Rob Caron, Caron Engineering: Smart Technology for Lights Out Machining

Wolfram’s Open House featured guest speaker, Rob Caron, President and Founder of Caron Engineering

Full Video Transcript

For those that don’t know me here, my name is Rob Caron. I’m the President and Founder of Caron Engineering. I started the company in 1986. My background’s electrical engineering and software. So all the products that you’ll see both on my presentation as well as out in the shop here at Wolfram have that component to it. TMAC is our flagship product. I developed the first one in 1990.

So this technology and what you’re gonna see on every machine here at Wolfram has been around that long. It’s obviously been enhanced. We’ve spent a lot of time working with companies like Wolfram who are really high-end users, trying to understand better on how we can make this the best product in a world-class product on the market. We specialize in all types of smart manufacturing solutions. I’m going to go through them all today, but everything that we do as a company component that helps basically allow less operator intervention, make things more foolproof, but also provide a tremendous amount of data to be able to go in and analyze when things are going wrong.

So why do we need smart technology, especially for automation? So even though kind of gearing this towards automation, this same technology is really needed whether you are automating or you have people running the machines. But with automation, you definitely want to have this technology as well. You guys can come up if you want. You guys in the back if you want to sit, come on in. So basically we look at the manufacturing challenges right now. The skills gap doesn’t even need to be explained. It’s everywhere in every industry and making it very challenging for all manufacturing companies. Process complexity. I think one of the biggest points here is that we hear this all the time from our customers. The material is changing. We’re forced to buy material from other countries, other vendors, and that adds a whole other level of complexity to the manufacturing process. Things that you have to do or you knew tools last an X long before, and all of a sudden they’re not last this long. Why is that? There’s a little bit of change in the material. But there’s also other things. Mill turns and other complex machines are just simply making the process of manufacturing more complicated. It’s making it better, but more challenging for operators. Just manufacturing jobs, there’s just less people that seem to want to be in manufacturing in general. That makes it– challenge there.

But when you are incorporating robots into your manufacturing cells, this is where smart technology is an absolute necessity because there’s not a person there hearing that a tool’s breaking or that a tool is not cutting well. There’s probably not even someone measuring the parts. So I’m gonna go through really why this technology is needed and how it fits in. So before cutting, the biggest error in manufacturing is loading tools into the machine. We have a lot of solutions and one of our partners here, Omega, is showing a pre-setter. We’re using this technology to automate the process of getting the dimensions of the tool into the machine correctly. Also, making sure the right tool is in the right machine. There’s a lot of other things that can be done with this technology. There’s two basic technologies. One is the RFID method, and the other one is a 2D barcode. I think this is essential for automation cells. Also, we’re working with different companies now where we’re actually putting tools into the machine with robots. Now, there is nobody there to type anything, right? So the actual data on the tool needs to be tracked very accurately, very well. So the system starts and Omega’s here with their unit. The system starts with the presetter and a tool crib, accurately measuring the tools and then writing that data automatically to the RFID tag that’s in the tool holder. We don’t need to just write the length and diameter of the tool, we can write a lot of other things. Which pulse stud does it have? Does it belong in a Sagami machine or an Akuma machine here? There’s a lot of other information. How fast should the tool rotate? How heavy is the tool?

Does the tool changer need to be slowed down because this tool is exceptionally heavy? So a lot of information can be there. Things that go wrong in the shop every day can be foolproof by using this technology. Once the tool gets to the machine, we have software and hardware that reads the data, can basically stop the operator from putting the tool in the machine if it’s not the right one. But it also prompts them of all the steps if there is an operator there on exactly what needs to happen and will not allow the process to proceed if they didn’t fulfill everything that was needed. Once the proper steps have been taken, that data is automatically written to the control. And there was no operator intervention in this process. So it happens automatically.

And it’s also logged, cataloged, and stored. So you know exactly what date and what time every single tool went into the machine. Sort of in the low-cost world, we have a barcode system, which simply takes the QR code that’s printed off the pre-center. You stick it on the tool holder. And the lengths of diameter are written back on the tool holder and forth to the machine.

It’s certainly not the more robust setup. The preferred method is the RFID technology. And one of the great things about RFID technology is, oftentimes you’re taking tools out of a machine that are still ready to cut again. So with this RFID system, we can take the current data. We can take the where offsets, maybe tool life, other information that might want to go along with the tool. We’re going to write it back to that tag, and that tool can then go on to the next machine. Tomorrow, next week, or next month, all the pertinent data is already ready to go, and ready to go into the next machine. So an essential system for both automation, but just in general to really foolproof the getting of the tools into the machine. Another technology that we have, and we call it before cutting because we do this as a warm up, say Monday morning when you’re warming the machine up, it’s a bearing analysis technology. What we do is we put a vibration sensor on the spindle. It stays on the spindle, stays in the machine, and is wired there permanently. Every week you can do it as often as you want, but typically every week you’ll run a bearing analysis on the machine and it’s going to tell you the health of the spindle. In the coming weeks, we’re going to show you how to do it. Graphs that you see on the screen, the left hand graph is what we call the acceleration of the vibration signature, and that’s going to tell you with a single number how healthy the bearings of the spindle are.

