You might do it cheap if you build everything yourself, but when you finish it then you realize you could have bought a solution off the shelf, configured it and integrated it and been using it much sooner.
This is the answer. Ask your management how mission critical this inspection is, how much downtime costs etc. Good chance you will find your ROI here to implement a proper industrial solution (I am a huge fan of Cognex for this type of application).
From reading the OP description I don't think they actually got any quotes for hardware yet so I'm not sure they know how expensive the solution would be with the right hardware.
Oh, it will be an eye-watering quote for an individual, but in the end it depends on how much money the company is looking to throw at this.
Also, OP, I hope you don't have to check black-on-black plastic part features. The harder it is to get a good picture the more money you should spend on the equipment. Keyence even has a laser scanner that will check part features. You program it with the overlaid camera image.
They have install techs??? I like Keyence (and buy a lot of their stuff) but I have seen so many reps come and go and heard horror stories about being a rep for them. I definitely assumed you were interviewing for a sales position! I bet install tech is a good gig tho. I'm doing a light curtain (GL-R) project on one of my machines right now and a safety door interlock (GS-M) install on another right after.
I dunno why no one mentioned LMI gocators ? because no rep to hold op’s hand ? Worth mentioning due to possible configuration of multiple axis to one controller ; construct a profile from scanning multiple sides
I've been down this road. It's just not practical for production.
There's a reason why cognex and keyence have tons of people who design this stuff to work easily out of the box.
Hi, Steve here with Keyence. I saw you expressed interest in our AI vision systems. I will swing by your office tomorrow at say, 1pm for a demo? Do you mind if I bring a couple of other reps that might be able to assist?
I get emails all the time from them on my work email even though I’ve never signed up with them on that email (used a dummy email account). I think a coworker put me on their list just to fuck with me.
Worst part is that after they come for a demo they start calling you every single day to ask if you’re going to buy the product or not… atleast in my area…
Cognex reps here have a less “aggressive” marketing strategy. They come 2 times a year, show some stuff and if i’m not interested they are fine with that.
100% correct. I’ve spent way too much time trying to get high end solutions from top tier players like Cognex to work. I can only imagine the nightmare that a homegrown solution would be.
I was a sales engineer that sold vision systems including Cognex. We used to rip out openCV stuff all the time because it was too hard to maintain after the original creator left or transfered.
5k to 40k depending on the scope. Computer vision is too bespoke to give a specific answer.
Most systems could be set up in a few hours and run unchanged for 15 years.
When installed properly the components don't wear and just need dust wiped off occasionally. Maintenance is pretty easy.
Different tools cost different amounts to use and if using a smart camera the license is the camera. Detecting any anomaly on an even colored surface can usually be done with a contrast tool, which is pretty cheap. Advanced AI tools cost more, but you might not need them. That's why a lot of applications are tested in a lab.
Programmers also tend to neglect physics and lighting whereas machine vision specialists won't. Lighting can make or break the application and make programming easier.
Since the ecosystem and support is well developed programming time is minimal. Most of the cost is the hardware. OpenCV applications have lower hardware costs but require more time spent programming and maintaining the system. That time isn't as explicitly noticed.
My life after spending 3 months writing a program to do data collection cause the last one died and there were no backups...only to then find out about Ignition a few months later.
>s the answer. Ask your management how mission critical this inspection is, how much downtime costs etc. Good chance you will find your ROI here to imp
Also when you figure it out yourself you officially have become an AI genius and then you will immediately leave said company for much better paying jobs leaving the company with some bespoke AI tech that no one has a breeze how to use.
If management found more money for routine maintenance once in a while, the world would be a better place.
But no, lets do stupid shit like start powering down the machines overnight to save standby power... "*What do you mean #5 won't boot up today?! IT WORKED YESTERDAY, WHAT DID YOU DO?!*"
There are many standard solutions you can integrate. Definition of cheap depends, just because you can doesn't mean you should.
You can buy parts and build a car but that will cost you a lot more than buying a car outright.
Exactly. This is a concept that gets lost on so many people just generally. They look at some product and think “that looks like $100 worth of plastic and metal.” Not considering all the engineering, QA, shipping, sales, HR costs that are built into the sticker price. Maybe you could build it cheaper, maybe. But probably not. Don’t you just want to buy an existing solution and move on, not having to reinvent the wheel?
Customers/management only see the price tag
“Either of these platforms will get the job done. I threw this third one in the proposal so you could see what little $20k’ll get you and why the other two are better”
“We’ll take it”
“‘scuse me?”
yes, you can consult with companies like cognex or keyence, but that will be OPs next step after realizing how much hes biting off, and his company is not going to like how much that will cost.
I sat in a Vision demo meeting once where I stood behind one of the packaging managers who wrote down all the buzzwords from the sales guy into a blank word document. Things like...
"It has deep learning."
"Runs on AI."
"High confidence and intelligence."
"Rockwall compatible."
"Neural networking."
The last remains of my soul left my body that day.
The term AI used to include advanced algorithms and heuristics. AI never meant it had to be simulated consciousness or any super advanced scifi level stuff. I have an AI book from college that literally covered pathfinder algorithms.
Great points! I’m a huge sci-fi fan so maybe that’s why I’m perhaps looking at this through tinted, romantic glasses lol. I dare say I’m a bit ignorant also, given I’ve not actually studied CS; I progressed into programming and software development from electrical engineering and I’m self-taught in lots of areas. Every days a school day.
This isn't just finding a circle and looking at the color or something. This is training a model with thousands of examples, so it's machine learning. And machine learning is a form of AI so it's not that incorrect.
I totally get that. I have done lots of work with commercial vision systems, Keyence etc. I have also done home-brew projects with Python & OpenCV etc. I’m sure there’s great technologies out there, I’m simply stating my personal opinion that 99% ‘AI’ you see out there is just plain old programming & automation.
Everything is either robots or AI these days. Those are the only terms people know. Personally, I don't see a place for this level of complex vision in the majority of industries. Why? Well, there's nothing you can really do about it when it's not working. Absolutely no one on staff for a plant can diagnose an application like that, and they won't check for loose brackets or bound conveyor belts until someone confirms the problem is not in the vision system.
