AU Class
AU Class
class - AU

100% Utilization: The Cutting-Tool Conundrum

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

Underutilization stems from a variety of reasons, ranging from simply being uninformed or unaware, to misapplication while attempting to maximize existing cutting tools. The biggest area for improvement is the optimization of cutting tools, which can be done by paying closer attention to the various other manufacturing technologies at hand. Machine tool capabilities, materials being machined, and other manufacturing technologies—such as CAM programming abilities, high-pressure coolant capability, fixturing, small spindles (such as driven tools), and the like—should all be considered and used. No matter the reason, even the smallest of companies now have tools and technology at their disposal to assist in making better cutting tool choices while considering the manufacturing technologies. A lot has changed recently in the world of manufacturing, and cutting tool production is no different.

主要学习内容

  • Learn how to increase manufacturing throughput.
  • Learn about reducing defects and non-conformities.
  • Learn about reducing resource consumption.
  • Learn how to improve quality and reliability.

讲师

  • Tom Raun
    Thomas Raun is Chief Technical Officer at ISCAR USA. Tom has 31+ years of manufacturing industry experience. Tom joined ISCAR in 2003 and has performed various roles focused on project and product management, while engaging with manufacturing companies throughout the USA to improve CNC machining processes through implementation of cutting tool technologies. In his current role, Tom oversees a team of product and industry specialists responsible for developing and articulating cutting tool application strategies that maximize cutting tool utilization and drive productivity improvements for the many manufacturing companies served by ISCAR. Tom achieved the highest certification in Lean Six Sigma (Lean Six Sigma Master Black Belt, LSSMBB) and has completed coursework through Villanova University related to Lean Six Sigma and Strategic Organizational Leadership. Specialties: Process Improvement and Project Management (Lean & Six Sigma), Cutting Tool Applications
Video Player is loading.
Current Time 0:00
Duration 37:53
Loaded: 0%
Stream Type LIVE
Remaining Time 37:53
 
1x
  • Chapters
  • descriptions off, selected
  • en (Main), selected
    Transcript

    THOMAS RAUN: Hi. Welcome to 100% Utilization-- The Cutting Tool Conundrum. My name is Thomas Raun. I'm the chief technical officer for ISCAR USA, and I'll be speaking with you a little bit today about cutting tools impact on productivity, and the things, or some things that we can do or be mindful of when we're trying to improve productivity of a machining process, and overall manufacturing processes.

    Just a real quick comment on this safe harbor statement. I'm here today with Autodesk, and we're looking at things that we can do together to try to be more productive in programming. We'll be talking about some things that we hope to develop together, but obviously things change, initiatives change. But I think you'll see some good things from the two companies working together in the future. But just take today's presentation as a look to the future on some of the aspects that I'll touch base on, and we'll look forward to bringing some innovative, productive solutions to you in the market in the near future.

    So, 100% Utilization-- Cutting Tool Conundrum. We'll talk about three areas-- overall equipment effectiveness, the cutting tool productivity aspect, and looking at that, the cutting tool from the equipment effectiveness perspective. And then we'll look quickly at sustainability in terms of cutting tools, and just try to give you some thoughts on things that can be done to be better stewards of the environment, and to better utilize the technologies that you're investing in.

    So overall equipment effectiveness, or OEE, it's about measuring productivity. A lot of times, the main focus is about measuring the productivity of machine tools. Companies look at the machine tool as the hub of the manufacturing process, for the most part. So it makes sense to measure how these machine tools are performing.

    And to do this, they're looking at how much time is available-- and we all have the same amount of time available-- how those machines are performing within that given amount of time, and then they're looking at the quality aspects of the parts that are coming off the machine. And so you take all of that into consideration, and you come up with a percentage.

    And, just food for thought, world class performance in this area is considered 85%, and most companies are not at that level. They use that as a goal to try to achieve in their measuring processes, and trying to improve. But 85% being world class, we wanted to take a look and see how that goes when it comes to the cutting tool, and measuring cutting tool productivity in terms of that piece of equipment, and its effectiveness, and how it can impact the overall productivity of that machine tool.

    So when you look at a machine tool, and programming the machine tool, machine tools carry a lot of cutting tools, and the cutting tools are-- they have different design, different attributes that allow them to be more productive than others. But the main person in control of that is that picture towards the bottom left with those people in front of the computer screen, maybe on a CAM system. They're the ones that are making the choices, looking up the information, and they're the ones that are really driving what goes on with that cutting tool in that machine tool.