If you’re doing this every week and all of a sudden there is a crash on the machine, you can then run the bearing analysis again, and if you see a step in this number, then you know that that crash had an impact on the bearings right away. But it also is, gives you a little bit of a break, but it also gives you a little bit historical graph over time to tell you sort of an early warning indicator that your bearings are starting to go out of this machine and you should think about get your main department to schedule some time to rebuild or redo the spindle on this machine. So it’s a great tool. We have a lot of shop views in this now and this is kind of one of historical graphs. So as the bearings start to fail you just simply look at this graph over whatever time window you want And it’s going to show you where the health of the berries are today. But where were they last week, last month and last year?

So now we’re going to look a little bit at what happens during a cutting, and this is probably going to be the most prevalent technology you’re going to see at Wolfram when you get the shop tour out there. So the system that we use is called TMAC. You heard Nathan talk about it earlier. It stands for Tool Monitoring and Adaptive Control. TMAC uses a number of sensors. I’m going to talk right now about the power sensor, but what the system does is it has a real-time processor. You can see on the right the sensor in this particular case is a power sensor. This is a digital sensor and everybody’s kind of used to looking at a load meter on a machine. This is a thousand times more accurate than the load meter on a machine. It’s measuring the power in real time, and it can scale itself. So if I have a 40 horsepower spindle and I’m cutting with a four inch shell metal, a big heavy cut, it scales one way. If I go in with an eighth inch drill on that same 40 horsepower spindle, it’s going to scale itself way down, so that I can see that tiny amount of cut on a very large motor. We also have the user interface and again you’re going to see a lot out here in the shop. Our processor that you see on the right end-hand side has its own web server inside. It can be a direct connection to a PC, but all the screens, all the live cutting data and all the historical data you see are actually seen through a browser. It’s not an actual application.

So because of that, if you have a connection to that TMAC processor from anywhere in the world, you can watch live cutting data and you can look at any historical data that’s been cut previously on this machine. So the goal of TMAC is to maximize tool life, prevent tool breakage, reduce your cycle time and I’ll talk about adaptive control with that. It really eliminates the need for an operator intervention. Many shops are changing tools by cut time, by part count, but that’s not really very accurate because the material changes, the tooling changes. This gives you a way to get much more… more accurate tool life and do it very consistently over time. It also provides a common interface. So the screen you see in the center, whether you have a Sugali machine or some machine from Europe or any other country, our system looks the same. You know, every operator that uses it, no matter which machine they walk up to, they’re gonna see the same screens and the same type of information. So a little bit about how we actually look at tool wear. So basically, when a tool cuts and is brand new, there’s a certain amount of work that that tool does, and work is basically area under the curve. So we calculate all the amount of power that’s under the cutting line.

The cutting line in here is the white line. It’s shaded under green and yellow there, so you can see how that tool was cutting. Okay, we’re actually calculating how much work that tool does. When the tool gets dull, the work that tool does you can see the time hasn’t changed, but the tool is generating more effort, basically, and telling us this tool is worn. And this is definitely the most accurate way to measure the wear of a tool. Yeah, it ran its tricks. Look at me. So these limits, these settings, can be done for every tool. A tool can have different limits, let’s say you’re cutting at 1,000 RPM and then you go over and do another section at 2,000 RPM. Those can all be the same tool, but completely different limits and we can look at it separately. We still have the ability, if the tool gets to an exceptionally large power level, we still have the ability to have what we call an extreme limit. We’re gonna stop the machine, retract the tool out of the material and basically it will sit in an alarm at that point until someone gives it some attention. Good. And now it won’t happen. So we look really, when we start getting an automation now, we feel that this system is essential for automation because you have a robot, it’s loading parts all day long and it just keeps cutting, right? If the drill breaks and all of a sudden you’re missing one hole in a part, it may make 50 parts with one hole missing in it. So without having some type of system that’s looking at the tool health in real time, you can do a lot of, you can make a lot of bad parts with an automated cell.