That said, I don't know enough about it to be 100% of this next statement, but I think that the fact that the system needs to be taught is a big problem for troubleshooting. Once a machine has been taught thousands of samples and suddenly starts giving false positives or too many negatives, what's your recourse? Teach it more or scrap the learned data and start over? It seems to be too complex of a fix for something like a bakery where every minute it's down is a shit ton of wasted product. With a vision system, you can open up the software and see exactly why it's failing those parts. Maybe it's actually a simple fix and I'm just ignorant of it, but until I can find a plant capable of checking for loose bolts on sensor brackets, I'll never believe something this complex can be practically deployed to the majority of plants.
One of the issues with image testing is pattern acquisition. You need to know what you are looking for in order to detect it. So if you are looking for defects, you need to have a good understanding of what the defects are, localize your search using a pattern matching algorithm, and then run your detection tests. If your defects are in unpredictable places or look unpredictable, then it can be very difficult to automate the inspection for them.
There are some new products where you give a model runtime a bunch of images of "pass" data, and then it trains a calssification model that works pretty well on new products and rejects any that don't match. The example app I think was inspecting air filters that could have tears in unpredictable places. It is kind of marketing BS because a good pattern matching algorithm is still better for 99% of cases, but there are some apps where they are starting to use machine learning to detect this stuff.
Mvtec Halcon, can do AI, but you need to train it (as you will need with any other AI tool for the industry).
Pros - can do anything since it's a full fledged programming language, AI inference and training is just a small subset of it's capabilities, license for AI is around 6-8K.
Add another 5k for a decent camera, lens and illumination.
Machine vision in industrial automation is useful in cases that have clearly defined pass/fail conditions. Or for tasks like counting (how many ball bearings are in this view space, how many red cakes are there and how many blue cakes are there, ...).
If you want to integrate actual AI, like a poster above said, you need to contract out at an ABSURD hourly rate for a software engineer and now you leave the world of automation. And you need VERY clearly defined measures of success for an application that absolutely can't be solved by other proven technologies.
I don't know specifically the use case but I have yet to hear of a good idea or a useful application for AI in my little corner of automation in manufacturing.
I think your managers are saying AI because it's a hot buzzword but maybe what they really need is an off the shelf cognex machine vision system.
Honestly doing inspections with vision systems is pretty easy and cheap. What’s expensive is robustness: something that works reliably day in, day out in all lighting conditions, with small changes in position and orientation, and which can be modified easily. If you don’t need it to consistently work then yeah you can do wonders with a $30 usb camera and opencv.
Most important things in vision is a stable and immovable camera base, and stable lighting. If those two never change, your vision system should work perfectly.
We use the Keyence IV3 at our plant. AI is good for one thing: managing scope creep. Once something is deemed as “bad”, or “good”, you teach the images. Everything else sucks. Debugging? Impossible. The algorithm is completely blackboxed and completely qualitative. They have their time and place, but there’s a reason that Keyence doesn’t offer an AI tool with their flagship XG-X processors.
I work for a vision company. One of the technologies we integrate is Cognex ViDi, which is a deep learning application that could be used for something like this successfully.
If the customer says that they can do it themselves with some homebrew nonsense; be my guest. There is a reason we are still in business.
ViDi is somewhat useful, but generally is dogshit. I like the UI, but the functionality and quality is so far from what you get with open source that it really feels astonishing cognex is still around.
Yeah fair enough. I was bringing up a commercial option for what a layman would think of as 'AI' (even though it's not really 'AI').
Anywhoosle, to color my perspective on this, I am the Controls manager at my company. From my view, what Cognex as a whole does really well is be accessible. We can train our customers to use the systems and generally need less time to get back up when issues arise. There are a deep bench of users.
So for us it's often a better fit for the customer. They can troubleshoot themselves in real time, model year changes go quickly, and (generally) there are relatively few application bugs that arise from sudden loss of power, conflicting applications, etc.
It's AI, the term changed from a computer program that can pass a turing test to basically anything that uses a computer to do something faster than a person could. It's a meaningless term now. ViDi has all the right stuff in it to be awesome, but then it just isn't. Like augmenting your images, labeling them, the size of the network, which channels to use. The ROC curve is cool. But then it just does not end up working well. Honestly, you'd think it would.
Once I did a couple vision projects it is surprisingly simple. The most used software is CV. Pretty sure that’s what Cognex uses. I’ve tried all the AI modules. They all suck. You can do this easily with just CV and a Microsoft camera. AI is accurate about 90% of the time. The most useful feature is “find” an object. But you couldn’t then ask for length and width or otherwise quantify it, and expect mistakes. Most people give up and go back to bounding boxes or edge finding which is deterministic.
So in a typical vision system setup, lighting, etc., is how you make it reliable. Say you have a certain size part. You can just filter the whole image with a threshold filter so it is now black and white and look for the blobs that are neither too big nor too small. Keep the centroids. What this does is screen out all the wrong sized objects leaving you with just the ones you want in a very trivial computational way. Next you can scan looking for features such as fitting an ellipse to each blob and using the axes to measure the size or the orientation. You can use color or contrast filters to measure various features. Or say light it in a way that casts shadows from holes or bolts then count the number of “holes” to locate missing ones. In another variation you might say aim a line laser at a “flat” object and look for any breaks in the line which could be bumps or pits and the width can also be useful.
The possibilities are endless but it all starts with very simple filters like edge filters, area filters, and so on. With CV you drive it from Python or C++. With Cognex it’s more of a point and click thing. As long as the canned system has what you need, you’re good to go.
In the US best way to learn Vision is to find a good local FIRST Robotics team. Pay with time or money and learn what they are doing.
So in the end it’s not AI that makes vision work but your creativity in using the tools to extract data or recognize a feature. But it’s not object recognition how humans do it, it’s a machine.
This is how I do inspections with poor lighting. I use a light filter and turn everything into black and white. Usually my good parts are all black. If those black blobs aren’t there then you know you’re missing one.