    So when we look at what they have to do, they have to take into consideration what I like to refer to as the metalworking universe. And what is their metalworking universe? So when you look at what they're taking into consideration when they program a cutting tool, it's the machine. It's the fixtures, the material, the coolant, considering-- and there's many others that they have to consider. These are the main factors in what they're considering on how they program a tool.

    But if you look up at the top left, my estimation, and many in the industry-- the cutting tool industry's estimation is that, do you ever take a little bit-- there's about 50% utilization on a cutting tool. And that sounds really poor, and it is because cutting tools are perishable, and they wear out fairly quickly in terms of all the other manufacturing technologies that are in play in a given process.

    So to really get full utilization out of the tools, and use the carbide, or whatever the composition of the cutting tool is wisely, it makes a lot of sense because you're paying for it, and they're wearing out quickly. So we want to do as much as we can to make sure we're as productive and increasing utilization to maximum levels.

    So what is the utilization conundrum that I speak of? There's misutilization and there's underutilization. A lot of times, day-in and day-out, week-in and week-out, as someone who's been focused on cutting tools for many years-- over 20 years now with ISCAR-- we see misutilization and underutilization so much. And let me just briefly give a definition of what that is.

    So misutilization, it seems fairly obvious, but some of the things that we're talking about is using the incorrect tool for an incorrect material, or choosing a tool just because it's the tool that's available, and maybe not the best suited for the application. It sees obvious low-lying fruit type opportunities, where if we just took a step back, took some time to think about it, would we really use that tool? I'll use a kind of a prime example of this.

    Maybe you're a company that machines aluminum, and also ferrous materials. So you have a lot of cutting tools that you use to machine aluminum productive, and you get a job in that's for ferrous materials, and you think, I'll just use those same tools, or a lot of those same tools to machine your ferrous materials that you're using in aluminum. And they don't hold up as well, and you have to pull back on your cutting parameters. And the next thing you know, you've utilized or used a lot more tools than you think you would have used.

    And conversely, if you're in a shop that does a lot of ferrous materials, but then you get that oddball aluminum material job, and you try to take that same end mill or drill that works well in the steel, and then you apply it in aluminum, and the next thing you know, it didn't work, maybe not even for a few seconds, and maybe the material galled up in the flutes or the gullets of the tool. And then, when that happens, it's game over, usually. The tool breaks. So that misutilization, it's very common, and we're trying to find the right tool for the right application, and help you do that in a productive way.

    Now, underutilization, that's also a big problem because if you're underutilizing something-- I don't care what it is. Anything that you purchase, if you underutilize it, you didn't realize the full value that you were hoping to achieve. There's been some famous statements out there about price is what you pay, and value, or the overall value, is what you get. So underutilization is probably the most common.

    And I'm going to go ahead and talk a little bit about some of these things in different applications, and I'm going to do it from the perspective of a formula that I learned when I was learning about Six Sigma and Lean. There was a formula here called efficiency times effectiveness equals productivity, and this is a formula that you can apply to many different aspects of manufacturing, as well as other things. But I found it to be very interesting, and a very good way to look at what I'm doing with the cutting tool, and how I'm applying it.

    So when you look at efficiency, another way to look at it is that you're doing the right things. And I kind of mentioned the right tool. So, do you have the right tool? When I look at effectiveness, it's doing things right. And then from the productivity side, we're always trying to increase or improve productivity.

    So let's take a look at, from the cutting tool perspective-- I kind of jumped ahead of myself there a little bit ago, but let's just say, from a cutting tool perspective, efficiency is getting that right cutting tool. Effectiveness is the right approach, or the right parameters in applying that tool. And, of course, the other thing I like to do is I like to change the efficiency aspect and say utilization. So this is my formula that I use to qualify what I'm doing when I apply a tool, or if I'm looking at contrasting maybe an incumbent tool versus a new tool, and what that tool might be able to do for me.

    So let's take a look at this in the three common machining applications, and we'll start off with hole making. With hole making, there's a lot of different types of tools. There's solid carbide drills. There's indexable drills. There's deep hole drills. So there's a lot of different areas to-- that a programmer has to think about when they're choosing a drill.

    So not only is that a decision that takes some time-- make sure you're grabbing that right drill, or choosing that right drill-- then you got to look at the utilization of it. And this is easy for hole making because you're using the end of the tool, and when you're drilling, 99.9% of the time, that drill is 100% utilized on the diameter. Sometimes you're coring out a hole, but that's an outlier application.