So the other technology that’s inside a team act is tool monitoring, which is, you know, the work we talked about, there’s also adaptive control. And adaptive control, basically, you know, the ability to program a constant power cut and TMAC will automatically override the feed rate to maintain a power cut. Huge advantage in castings and forgings but any type of material where there’s anything changing at all it allows you to cut at the best horsepower for that tool. If you think about the service of a casting where there’s peaks and valleys all the time they’re not in the same place on every part TMAC can automatically compensate for that. It’s gonna cut fast when it can. It’s gonna slow down what it needs to. Protecting the tool, essentially also giving the tool a little bit better tool life because it’s never allowing the tool to cut excessively. So basically you can kind of see what happens is the power is the white line that’s shaded under there and the feed rate is the purple and it’s indirectly proportional. So when the hour was up, the feed rate goes down. down. It’s trying to achieve the green line and it does it very well. It’s doing this very fast. It’s with all the calculations in real time and it keeps a very consistent cut. And it really, the end goal is that it saves you cycle time because especially in materials like titanium, you cannot program as aggressively as you’d like to because you don’t know what the health of the tool is. The material may change a little bit. So you have to program a little bit slower and more conservative. With TMAC, you can get more aggressive and it will slow the tool down when it needs to or the tool degrades some.

But when it can, it’s going to go as fast as you allow it to. The maximum feed rate you can see here is 150%. It can go up to 255%. You have the control over that as the user. So we have other settings, sensors I talked about, the power vibration for varying analysis. We also have strain sensors. We use this a lot of times in Swiss machines where you have very tiny tools. The tool that’s pictured in this screen right here is a one millimeter tip boring bar. It took five, 10,000 step to cut. We’re able to monitor it with a strain technology. But there’s other sensors as well, like coolant flow and coolant pressure. Coolant flow is a huge indicator. Looking at coolant flow is a huge indicator because if your coolant pump gets clogged, then you’re going to really lose some tool life simply because you don’t have enough coolant delivery. But if you’re standing outside the machine and you see it splashing against the window, you really have no idea that it’s 50 % of the coolant flow. So these are other types of sensors we put on machines often to really look at the full… closed loop and analyze everything that’s going on. We can actually look at the data from the cold flow and overlay it onto the power data and say, “Why is it drawing more power now?” Well, the coolant was 20% lower than it was yesterday. So sensing, everybody sees all the, the loop on chat PT and everything, right?

But what AI needs or what machine learning needs? It needs as much data as possible. So the more things that you can monitor and sense, the closer you’re gonna get to be able to automatically determine problems. So, but TMAC can monitor all these channels simultaneously and basically allow you to review them. It also allows you to, as I said earlier, remotely look at TMAC. So, if you have the access to your shop via VPN or some network connection from anywhere else, and you can get to your TMAC system, you’ll be able to look at all of the cutting that’s going on.

We also collect all the data. You can look at it historically. You can go back and track. And again, you can see a lot of this out here at Wolfram. We also can store the access position. So you click anywhere on that screen and say, when this little blip happened in power, where was the access position? What was going on in the BAR program? So a lot of information that’s very, very useful when you’re trying to look at problems and look at situations.

Another sort of in-process technology we have is, again, go back to that BAR, the vibration sensor, except this time we’re going to use it on a BAR feeder. And for anywhere there’s a lot of information. of bar feed applications, you could have bend bars, anomalies in your bar. It causes the bar to vibrate. And what that does is cause you to make bad parts. Bar is vibrating, the tool is vibrating, and it’s creating, you know, out of tolerance dimensions. With our technology, we can put a sensor on a bar feeder, vibration. We can look at that vibration, and we can tell the CNC control, this bar is vibrating too much to make a good part. In your CNC control you can iterate through dropping the RPM small amounts until the system says your vibration is okay now. You can cut the part. The beauty of it is you can also go the other way so in a shop and we’ve seen this plenty the you know an operator here’s a bar vibrating they turn the spindle override down it may stay there for three weeks and then they’ve been cut parts that you know 70% of the cycle time for three weeks this system is Closed loop and adaptive so it will put the bar RPM back up when you need to and automatically correct for those processes.

Again, think about automation – more people are moving to bar feeders now with automation. That’s still a problem, Bar stock is not always good quality. Another thing is in the cutting process. So I talked earlier about presetting tools, right? It’s a good way to foolproof getting your tools in your machine and make sure the right tools go in the right machine. However, once the tool cuts part one, it may not be the right size anymore. So employing the laser technology in the machine to really continually measure your tools in real time and adjust the tool offsets, your wear offsets correctly, so you’re always cutting a good part.

So we, Caron Engineering, sell the Blum technology. We sell the pre-setter and the Blum technology a lot, especially in aerospace and tougher materials where literally the tool is already broken down after the first cut. So it’s a great technology, it’s incredibly accurate, it gives you a ton of information about how tools wear over time. So the last phase sort of the, you know, automation smart manufacturing section is really the after cutting part.