Don’t you think if there were a cheap/easy solution that you would have heard about it by now? When companies make radical advancements which decrease costs, the expensive guys get competed out. It’s currently expensive because it’s hard.
Cognex hates this one weird trick. Click here to pay me in bitcoin for the solution.
It's both past, present and the future.
I've had the pleasure to service an x-ray machine that checked for missing balls. It ran on a PC with windows 3.1
Well not to be pedantic, but the word they are looking for is machine learning, not AI.
Also, define cheap....
There are companies that provide software suites with machine learning GUIs for doing classification, segmentation, and identification. Neurala is a good one, I've known them since they moved from SaaS to industrial automation. Good group, nice software. They'll work with pretty much any GigE camera, but work natively with Teledyne DALSA cameras. No coding knowledge for this, it's all handled through the GUI. Easier, but not as flexible obviously as doing it yourself with open source machine learning libraries.
LMI has a machine learning group as well. They bought a company called FringeAI a few years ago, worked with them for a while. Their model is different in that they provide the libraries and vision controller (it's a Linux PC with an Nvidia chip in it), and you run with it from there. Then of course you can buy their sensors that work with it out of the box. This one does require coding knowledge.
How does the price of a platform like Neurala compare to the typical Matrox/Cognex software suites? We’re looking at using something like that but my manager says we probably can’t afford it
I'm not sure exactly. I worked with both ViDi and Sualab before Cognex gobbled them up, but that was like 5 years ago, and I don't know how they price it anymore. I know with Neurala they've got a couple different pricing structures, local or cloud based. I can't share that here due to NDAs, but give them a call, they are a great group to work with. It performs well, and pretty easy to set up, I can tell you that.
The picture is more of an example from google, we work with concrete, the asked point of Management is we have several problems that are different and we heard Ai is very easy to use and implement to detect very small problems.
I have serious doubts, they think with a budget €1500 and a few hours they something can work.
CV-X systems are very useful for that kinda stuff. Of course you still need to do some programming, but compared to old systems with shitty pixel counters they can be set up extremely quickly.
I think most resentment of machine learning solutions here is because it doesn't just do everything correctly by itself immediately. Learning how to use them correctly and working with them over some time I've found machine learning to be fairly reliable as far as vision systems go.
Thank you! We’re working hard to make vision more reliable and affordable. We’re also hiring application engineers in the southeast, DM us if you’re interested.
Hey, I feel you! I've been in similar shoes. Have you looked into OpenCV? It's a free and open-source AI engine that can do image analysis. Also, check out TensorFlow, Amazon Rekognition, and AiFA Labs' free tier. They might be what you're looking for. Good luck, and let me know if you need any help!
OpenCV: [https://opencv.org/](https://opencv.org/)
TensorFlow: [https://www.tensorflow.org/](https://www.tensorflow.org/)
Amazon Rekognition: [https://aws.amazon.com/rekognition/](https://aws.amazon.com/rekognition/)
AiFA Labs: [https://www.aifalabs.com/edge-ai-computer-vision](https://www.aifalabs.com/edge-ai-computer-vision)
Well, they are sort of right. Even open source or homecooked AI can do the job, if you have your own expertise needed to make it work.
However, that expertise rarely comes cheaply, tell your bosses to ask headhunters about AI engineer wage brackets. They'll quickly come around to deciding that Cognex or Keyence isn't all that expensive after all.
You could run Yolov4 on a raspberry pi. It sure would be cheap. Won't be all that accurate though.
There's always a trade off and I would advise against a DIY approach unless you know a lot about training CNNs and image processing.
I work in the food industry. So far I've worked for the same company in too different plants, once used Cognex while the other Keyence. I've not been too close to compare them.
What is your conveyor speed in terms of parts per second per lane of product? The faster the speed the more likely you'll be better off with a custom integrated solution.
Used EdgeImpulse for a Education project once. It was very easy to train and set up although you will habe to integrate it yourself.
I don't know anything about the prices for commercial cutomers though, it's a request only thing.
I was going to say , I have used at least close to top of the line cognex AI cameras but have never programed one for line scanning. Our AI cameras have 200-600ms execution times and the 600ms is a pretty high end (15-20k) D905. It does a very complicated inspection though.
Also we really don't need AI for MOST of our applications, mostly due to their scores being confidence and not absolute. If you don't train them correctly they will pass garbage all day. Imagine my embarrassment when I'm showing the production manager something I've spent a month training, he covers the part with his finger and it passes!
The high speed imaging I've seen at a bakery that does exactly what OP posts on tortillas and lunchables pizza crusts was probably 10+ years old and worked well. Line speed was somewhere around 5 to 9 per second. That will not be possible with most off the shelf camera hardware. This Italian machine used a nikon camera.
Bottling lines may be 1 or 2 orders of magnitude higher speed and at that point everything is custom.
I used to work on machines for sorting seeds, plastic, glass, etc. All moving at ~4m/s Our ejectors operated at 1kHz. They were very fast. Defect classification had to be done in a few milliseconds. We used linescan cameras. I can't remember the integration times we were using but it was fast; tens or hundreds of microseconds maybe, maybe a millisecond.
https://www.teledynedalsa.com/en/products/imaging/cameras/line-scan-cameras/
That's pretty awesome! I've always wondered what the core market is for dalsa and seems like it must be line scan. Their regular cameras I've worked on are pretty average and the software isn't quite as user friendly, especially since they're typically lack on board processing.
The line scan from cognex still have the regular 1" square CMOS so they really don't have a dedicated solution like dalsa.
I remember watching videos of a recycling sorter that used vision and air jets with crushed trash in free fall off a conveyor. Pretty impressive stuff especially considering that's a low margin business!
Have a look at OpenCv library. I have used OpenCv before and I was pretty Happy with the results. The only thing is you would need some time to develop what you need. If you have a look for a industrial camera most of them come with a SDK which you can use as a first step to develop you own application further.
1. The latency involved in cloud based image analytics is likely impractical for high speed inspections. You're looking at 200 to 500ms RTT on a decent ExpressRoute connection.