    So we have 100% utilization, which is a good thing. We're fully utilizing that drill or that tool that we invested in. But now we got to take a look at effectiveness. And when I say effectiveness, now we're talking about the cutting parameters. And for a drill, there's a few-- only a few variables that you have to keep in mind.

    We're looking to calculate the overall velocity of the feed, the Vf-- so the overall feed in inches per minute when you program, as a CAM programmer-- and that value is derived from your feed per revolution, or fn for hole making, times your RPM. Or, in this case, n represents RPM.

    So if I look at that, and I say, OK, what do I have to work with in to calculate those values, now, a common thing for a programmer to do is to have to go back through, and either use an electronic catalog or a paper catalog, and they get to a portion where they've-- of the tool they've selected. The manufacturer will have provided these recommendations, and in hole making, when it comes to calculating speed, will give you different speed values for different materials.

    So that's a big factor to keep in mind because material and material hardness is the main factor for determining the speed at which you can run the tool. So it's very important to keep this in mind. And then for a drill, the typical feed parameters are by diameter. So, to be obvious, the smaller diameter drills will have lower feed recommendations. And then, when you get to the larger diameter drills, they're more robust. They're going to have higher feed recommendations.

    So in this case, we want to take and look at an example where we have a 1/2 inch tool. And you can see here, I highlighted the parameters for a given material. And if I look up at the top right-hand portion of the screen here, I've selected a 1/2 inch diameter for my tool, my material's 4340, and I've selected the parameters that would apply to that 1/2 inch tool in that material group.

    So we want to pull those parameters down, and take a quick look at them. So we have our feed recommendation range, which is from 6 thousandths to 13 thousandths feed per revolution, and then we have our RPM range recommended from 1757 to 2750. So a little better way of looking at this, a little easier visual-- let me jump back for a second.

    You could take this, and I'm going to I'm going to set my benchmark at the mean operating parameters-- those ones marked in red where I've got 9 thousandths feed, and 2292 RPMs. Based on our knowledge of our tooling, our carbide grades, how the tools are designed to perform, we're right in the middle of the operating parameters. I'm setting that as my benchmark.

    So if I look at my formula for effectiveness up top, I've got fn times n. So I've got my feed per revolution of 9 thousandths times my RPM. That gives me my Vf of 20.63, and that's my-- I'm 100% utilizing that tool, and I feel good about that. Now, this is my benchmark.

    If I'm comparing to a given tool that's already running, I'm going to take those parameters that you're using, and we'll use that as our benchmark to compare ourselves against. But that's a variable that, obviously, we can't account for here today, and it'll be different for everyone out there who's programming, and putting in values, and trying to get to a good, productive set of cutting parameters.

    So let's look at the lower set of values. If I was programming at the lower feed rate and speed, could see there, I've got 51% highlighted if I were to do that. So I'd have 100% utilization times 51%. Well, that's easy math, and that's why we picked the tooling that we did. So we're at 51% productivity compared to somebody who's running at the mean operating parameters.

    And if I'm in a situation where I know I've got good, rigid scenarios, I've got-- maybe I've got high-pressure coolant to help flush the chips out from the drilled hole as the drill's penetrating into the material-- you know, I might be this person, if I've got a rigid scenario, who can actually push beyond the 100% benchmark. And if I'm running at the top operating parameters recommended, I'm at 35.75. I'm 73% higher than the benchmark.

    So another way to visualize this is to say, I've got this operating range, this chart here. And you can see I've got my feed per revolution on the vertical axis, I've got my RPM here on the horizontal. And you can kind of just take a peek at, hey, this is the operating range that I'm supposed to be running these tools in.

    You would be surprised. When I talked about misutilization or underutilization, you'd be surprised how many times we find-- even though this information is published, it's readily available, you'll be surprised how many times we find customers who are running outside of this-- outside of this box. And we I know we talk about in manufacturing, a lot of times, getting outside the box as a good thing.

    But usually, when you're talking about cutting tool parameters, and cutting tool design, they're designed to run in a specific range. If you're getting outside the box, in terms of your effectiveness and your cutting parameters, not always a good thing. Not that it can't be done under certain circumstances, but it's a case-by-case basis, for certain.

