner to the line, reducing cycle time and the chance for errors. However, this piece of equipment is around $259,000 US, which we will have to justify.

Scenarios can then be leveraged in the output viewer and make it simple for even nonCAD-oriented personnel to experiment with different configurations. The output viewer lets us clearly see problem areas represented in magenta for black processes, green for running, yellow for waiting, and blue for idle. Red representing downtime. The Throughput tab allows us to see that we were able to produce 12 more engines in two shifts.

So as we can see, we're able to validate space claim in 2D and 3D and validate that our line will produce more engines per shift, yielding 12 more engines per day based on the data that we had input into the simulation. It's projected that our profit on each of these engines produces around $984 per engine.

The estimated cost of adding a multi spindle nut driver to the line is around $245,000. Based on this, we can extrapolate an ROI of 20 days, giving confidence that the investment made in the equipment will pay back.

Moreover, you can reuse a simulation over and over again to test for different scenarios, process changes, or new processes based on this process. Or add more criteria to even further refine the process. Or to look at the process running over 16 months and see what the benefit over time is, including things like shifts, downtimes, and manpower constraints.

We can try other criteria as well based on the findings that the simulation provides, all in an environment that allows us to test these ideas before committing any capital.

Let's take a look at another example. A process retrofit that we've been trying to accomplish for over 30 years but always run into a roadblock when we reveal the price tag to make that change.

Sustainability is becoming a critical part of business decision making due to the cost of energy as well as being better to the planet. In this case, we'll use this to our advantage to sell this project to upper management and the financial controller.

In this example, we have a customer that is using a 1940s developed manufacturing process reliant on old technology machine tools that take a long time to change over and a natural gas fired heat treating process, which consumes a lot of natural gas and outputs a lot of carbon dioxide.

In addition, a substantial amount of space is required for the ovens, which, of course, needs to be climate controlled and electrically powered as well as maintained. Also in consideration, change over time.

When we originally commissioned this line, a 4-hour change over time for the analog bar feeding machines was acceptable as we had only six product variants. Natural gas was also inexpensive to provide fuel for the ovens that must run at 1,500 degrees Fahrenheit 24/7. Otherwise, we risk damage to the fire break linings of the ovens. Of course the financial controller says what he's said for the past 30 years. It works. The machines are long paid for. Let's just keep using it for another year.

Well, in today's production, we now have over 80 different variants of that art. So to offset change over time, we manufacture extras of each part, which becomes inventory. So this increases cost and promotes waste, both in space and old inventory that may or may not be used.

By using modern tool sets, we can use both spatial data and throughput data to our advantage. And in this case, factor in how energy costs can not only help us make the parts at higher quality and a lower cost but also reduce the carbon footprint, which may help improve the bottom line more through tax incentives for green initiatives. We can further reduce risk by using 3D layouts to ensure seamless installation and commission of the line.

Let's have a look at the tool in [AUDIO OUT]. Here we have a representation of current space. Analog screw machines, older three axis machines, and a gas fired heat treating process that requires its own building and also requires an automated guided vehicle to haul parts back and forth for construction process.

As earlier stated, these screw machines are not CNC. They're difficult to load, maintain, and takes a long time to set them up. Our design requires us to change only one part of the line, the beginning portion of the process, and eliminate the need for the gas fired heat treating ovens.

In the same drawing, we have a representation of the proposed process. We can tell ProModel to compare these two different scenarios. In this case, the current state being the baseline and our proposed future state. It's understood that a fairly-sizable investment needs to be made to modernize. So our goal is to show that the cost justified or the cost is justified for better line flow and reduced energy consumption.

We can start the simulation, and we'll see both systems running and running their parts based on the schedule that we provided. We're also tracking energy consumption on each machine and comparing the baseline against the proposed state.

In addition, we can see the simulation running in our 3D model representation or integrated factory model. The building that's shown in this view is a Revit model provided by our building design contractor, and is linked into the model.

If the building design changes, we'll see the update automatically in our 3D model as well as the 2D model. This prevents pollution issues when building or MEP changes are made, which, if they are not caught, can put the installation schedule at risk. We can also see that the current proposed models are displayed and run in 3D, making it better for communication of our design intent.

We also have a data table in the AutoCAD environment that's providing feedback on the line performance based on our criteria. We can see that a substantial energy savings is realized, and a dramatic reduction in carbon footprint is also realized. We also get the data dashboard that tells us all we need to know in regards to cost throughput and manpower needs.

So from here, we can see the summary of all of the operations that are happening, and we also have the ability to look at each of the operations as compared to each other.

So let's recap the results. With a sustainable, friendly workflow, not only do we consume 65% less energy, which reduces costs and has positive tax opportunities, we drive down the cost of the parts and produce more parts with less, and impressive 73% reduction in energy costs per part, which in turn reduces the production costs of each of those parts. This doesn't include the benefit of unneeded inventory, but that could be measured as well to further build out our case.

Also, 69% less carbon dioxide getting released into the environment to the tune of nearly 500,000 pounds of carbon dioxide reduced each year. With a sustainable, friendly workflow, the extrapolated benefit would pay for two of the new machines in the first year. Our outcome is a well supported, well documented reason to change that finance people can't argue with.

Last example is a logistics study. So this customer built in four lines into their new distribution center, and we're currently using only three of them. When they turned on the fourth line because of an increase of demand, the outcome wasn't quite what they expected. They were having trouble determining where the problem was, and they were considering adding more equipment or expanding space based on past experience.

So we worked with the customer, and we built out a simulation of the process, both the as is state and the new state running the fourth line. We were able to determine from the data and the flow the new line was feeding the system at two faster rate, disrupting the flow of the existing system. In short, adding the fourth line did the exact opposite of what they expected. It slowed the system down. It raised costs due to overtime being needed to keep up.

From the data and by watching the simulation, we can see where the problem lies, and we have a good idea on where to start for correcting this problem. According to the simulation, the proposed change gets rid of congestion, allows the entire line to flow efficiently within a standard 40-hour workday, or work week, I should say. So as we can see, the congestion is now eased in here, and we have a smoother running line.

Let's take a look at it running actually, and you should be able to easily see the difference. So the change in the design of the pellet feed into the warehouse was a simple, low cost change as compared to the other options of building expansion and equipment additions, which in reality probably wouldn't have solved it.

As we run the current against the proposed, it becomes obvious where the problem is. If you look at the left side of the screen, you can see that the conveyor is backing up in the Azure simulation. The proposed change, which was simply a change to the conveyor speeds and smarter feeding into the system, alleviated the backup and it solved the problem.

By applying the entire solution, cost savings and design confidence can be assured not only in the installation phase but also validation that the design will meet production output goals with financial information to back it up. In all cases, we proved our ideas with clear, actionable data that can be used over and over again for testing new scenarios of production.

By applying the entire solution, cost savings and design confidence can be assured in not only the installation phase but also validation that the design will meet production output goals with financial information to support it. We have complete design confidence.

So would you like to know more about the ProModel solution and how it interfaces with the AutoCAD tools that you're using already today? Well, come over and see us over at booth 220. We have consulting staff available to answer further questions.

We are also going to be having special show pricing for ProModel, and that's where people that show up at the booth with a coupon. And we can explain more of how that program works to the people that come. And reseller partners are also available to provide software and training. In fact, some of these reseller partners may already be the partner that you're working with.

I'd like to take-- I would like to thank you for your time and attention. Hopefully, you found this to be a useful set of tools and a useful workflow to help you and your company be able to save money and make things a lot more efficient.

______
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。