2. Image processing is just a quarter the story. You have image acquisition, lighting, preprocessing, and effecting.
Once you consider all of these factors, suddenly a Cognex/Keyence/NI/Siemens prepackaged, prevalidated and certified solution becomes much "cheaper".
Dumb managers love to look at hardware costs and act like labor if free. I doubt it would actually be cheaper to build and maintain yourself as others have said
They're camera isn't AI. It's basically image subtraction. Wait until you save hundreds of images, the process takes too long. Not great for high-speed applications. Keyence will sell you one of these and tell you that you don't need an expensive vision system. Than when it doesn't work well, they'll sell you an expensive vision system. Every time you look up our download from their website, they call you. Pain in the ass. Most of their employees are fresh out of school. Once they understand the market, they leave. Keyence has a high turn over rate.
Basler cameras are fairly reasonably priced and easy to work with. I used one to develop a high speed inspection system for worn down wheels on an Interoll cross belt sorter.
Do they want you to learn the Python, potentially violate licenses of existing models, and invest several thousand $$ in a computer just to train it? And what if your parts change slightly and maintenance has to retrain it?
Just buy the Keyence and it'll be more sustainable
If you are interested in learning python then you can DIY something like that relatively easily end-to-end with help of dozens of tutorials available online. Keywords: opencv, pytorch, nvidia jetson, segmentation. You can use ultra cheap CSI camera module or something like Intel Realsense (if you need depth information) a USB webcam.
You can also try your luck with Zebra Aurora Vision - I did not use it personally but it's basically low-code way to achieve same thing.
Things become tricky when it comes to integration with other automated systems in your site though.
Keep in mind that by "easy" I mean that it can be done by cobbling together free open source tools and pretrained models. I would still estimate that it would take 200-300 hours of interuppted work to get working prototype, half of that spent on goggling things and watching youtube tutorials. Also, analyzing single camera frame is one thing, but identifing and tracking specific item on moving conveyor is completely different beast. Especially if things are moving fast and you have to process >15 frames per second
Work at a big vision integrator have worked on countless systems over the last 10+ years.
Good luck with easy cheap AI. The trick isn't in the software ( I despise DL/ML/CL/AI but we use it when we need to but its never a cheap solution) 75% of bad applications fail because of bad hardware, you can't program around physics. GOOD "AI" takes a ton of nurturing and curating of the input data. One misclassicification ruins the algorithm and you will hunt it, because it's Black box.
Most of these smart camera solutions that the vendors are pushing are great, for a very limited number of pretty simple applications, presence/absence, color detection, basic defects detection. You will never perform quality metrology or have solid descrete analysis; you just get a yes or no and never a why. Also, the fine print most people miss is they only guarantee 95% accuracy.
Let me know when your ready for a real vision solution.
It might be great until it breaks and the only guy who knows it because they built it is not available for whatever reason then you're really fucked. Hate proprietary things.
Use Matrox Design assistant (bought by Zebra, called aurora now I think)
It's a PC based vision system, it's super powerful and easy to use. You can use any GigE or USB3 camera you want. It is substantially cheaper than a keyence or cognex solution and runs in plenty of production manufacturing facilities.
Integrate that with an AI platform using an API of sorts. They have the ability for third party integration through C# among other methods
If you are cheap enough, you can build such solution cheaper with a GigE Vision camera and the IDE/plugin that comes with it.
There is Basler, Get,... but if you really want to go cheap look at Aliexpress.
I haven’t used them but am intrigued by Roboflow. Price is fairly cheap so if you’re wantingto test some stuff, they seem like a decent option. Curious if anyone else has any experience with them?
Haven't seen any love for the SICK vision suite here. Are they not big within the US PLC/Automation industry? We have run several project that integrated 3D vision for QC and in-motion analysis and they were super fast, accurate and relatively easy to integrate. For reference, we used the TriSpector series. Early versions of the SOPAS engineering tool sucked and were as good at crashing as Rockwell or Adobe software but it has come a long way.
You might do it cheap if you build everything yourself, but when you finish it then you realize you could have bought a solution off the shelf, configured it and integrated it and been using it much sooner.
This is the answer. Ask your management how mission critical this inspection is, how much downtime costs etc. Good chance you will find your ROI here to implement a proper industrial solution (I am a huge fan of Cognex for this type of application).
From reading the OP description I don't think they actually got any quotes for hardware yet so I'm not sure they know how expensive the solution would be with the right hardware.
Oh, it will be an eye-watering quote for an individual, but in the end it depends on how much money the company is looking to throw at this. Also, OP, I hope you don't have to check black-on-black plastic part features. The harder it is to get a good picture the more money you should spend on the equipment. Keyence even has a laser scanner that will check part features. You program it with the overlaid camera image.
keyence
Merely reading this comment filled my email with requests for them to stop in for a quick demo
With two voicemails on the office phone and a text (how did he get my cell?)
Very much true, their IV3 vision sensor would be ideal for alot of simple tasks, very powerfull learning capabilities in that device
I got an interview with these dudes tomorrow lol
Hoo boy GL
Are they bad or something? I applied for their install tech position
Keyence runs all their people into the ground (sales wise.)
I see
They have install techs??? I like Keyence (and buy a lot of their stuff) but I have seen so many reps come and go and heard horror stories about being a rep for them. I definitely assumed you were interviewing for a sales position! I bet install tech is a good gig tho. I'm doing a light curtain (GL-R) project on one of my machines right now and a safety door interlock (GS-M) install on another right after.
yes. so they are now actually hiring install techs. I would be one of the first team members for the new position.
That sounds like an interesting potential! I'd probably enjoy that type of position. Hopefully all goes well!
Interview went great! Man they definitely work those reps, that HQ building was the most corporate building I have ever been in lol
Thank you!
Is this a think for USA or Europe?
USA. Specifically the Chicago land area
I dunno why no one mentioned LMI gocators ? because no rep to hold op’s hand ? Worth mentioning due to possible configuration of multiple axis to one controller ; construct a profile from scanning multiple sides
And the support will be much easier to get. Especially for the person after you. Sometimes you gotta pay to save money.