    So, as I mentioned, I can look at my formula here. I've calculated this out, and at the mean parameters, I'm at 100% productivity. Another way of checking your math, and just kind of seeing the visual of what you're doing is that, if I look at a bar chart that has the minimum, the mean, and the max parameters, and I look at volume of material removal, which is very easy to calculate in a hole making process, I'm averaging 2.06 cubic inches of material removal per minute with that drill at the minimum parameters. The mean parameters are 4.05.

    And if I'm that person that can push the limits because I've got a rigid robust scenario, and I've got some better technologies in play, I'm going to be that-- like I said, that 73% more material removal rate over somebody who's forced to run at the mean parameters. Just another way of taking a look at that.

    Let's look at milling. Milling, it actually gets more complicated with milling. As someone who oversees some specialists in each area, I'm always teasing the milling or the homemaking specialists that their job is much easier than the milling guys. I hope I'm not offending anybody out there that focuses on homemaking applications, but the proof is in the number of variables that you have to deal with.

    So when we look at milling cutters, you can see, now I've got to take into consideration not only the end of the tool, I've got to take into consideration how I'm applying the tool both on depth of cut, and width of cut. And then my utilization gets more complicated. But I'm not going to go through an in-depth step-by-step process with this particular example. I just want to show really quick how the utilization aspect, and how you're applying the tool, can quickly reduce your overall productivity of the tool.

    So let's just say I'm looking at the average 1/2 inch end mill. And 1/2 inch end mill, typically a standard end mill might be two times diameter in cutting length on the flute. So I've got 1 inch flute length. So if I'm at a 1/2 inch diameter on my width of cut, and 1 inch on my depth of cut, I'm fully utilizing that tool.

    But let's take a look at what typically, or what really happens. In the real world, we see this all the time, where people are-- they only need to take a small depth of cut. So they might only be engaging 200 thousandths on the very end of that tool. So now you're wearing out the end of the tool, nothing's going on up here. You're not utilizing that tool as it was designed to be used, or you're over-utilizing it in terms of I don't need that much, but that was the tool I had available, so that's what I picked.

    But as you start to look at your utilization, you say, OK, it's very easy. If you're at 200 thousandths depth of cut, and you divide that by your 1 inch-- what we call APMX, or your maximum depth of cut that you have-- you're 20%. You can put a formula to that really quick. And if you're starting off with only 20% utilization on the carbide that you've used, then I could do the rest of this formula just the way that I did it in my previous slides on the homemaking, and I'm not going to be very productive at the end if I'm starting off with only 20% utilization.

    So when we look at this, real world things that we can be looking to do, there's interchangeable-- there's modular systems that-- they're designed to optimize the carbide because, if you don't need it, you don't need to buy it, let's put something in there that uses less natural resources, and still is effective at getting the job done. So this is just another example of looking at that from that utilization perspective.

    And then, finally, real quickly, I'll touch base on turning. The number one, in terms of volume, purchased cutting tool is a CNMG Insert for turning applications. And when you look at how many of these inserts are out there, they're not very expensive, but we're still using natural resources, and we're still pressing these inserts by the millions.

    So why wouldn't we want to fully utilize them? But if you take a look at the standard 432 or 4 series CNMG insert, the inserts designed for roughing applications, they might have recommendations on 200 thousandths, or a little more than 200 thousandths depth of cut on a 4 series.

    But how many times do you see somebody in a lathe, especially in today's world, where it seems like the machine tools are getting smaller, less powerful, more capable in terms of speed? How many times do you see somebody taking 200 thousandths per side in a lathe? Not that often.

    I would say it's-- the vast majority is maybe 100 thousandths or less. So if I throw that in there, and I say, OK, my utilization is my 100 thousandths depth of cut on an insert that's capable of 200 thousandths, why did I buy that 4 series insert? Why didn't I look at something that was less carbide, that was capable of the 100 thousandths, or maybe a little more-- maybe I need some freedom in there. But I'm all-- that's easy math.

    0.1 time-- divided by 0.2, I have a 50% utilization factor before I ever start doing any of the other calculations for how effective I'll run the tool, in terms of speed and feed per revolution. And then, looking at it from an overall productivity, if I started out at a 50% utilization, I'm not going to be very good at my overall value.

    So this utilization conundrum, let's face it. Why is this happening? Programmers have to keep a lot of things in mind. They're making hundreds of decisions a day. Think about a part that might have-- if you're on a multitasking machine, it could have all three aspects of machining-- turning, hole making, milling, and any of the operations that are within each one of those areas. So you see that, with every tool program, there's two, four, three variables to-- that those programmers have to look up, enter into a CAM environment, verify.