So I’ve got this robot, it’s taking parts out of the machine, and it’s actually putting them in a gauge and measuring them automatically. Well, that’s great, but the tools are still wearing, and there’s nobody sitting here looking at that data. So we use our software called AutoComp that allows you to take that gauge data and automatically update the tool offsets. So it’s going to continually update tool offsets based on the measured data. And it’s also going to track how much is changing those offsets. It can inform somebody or expire a tool because it’s worn beyond a certain weight. And this can be this software that can work whether it’s an automated cell with a robot or as a person. It’s simply eliminating the need for anybody to think about what to do and how to adjust tool offsets.

It also gives you traceability. It can track those offsets and adjustments over time, so now you have some data to work with. So basically, the flow is that you’re going to cut parts, you’re going to measure them. The measurement can be with a handheld gauge or it can be with a CMM or a vision system or any type of device, including the probe in the machine. So we still do probing in machines, but we can send the data out to Autocomp, so we have statistical and data logging for any of the tool offsets that happen. So all the devices that are measuring the part can be used to automate and offset the tools.

Another technology that can be used sort of after cutting is the surface roughness gauge. Again this is a blow product so you can actually measure surface finish inside the machine with a probe and gives you real-time results and so you don’t need to necessarily wait till parts come out of the machine. One of the advantages of this technology is if you’re measuring surface finish you can tell that the tool is degrading and maybe switch it out earlier. You know, e-max is going to tell you the power is getting higher but this is going to be a fire level of determining what the health of that tool is. Another sort of after cutting technology is a scanning probe. This probe is not a touch probe. It actually measures the displacement, the deflection of the stylus into thousands of an inch or microns of an inch. And what it does is it’s going to tell you when you come across the surface of the part, what did that deflection mean? From an anomalous surface or from a master surface? So again, it’s another tool in the toolbox of automating and inspecting in the machine itself. Yeah.

The last kind of piece of the automation and smart manufacturing is our MiConnect software. This software is an application builder that allows you to tie all the different people of automation together using a graphical flowchart programming style. You know, when you’re going to put automation and you’re going to tie all these systems together, oftentimes there’s many different pieces to it. You know, I want to incorporate a barcode reader. I want to send the data up to an ERP system or an MES system. Those things are challenging for automation companies who are used to just putting a robot on a barcode reader. This software allows integrators to build applications using a flow chart program, and it creates just an application that automatically allows all these things to tie together and communicate to each other. It has data logging in it, so anything you want to log in there, when someone reads a barcode, when did the robot open the door? All that can be logged and saved and you can look at it from an analytical standpoint. All the things that you wanna do, we pre-built in using developing our own software as we call plug-in. If you wanna talk to a CNC machine, you simply click on that plug-in, pick whatever control you wanna talk to. All the things you can redirect to that control are done automatically and have a name. You just incorporate those in the flow chart. REST API and SQL can be used for talking to database systems. or supervisory systems. So, we’ve already done the background work. You’re now just going to build a flowchart program, and that becomes an application that runs on this cell. If I have an application that’s for a specific control, I want to do the same thing on another cell, same thing but different control, you just select the difference and seek control. So, it really allows you to automate and Wolfram is again using this out here in their shop as well, but allows you to automate all types of things very simply. You don’t have to hire a computer programmer to tie all these pieces together.

One of the things pictured here is the actual badge. So most plants have a badge to get into your plant. You can actually read that badge for a cell and it can allow you to access different pieces of the cell without having to know usernames and passwords. So all that can be built with the software. So each of these technologies collect data in real time, everything we have, we have so many sensors, so much technology, there’s a lot of data flying around over there.

What you see in Wolfram is the OnTakt software. However, they’re actually taking that data and giving meaningful reports back into the system. So, you know, you kind of look at all this data and everybody looks at lots of data like this and say, “What do I do with all that stuff?” Well, the OnTakt software from Wolfram aggregates that data and gives you a meaningful report of, as Nathan talked about earlier, if you’re up in here to talk, am I on target with where I want to be or am I above or below that target? And what’s going wrong from there?

So basically all these smart made factory products that I’m talking about there the ultimate original goal is to eliminate operator error and any human intervention. But now that we have automation, we need to allow the unattended operation. We need to look at all the things that a person was doing that looked at before because they’re not there in the cell anymore anymore. And we want to really stop downtime. That’s the goal. We want to make sure that we understand what’s going wrong, but get someone involved before there’s actually downtime on the cell. Because the reason and your motivation to automate is you just want to run all the time. You want to create a lot of parts and create a good production run. So downtime is critical. And then the data is super important, you know, getting data for the analysis, we really, the more data we have, the more analytics we can do, and the more things we can figure out and help you really solve problems that are going on in your day-to-day environment. So, implementing smart manufacturing technology ensures consistent and accurate manufacturing parts in a fraction of the time.

So, that was a lot of information in a very short presentation, but we have several people in Caron Engineering here. Obviously, the Wolfram Group is very, very familiar with our technology. If anybody has questions right now, I’ll certainly take questions. Otherwise, we also can, you can come and see us throughout the day.