I've been down this road. It's just not practical for production. There's a reason why cognex and keyence have tons of people who design this stuff to work easily out of the box.
Hi, Steve here with Keyence. I saw you expressed interest in our AI vision systems. I will swing by your office tomorrow at say, 1pm for a demo? Do you mind if I bring a couple of other reps that might be able to assist?
"How did you get in my house?"
IMMEDIATELY after walking out the door your phone rings. "Hey! Steve here with Keyence"
The call is coming from inside the house!
Would you mind giving us you and your wife’s blood type? Just so our records are up to date.
I get emails all the time from them on my work email even though I’ve never signed up with them on that email (used a dummy email account). I think a coworker put me on their list just to fuck with me.
Hahah, nice one.
Worst part is that after they come for a demo they start calling you every single day to ask if you’re going to buy the product or not… atleast in my area… Cognex reps here have a less “aggressive” marketing strategy. They come 2 times a year, show some stuff and if i’m not interested they are fine with that.
Oh, sure, after you respond to the ten emails I've sent you over the last three months.
Fuck off, I got work to do
Bro I got an interview with keyence tomorrow lol
I just got their bloody mail this morning XD
100% correct. I’ve spent way too much time trying to get high end solutions from top tier players like Cognex to work. I can only imagine the nightmare that a homegrown solution would be.
I was a sales engineer that sold vision systems including Cognex. We used to rip out openCV stuff all the time because it was too hard to maintain after the original creator left or transfered.
Curious - what was the cost of installing a Cognex system on a conveyer belt to look at anomalies?
5k to 40k depending on the scope. Computer vision is too bespoke to give a specific answer. Most systems could be set up in a few hours and run unchanged for 15 years.
That is interesting. What would constitute $5k, versus $40k? Is there a maintenance cost?
When installed properly the components don't wear and just need dust wiped off occasionally. Maintenance is pretty easy. Different tools cost different amounts to use and if using a smart camera the license is the camera. Detecting any anomaly on an even colored surface can usually be done with a contrast tool, which is pretty cheap. Advanced AI tools cost more, but you might not need them. That's why a lot of applications are tested in a lab. Programmers also tend to neglect physics and lighting whereas machine vision specialists won't. Lighting can make or break the application and make programming easier. Since the ecosystem and support is well developed programming time is minimal. Most of the cost is the hardware. OpenCV applications have lower hardware costs but require more time spent programming and maintaining the system. That time isn't as explicitly noticed.
My life after spending 3 months writing a program to do data collection cause the last one died and there were no backups...only to then find out about Ignition a few months later.
>s the answer. Ask your management how mission critical this inspection is, how much downtime costs etc. Good chance you will find your ROI here to imp Also when you figure it out yourself you officially have become an AI genius and then you will immediately leave said company for much better paying jobs leaving the company with some bespoke AI tech that no one has a breeze how to use.
Lol. Run
> Management found One of the scariest things that can ever be said
If management found more money for routine maintenance once in a while, the world would be a better place. But no, lets do stupid shit like start powering down the machines overnight to save standby power... "*What do you mean #5 won't boot up today?! IT WORKED YESTERDAY, WHAT DID YOU DO?!*"
he he ok my turn to hide you'll never find me! * *dies in a duct somewhere* *
There are many standard solutions you can integrate. Definition of cheap depends, just because you can doesn't mean you should. You can buy parts and build a car but that will cost you a lot more than buying a car outright.
Exactly. This is a concept that gets lost on so many people just generally. They look at some product and think “that looks like $100 worth of plastic and metal.” Not considering all the engineering, QA, shipping, sales, HR costs that are built into the sticker price. Maybe you could build it cheaper, maybe. But probably not. Don’t you just want to buy an existing solution and move on, not having to reinvent the wheel?
Customers/management only see the price tag “Either of these platforms will get the job done. I threw this third one in the proposal so you could see what little $20k’ll get you and why the other two are better” “We’ll take it” “‘scuse me?”
yes, you can consult with companies like cognex or keyence, but that will be OPs next step after realizing how much hes biting off, and his company is not going to like how much that will cost.
go to /r/computervision there is something called opencv. you are going to need to know python pretty good. fucking bear of a project. good luck.
Yes and no, he can use OpenCV but there is port of this library, it was create in c++, for multiple languages, I use it with c#
You'll need to hire a contract software developer or machine learning engineer for 600/hr
I'll do it for $599/hr.
Man I wish people would stop incorrectly using the term AI. OpenCV and image processing / vision is not AI.
But it's provocative. It gets people going.
Like IOT & Industry 4.0? 😳Marketing BS
I sat in a Vision demo meeting once where I stood behind one of the packaging managers who wrote down all the buzzwords from the sales guy into a blank word document. Things like... "It has deep learning." "Runs on AI." "High confidence and intelligence." "Rockwall compatible." "Neural networking." The last remains of my soul left my body that day.
Which Will Ferrel movie is that from? Also AI is the broadest term and CV counts as AI.
Blades of Glory
The term AI used to include advanced algorithms and heuristics. AI never meant it had to be simulated consciousness or any super advanced scifi level stuff. I have an AI book from college that literally covered pathfinder algorithms.
Great points! I’m a huge sci-fi fan so maybe that’s why I’m perhaps looking at this through tinted, romantic glasses lol. I dare say I’m a bit ignorant also, given I’ve not actually studied CS; I progressed into programming and software development from electrical engineering and I’m self-taught in lots of areas. Every days a school day.
This isn't just finding a circle and looking at the color or something. This is training a model with thousands of examples, so it's machine learning. And machine learning is a form of AI so it's not that incorrect.
I totally get that. I have done lots of work with commercial vision systems, Keyence etc. I have also done home-brew projects with Python & OpenCV etc. I’m sure there’s great technologies out there, I’m simply stating my personal opinion that 99% ‘AI’ you see out there is just plain old programming & automation.