    It takes a lot of time, and I think time is the reason why we have this 50% utilization, give or take. And this decision-making process, it takes time. And, let's face it, when we are on the shop floor, we want to see machines running. If people are looking at the machine monitors where they have the flashing lights up top, or the red, yellow, green lights, and that thing's not green, the person walking through the shop who's maybe the manager, or the shop owner, or the shop foreman, they're usually putting pressure on programmers to get these machines running, if they're not running.

    And so that's why. You used to have more people running a given amount of machines, and they had so much time to get these parts out the door. And today's world, it's less people running more machines. And one of the things that we can do until things get automated enough that it helps these people out is we can try to look to how are these programmers able to access information, the power of the cloud, and to be able to make these decisions maybe inside the CAM environment, where it takes less time to-- once you've programmed the tool, you have it resident on your computer.

    Or maybe there'll be tools in the future where the CAM company-- in this case, referring to Autodesk Fusion 360-- and a cutting tool supplier, like an ISCAR, are saying, hey, we're pooling our knowledge, all of our resources, Autodesk's knowledge of how to drive cutting tools, and how to drive machine tools effectively, and ISCAR's knowledge, decades' worth of imperial information on cutting tools, and design, and different materials, and in different scenarios for different applications.

    And to do that, if we do that, and if we pay attention to these things, I feel like to get to the 80%, or even up to 100% utilization on the tool is an achievable goal that we can start looking at. And it's a goal that we should be looking at even in today's world, is can we increase the utilization on the things that we're purchasing for that production environment.

    And so, one of the things that we can do now-- and I hope that a future state is where these things are merged together, and working seamlessly. But one of the things that we can do now is we can look to leverage the resources that we have.

    And in today's world, with the digital information that's available-- electronic catalogs, cutting tool advisors, just different pieces of information that are at our fingertips because of our phones, or our access on the web, it's-- that is the conundrum to me, is that, other than the time constraints, the information is there for people to go out and seek it, and to make sure that they're operating cutting tools at that effective level, or that higher utilization that we're seeking to gain.

    And for ISCAR, one of those tools is what we call NEO ITA. It's our ISCAR Tooling Advisor. This is decades' worth of imperial information, and it's a-- when you talk about AI being a large language, NEO ITA is ISCAR's large language for cutting tool recommendations. We've taken just massive amounts of data, and put it into an area that, with a few clicks, gives somebody an output that they can use, and they can make sure that the utilization of their tool is what they need it to be to increase, and make better decisions, and be more productive in that machining cell.

    So there's going to be a video coming up where we'll just quickly introduce NEO ITA, and give you an idea of what that looks like, and how you might be able to utilize it in your environment.

    [WHOOSHING]

    [DINGING]

    [MUSIC PLAYING]

    [WHOOSHING]

    [DINGING]

    [MUSIC PLAYING]

    So with NEO ITA, right now it is a very quick, effective solution to get your cutting tool data that you need. Being a past programmer myself, I envision a world where, yes, it's great right now that I can be in my CAM environment, I can be programming my parts, and maybe I've downloaded my models from an electronic catalog. And I have my 3D assembly of my cutting tool model. It's in my CAM environment for my verification and collision checking purposes.

    But now I still need to bring in all those cutting parameters for each tool-- speed, feed, depth of cut, width of cut-- and make sure that they're in those-- well, if you're bringing it in from a NEO ITA, you're getting good values to enter, but each one of those values is manually entered. And so there's an area of improvement, both from the speed of programming, but also the accuracy of programming.

    We all know that, when we're punching keys on a keyboard, and entering information, there's always that threat of having a decimal place in the wrong place, or a wrong number. And then when you post out that code, and that value's there, it's there, and when-- and, a lot of times, it can be catastrophic.

    So that's the world that I envision for us in the future, where there's these merging of technologies, like from a tool advisor, where, at the click of a button, your cutting recommendations are all mapped, so to speak, and they go to where they need to go. And hopefully, that'll really improve upon the speed and the accuracy of what you're programming.

    So before I finish up, just a quick word on sustainability in a cutting tool perspective. Now, a few of the examples I've shown earlier we're making comparisons on certain types of tools, and I've kept it consistent, just so you can see, from a sustainability standpoint, what making one decision in the beginning-- a programmer making that decision-- can mean in terms of sustainability.