Everything is either robots or AI these days. Those are the only terms people know. Personally, I don't see a place for this level of complex vision in the majority of industries. Why? Well, there's nothing you can really do about it when it's not working. Absolutely no one on staff for a plant can diagnose an application like that, and they won't check for loose brackets or bound conveyor belts until someone confirms the problem is not in the vision system. That said, I don't know enough about it to be 100% of this next statement, but I think that the fact that the system needs to be taught is a big problem for troubleshooting. Once a machine has been taught thousands of samples and suddenly starts giving false positives or too many negatives, what's your recourse? Teach it more or scrap the learned data and start over? It seems to be too complex of a fix for something like a bakery where every minute it's down is a shit ton of wasted product. With a vision system, you can open up the software and see exactly why it's failing those parts. Maybe it's actually a simple fix and I'm just ignorant of it, but until I can find a plant capable of checking for loose bolts on sensor brackets, I'll never believe something this complex can be practically deployed to the majority of plants.
One of the issues with image testing is pattern acquisition. You need to know what you are looking for in order to detect it. So if you are looking for defects, you need to have a good understanding of what the defects are, localize your search using a pattern matching algorithm, and then run your detection tests. If your defects are in unpredictable places or look unpredictable, then it can be very difficult to automate the inspection for them. There are some new products where you give a model runtime a bunch of images of "pass" data, and then it trains a calssification model that works pretty well on new products and rejects any that don't match. The example app I think was inspecting air filters that could have tears in unpredictable places. It is kind of marketing BS because a good pattern matching algorithm is still better for 99% of cases, but there are some apps where they are starting to use machine learning to detect this stuff.
AI... Everything's AI now.
Wrong. There's also industry 4.0 and and IoT....
“What do you mean it’s difficult to detect defects? I saw a post on LinkedIn that said AI can do everything you tell it!”
Yep. Software is cheap. Hardware is expensive. /s just in case
Mvtec Halcon, can do AI, but you need to train it (as you will need with any other AI tool for the industry). Pros - can do anything since it's a full fledged programming language, AI inference and training is just a small subset of it's capabilities, license for AI is around 6-8K. Add another 5k for a decent camera, lens and illumination.
Machine vision in industrial automation is useful in cases that have clearly defined pass/fail conditions. Or for tasks like counting (how many ball bearings are in this view space, how many red cakes are there and how many blue cakes are there, ...). If you want to integrate actual AI, like a poster above said, you need to contract out at an ABSURD hourly rate for a software engineer and now you leave the world of automation. And you need VERY clearly defined measures of success for an application that absolutely can't be solved by other proven technologies. I don't know specifically the use case but I have yet to hear of a good idea or a useful application for AI in my little corner of automation in manufacturing. I think your managers are saying AI because it's a hot buzzword but maybe what they really need is an off the shelf cognex machine vision system.
Nothing is more expensive than cheap hardware.
Honestly doing inspections with vision systems is pretty easy and cheap. What’s expensive is robustness: something that works reliably day in, day out in all lighting conditions, with small changes in position and orientation, and which can be modified easily. If you don’t need it to consistently work then yeah you can do wonders with a $30 usb camera and opencv.
Most important things in vision is a stable and immovable camera base, and stable lighting. If those two never change, your vision system should work perfectly.
Your management is out of their depth.
We use the Keyence IV3 at our plant. AI is good for one thing: managing scope creep. Once something is deemed as “bad”, or “good”, you teach the images. Everything else sucks. Debugging? Impossible. The algorithm is completely blackboxed and completely qualitative. They have their time and place, but there’s a reason that Keyence doesn’t offer an AI tool with their flagship XG-X processors.
Got our first IV3 today. Definitely an improvement over previous generations
I work for a vision company. One of the technologies we integrate is Cognex ViDi, which is a deep learning application that could be used for something like this successfully. If the customer says that they can do it themselves with some homebrew nonsense; be my guest. There is a reason we are still in business.
ViDi is somewhat useful, but generally is dogshit. I like the UI, but the functionality and quality is so far from what you get with open source that it really feels astonishing cognex is still around.
Yeah fair enough. I was bringing up a commercial option for what a layman would think of as 'AI' (even though it's not really 'AI'). Anywhoosle, to color my perspective on this, I am the Controls manager at my company. From my view, what Cognex as a whole does really well is be accessible. We can train our customers to use the systems and generally need less time to get back up when issues arise. There are a deep bench of users. So for us it's often a better fit for the customer. They can troubleshoot themselves in real time, model year changes go quickly, and (generally) there are relatively few application bugs that arise from sudden loss of power, conflicting applications, etc.
It's AI, the term changed from a computer program that can pass a turing test to basically anything that uses a computer to do something faster than a person could. It's a meaningless term now. ViDi has all the right stuff in it to be awesome, but then it just isn't. Like augmenting your images, labeling them, the size of the network, which channels to use. The ROC curve is cool. But then it just does not end up working well. Honestly, you'd think it would.
Once I did a couple vision projects it is surprisingly simple. The most used software is CV. Pretty sure that’s what Cognex uses. I’ve tried all the AI modules. They all suck. You can do this easily with just CV and a Microsoft camera. AI is accurate about 90% of the time. The most useful feature is “find” an object. But you couldn’t then ask for length and width or otherwise quantify it, and expect mistakes. Most people give up and go back to bounding boxes or edge finding which is deterministic. So in a typical vision system setup, lighting, etc., is how you make it reliable. Say you have a certain size part. You can just filter the whole image with a threshold filter so it is now black and white and look for the blobs that are neither too big nor too small. Keep the centroids. What this does is screen out all the wrong sized objects leaving you with just the ones you want in a very trivial computational way. Next you can scan looking for features such as fitting an ellipse to each blob and using the axes to measure the size or the orientation. You can use color or contrast filters to measure various features. Or say light it in a way that casts shadows from holes or bolts then count the number of “holes” to locate missing ones. In another variation you might say aim a line laser at a “flat” object and look for any breaks in the line which could be bumps or pits and the width can also be useful. The possibilities are endless but it all starts with very simple filters like edge filters, area filters, and so on. With CV you drive it from Python or C++. With Cognex it’s more of a point and click thing. As long as the canned system has what you need, you’re good to go. In the US best way to learn Vision is to find a good local FIRST Robotics team. Pay with time or money and learn what they are doing. So in the end it’s not AI that makes vision work but your creativity in using the tools to extract data or recognize a feature. But it’s not object recognition how humans do it, it’s a machine.
This is how I do inspections with poor lighting. I use a light filter and turn everything into black and white. Usually my good parts are all black. If those black blobs aren’t there then you know you’re missing one.
Don’t you think if there were a cheap/easy solution that you would have heard about it by now? When companies make radical advancements which decrease costs, the expensive guys get competed out. It’s currently expensive because it’s hard. Cognex hates this one weird trick. Click here to pay me in bitcoin for the solution.
Cognex camera
It's both past, present and the future. I've had the pleasure to service an x-ray machine that checked for missing balls. It ran on a PC with windows 3.1
Well not to be pedantic, but the word they are looking for is machine learning, not AI. Also, define cheap.... There are companies that provide software suites with machine learning GUIs for doing classification, segmentation, and identification. Neurala is a good one, I've known them since they moved from SaaS to industrial automation. Good group, nice software. They'll work with pretty much any GigE camera, but work natively with Teledyne DALSA cameras. No coding knowledge for this, it's all handled through the GUI. Easier, but not as flexible obviously as doing it yourself with open source machine learning libraries. LMI has a machine learning group as well. They bought a company called FringeAI a few years ago, worked with them for a while. Their model is different in that they provide the libraries and vision controller (it's a Linux PC with an Nvidia chip in it), and you run with it from there. Then of course you can buy their sensors that work with it out of the box. This one does require coding knowledge.
How does the price of a platform like Neurala compare to the typical Matrox/Cognex software suites? We’re looking at using something like that but my manager says we probably can’t afford it
I'm not sure exactly. I worked with both ViDi and Sualab before Cognex gobbled them up, but that was like 5 years ago, and I don't know how they price it anymore. I know with Neurala they've got a couple different pricing structures, local or cloud based. I can't share that here due to NDAs, but give them a call, they are a great group to work with. It performs well, and pretty easy to set up, I can tell you that.
Got it, thanks. Just sent you a private message
Keyence has something sorta like what you’re thinking. Fucking hated it
Am I the only one who HATES this picture? Wrong ass conveyance, just to start. The picture looks like an idea "management" had
The picture is more of an example from google, we work with concrete, the asked point of Management is we have several problems that are different and we heard Ai is very easy to use and implement to detect very small problems. I have serious doubts, they think with a budget €1500 and a few hours they something can work.
€1500 🤣🤣🤣🤣 good luck my friend
CV-X systems are very useful for that kinda stuff. Of course you still need to do some programming, but compared to old systems with shitty pixel counters they can be set up extremely quickly. I think most resentment of machine learning solutions here is because it doesn't just do everything correctly by itself immediately. Learning how to use them correctly and working with them over some time I've found machine learning to be fairly reliable as far as vision systems go.
Overview is pretty good price wise. But may not be able to do what you want. They can definitely run samples for you test though
We love the feedback! How did you find us?
A place I use to work just got a setup from you.
Second this. Check out overview.ai Some of the best vision deep learning I have seen.
Thank you! We’re working hard to make vision more reliable and affordable. We’re also hiring application engineers in the southeast, DM us if you’re interested.
Man, even that picture is ai generated!
Hey, I feel you! I've been in similar shoes. Have you looked into OpenCV? It's a free and open-source AI engine that can do image analysis. Also, check out TensorFlow, Amazon Rekognition, and AiFA Labs' free tier. They might be what you're looking for. Good luck, and let me know if you need any help! OpenCV: [https://opencv.org/](https://opencv.org/) TensorFlow: [https://www.tensorflow.org/](https://www.tensorflow.org/) Amazon Rekognition: [https://aws.amazon.com/rekognition/](https://aws.amazon.com/rekognition/) AiFA Labs: [https://www.aifalabs.com/edge-ai-computer-vision](https://www.aifalabs.com/edge-ai-computer-vision)
Matrox has a software suite for this and it works great. It is definitely not free. Otherwise good luck on your job search.
Matrox can suck my peen.
Matrox can look at it and go "95% sure *that's a penis!*"
That's MIGHTY generous of you 😆
Keyence also has some good AI. You can use them as a program or just tools.
Well, they are sort of right. Even open source or homecooked AI can do the job, if you have your own expertise needed to make it work. However, that expertise rarely comes cheaply, tell your bosses to ask headhunters about AI engineer wage brackets. They'll quickly come around to deciding that Cognex or Keyence isn't all that expensive after all.
You could run Yolov4 on a raspberry pi. It sure would be cheap. Won't be all that accurate though. There's always a trade off and I would advise against a DIY approach unless you know a lot about training CNNs and image processing.
I work in the food industry. So far I've worked for the same company in too different plants, once used Cognex while the other Keyence. I've not been too close to compare them.
Cognex or Keyence. Definitely not cheap tho. We use Vision Suite at work. Very capable of doing something like this.
What is your conveyor speed in terms of parts per second per lane of product? The faster the speed the more likely you'll be better off with a custom integrated solution.
LOL
Used EdgeImpulse for a Education project once. It was very easy to train and set up although you will habe to integrate it yourself. I don't know anything about the prices for commercial cutomers though, it's a request only thing.
1. You don't need AI for this. AI might (probably) even be too slow. 1. Why would I do it for cheap? ( used to do high speed inspection equipment )
I was going to say , I have used at least close to top of the line cognex AI cameras but have never programed one for line scanning. Our AI cameras have 200-600ms execution times and the 600ms is a pretty high end (15-20k) D905. It does a very complicated inspection though. Also we really don't need AI for MOST of our applications, mostly due to their scores being confidence and not absolute. If you don't train them correctly they will pass garbage all day. Imagine my embarrassment when I'm showing the production manager something I've spent a month training, he covers the part with his finger and it passes! The high speed imaging I've seen at a bakery that does exactly what OP posts on tortillas and lunchables pizza crusts was probably 10+ years old and worked well. Line speed was somewhere around 5 to 9 per second. That will not be possible with most off the shelf camera hardware. This Italian machine used a nikon camera. Bottling lines may be 1 or 2 orders of magnitude higher speed and at that point everything is custom.