    So we had an example earlier where I was talking about a 1/2 inch diameter end mill, and talking about the utilization factor, right from the get-go, of if you're not taking the full depth of cut, or you don't need the full width of cut, what that does for utilization. But think about it-- thinking about it from a natural resources perspective-- so each one of these tools is uses up a certain amount of natural resources to be produced.

    This solid carbide tool starts out as-- well, obviously, it starts out as natural resources. But these natural resources are brought together, they're pressed, and they're pressed into a rod. And then that rod is ground. But, in general, a 1/2 inch tool that's a standard length tool is going to be about almost a half a cubic inch of carbide volume or material.

    Now, modular tooling, interchangeable tooling, systems like ISCAR's MULTI-MASTER, or tooling that is indexable-- and I've shown an example here that combines both the MULTI-MASTER modular connection with an indexable tool on the far left. You can see the difference in the volume of carbide that's used.

    So when you think about that, and you look at, OK, but these tools are designed for different applications-- and I took the maximum engagement of each of these tools, and said, OK, if you're running in a ISO P material like a 4340-- and I've already done the math, and said, OK, here's my speed, and my feed that these tools will be recommended to run at. You're looking at a tool that's capable of 2.7 cubic inches over here on the left. The one in the middle, the solid carbide interchangeable, will be about 9.9.

    And then the solid carbide tool, if you were running it full slot, on a rigid scenario, you'd be able to get 26.4 cubic inches of material per minute. But as I mentioned in my earlier example, the reality is that a lot of times we're using just the end of the tool, even for a solid carbide tool. So if you start looking at the design differences-- and you can get into the minutia of this, but it's so close. When you look at the design differences, there'll be a little bit of difference between the indexable and the solid carbide versions.

    But 2.7 to 3.6 cubic inches a minute, it may or may not be a make-or-break, depending on what you're doing-- super high production, maybe that would make a difference. But think about, you're almost able to do the same thing with either 74% less or 99% less carbide. That's huge, in terms of sustainability. You think about that over the thousands upon thousands, probably millions of 1/2 inch diameter tools that are used in the market every year, to use that much less carbide would be a big impact.

    And then let's look at the 1/2 inch diameter drill example that we were talking about earlier. If I were to look at what I call-- or what is called SUMOCHAM from ISCAR, which is the interchangeable or replaceable head system, versus a solid carbide tool, like on the right, once again, the solid carbide tool starts out from solid rod, most likely. And the carbide volume used in the production of that standard-length tool would be about almost 3/4 of the cubic inch of carbide.

    Now, the SUMOCHAM head is nowhere near that. It's 0.022 cubic inches of carbide volume to produce that head. So I look at the design differences, and I say, yes, the interchangeable or replaceable head end system will not-- I mean, it's so close, but not quite. You won't be able to push it quite as hard, but it's very, very close. And also, dependent upon applications, actually, there's times when you can push the interchangeable system harder than you can the solid carbide. And there's reasons for using solid carbide.

    But let's take a look just between 2.9 cubic inches in an ISO P material that I selected and did all the parameter-- did all the calculations on-- to 3.4. Yes, the solid carbide, as I mentioned, will be a little bit better, or a little bit increased in the overall productivity, in terms of metal removal. But if you're not pushing it to the maximum limits, you're probably not seeing that difference anyway. And if you can drill those holes with the SUMOCHAM, you're using 97% less carbide.

    And this doesn't even go into all the other reasons why an interchangeable or a modular system can be a better solution overall. Because of the versatility to change to different head geometries for different materials, I mean, the options are endless. That SUMOCHAM tool right there will have 50 different drill heads you can put in it with the variables between diameter, and different materials, and different geometries, self-centering, double margin for accuracy, all the different heads-- 50 choices compared to one solid carbide drill.

    You'll have a hard time keeping up with the productivity. If you're taking the time to make sure you grabbed the right head, and do the right things with the SUMOCHAM system, you will not beat the production. But the main thing to say here is that, from a sustainability standpoint, 97% less carbide for each head-to-drill comparison. That's huge.

    OK, so just want to close by saying, thank you for taking the time to watch this. And if you saw anything that was interesting, please reach out to ISCAR, to our main customer service web page. They'll get you in contact with specialists, and with individuals in your area who can help you, or can help you achieve these goals of increasing utilization with your cutting tools, and your processes. And thanks to Autodesk for including ISCAR in this wonderful event, and for having the opportunity to present to you today. Thank you.

    ______
    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。