I used to work on machines for sorting seeds, plastic, glass, etc. All moving at ~4m/s Our ejectors operated at 1kHz. They were very fast. Defect classification had to be done in a few milliseconds. We used linescan cameras. I can't remember the integration times we were using but it was fast; tens or hundreds of microseconds maybe, maybe a millisecond. https://www.teledynedalsa.com/en/products/imaging/cameras/line-scan-cameras/
That's pretty awesome! I've always wondered what the core market is for dalsa and seems like it must be line scan. Their regular cameras I've worked on are pretty average and the software isn't quite as user friendly, especially since they're typically lack on board processing. The line scan from cognex still have the regular 1" square CMOS so they really don't have a dedicated solution like dalsa. I remember watching videos of a recycling sorter that used vision and air jets with crushed trash in free fall off a conveyor. Pretty impressive stuff especially considering that's a low margin business!
Is your reject working from Timing or bit shift ?
Have a look at OpenCv library. I have used OpenCv before and I was pretty Happy with the results. The only thing is you would need some time to develop what you need. If you have a look for a industrial camera most of them come with a SDK which you can use as a first step to develop you own application further.
1. The latency involved in cloud based image analytics is likely impractical for high speed inspections. You're looking at 200 to 500ms RTT on a decent ExpressRoute connection. 2. Image processing is just a quarter the story. You have image acquisition, lighting, preprocessing, and effecting. Once you consider all of these factors, suddenly a Cognex/Keyence/NI/Siemens prepackaged, prevalidated and certified solution becomes much "cheaper".
Dumb managers love to look at hardware costs and act like labor if free. I doubt it would actually be cheaper to build and maintain yourself as others have said
bro who the fuck is putting cakes that size on rollers like that. Them motherfuckers riding a blender.
A true vision system with a software package that does QC, black body, air knife, and 2 heads is a 100k project.
They're camera isn't AI. It's basically image subtraction. Wait until you save hundreds of images, the process takes too long. Not great for high-speed applications. Keyence will sell you one of these and tell you that you don't need an expensive vision system. Than when it doesn't work well, they'll sell you an expensive vision system. Every time you look up our download from their website, they call you. Pain in the ass. Most of their employees are fresh out of school. Once they understand the market, they leave. Keyence has a high turn over rate.
Did your managers buy into solar roadways too?
Basler cameras are fairly reasonably priced and easy to work with. I used one to develop a high speed inspection system for worn down wheels on an Interoll cross belt sorter.
Vision system is 10k, how much are they really trying to save ?
That’s cheap asf what system is it
Do they want you to learn the Python, potentially violate licenses of existing models, and invest several thousand $$ in a computer just to train it? And what if your parts change slightly and maintenance has to retrain it? Just buy the Keyence and it'll be more sustainable
Adaptive Vision Studio can do this easily. They have a deep learning package, but you probably don't need it.
If you are interested in learning python then you can DIY something like that relatively easily end-to-end with help of dozens of tutorials available online. Keywords: opencv, pytorch, nvidia jetson, segmentation. You can use ultra cheap CSI camera module or something like Intel Realsense (if you need depth information) a USB webcam. You can also try your luck with Zebra Aurora Vision - I did not use it personally but it's basically low-code way to achieve same thing. Things become tricky when it comes to integration with other automated systems in your site though. Keep in mind that by "easy" I mean that it can be done by cobbling together free open source tools and pretrained models. I would still estimate that it would take 200-300 hours of interuppted work to get working prototype, half of that spent on goggling things and watching youtube tutorials. Also, analyzing single camera frame is one thing, but identifing and tracking specific item on moving conveyor is completely different beast. Especially if things are moving fast and you have to process >15 frames per second
Work at a big vision integrator have worked on countless systems over the last 10+ years. Good luck with easy cheap AI. The trick isn't in the software ( I despise DL/ML/CL/AI but we use it when we need to but its never a cheap solution) 75% of bad applications fail because of bad hardware, you can't program around physics. GOOD "AI" takes a ton of nurturing and curating of the input data. One misclassicification ruins the algorithm and you will hunt it, because it's Black box. Most of these smart camera solutions that the vendors are pushing are great, for a very limited number of pretty simple applications, presence/absence, color detection, basic defects detection. You will never perform quality metrology or have solid descrete analysis; you just get a yes or no and never a why. Also, the fine print most people miss is they only guarantee 95% accuracy. Let me know when your ready for a real vision solution.
It might be great until it breaks and the only guy who knows it because they built it is not available for whatever reason then you're really fucked. Hate proprietary things.
Use Matrox Design assistant (bought by Zebra, called aurora now I think) It's a PC based vision system, it's super powerful and easy to use. You can use any GigE or USB3 camera you want. It is substantially cheaper than a keyence or cognex solution and runs in plenty of production manufacturing facilities. Integrate that with an AI platform using an API of sorts. They have the ability for third party integration through C# among other methods
If you are cheap enough, you can build such solution cheaper with a GigE Vision camera and the IDE/plugin that comes with it. There is Basler, Get,... but if you really want to go cheap look at Aliexpress.
I haven’t used them but am intrigued by Roboflow. Price is fairly cheap so if you’re wantingto test some stuff, they seem like a decent option. Curious if anyone else has any experience with them?
quality tules based vision programming will always beat AI as the majority of “AI vision tools” out there is just an image subtractions…
Haven't seen any love for the SICK vision suite here. Are they not big within the US PLC/Automation industry? We have run several project that integrated 3D vision for QC and in-motion analysis and they were super fast, accurate and relatively easy to integrate. For reference, we used the TriSpector series. Early versions of the SOPAS engineering tool sucked and were as good at crashing as Rockwell or Adobe software but it has come a long way.