We have promised you a visit to our ICO in Paris. And here we are. I am with Regis Pageon, who is our site director, and he will take us through this fascinating experience here. So, Regis thanks for having us. You're welcome. What is an ICO? So, an ICO is a real factory with real production, invested by the BCG, and created by the BCG to show to our clients, to our industrials, how the new technology could improve, could be a lever to improve the performance of the production. Okay, very clear. We have looked at different technologies in our course videos, and I am looking forward to seeing how those technologies work in the real world? Yeah. And so this is the goal in fact of the ICO is to show the technology in action during a real production. So, I will just explain you on this first station, that is in fact the quality inspection station. So, we have implemented three main technologies. So, the first one is the MES. In fact, this is the Manufacturing Execution System that will do the link between the order of the clients and the production. For the scheduling, for example, also you will see to guide the operator on each operation they have to do, okay? So, you could see the tablet. And the operator will open an order of production, and you'll see display on screen also, that you could have many information concerning the product. We have to insert in the line with indication about the serial number, the different variances for example, the due date, data time and so on. And an information concerning the operation he has to do with 3D models, with videotex, anything you want in fact to explain to the operator what he has to do. So, after the MES, in fact, we'll send directly to the augmented reality the right checklist according to the product we have at this station, okay? So, I will just change to show you the augmented reality. And that can adapt to both the scooter, because I know that's what we're seeing right now the scooter production, but also to other products. Yeah, sure. In fact, the goal is to guide the operator to save time and training first, and also to manage the diversity because the operator is limited by his memory. And now the memory is in the systems. So, it allows you to manage more and more variances without having to retrain the new operator or retrain the operator in case of introduction of a new product, for example, so you will manage more and more diversity. Okay. Okay. So, with augmented reality you can see the real show see. Okay? And you can see this 3D model of the parts we have to check. So, the use case that is presented here is a check by vision or by touching, but it could also mix with other devices to make the check bin automatically done by complex devices as 3D camera for the measurement if you want or anything else. But at first, for the operators just to select the part check if the part is okay. Yeah. And fill the form if the part is missing, you will see this 3D model that will change the color, or perhaps this part is not confirmed or this part is confirmed. And do the same for the second part, and so on, and so on, and so on. Okay. So, augmented reality basically guides the operator really step by step on what he needs to do. So, he looks, he validates and that all flows back into a data aggregation system that then gives you the status of your square. Yeah exactly. The goal, in fact, once again is to guide the operator and avoid the mistakes that can be done by the operator because we are paperless. So, the operator searching in papers, in files that are perhaps not updated or in files that he has to fact to find the right procedure. So, to recognize the right product and find the right procedure and could do mistake. So, this is the system that will guide to avoid all the mistakes and save time. Okay excellent. And then where does the scooter go from here? So, the scooter in fact before the transfer, we will use a certain technology connected also with the augmented reality and the MES. And we are using in fact the RFID. So, the radio frequency through this antenna, we will write in this memory the characteristic of the scooter in order to be read at each station. And once again, one at the first station we will read this information, we will be able to display on the tablets the right tag instruction according to the product we have at the station. So once again, no papers and no possibility for the operators to do mistakes. So, that's an element of Internet of Things where you have every element in the factory here has an identifier that knows if that's a scooter or a drying machine. Exactly. So, it could be a scooter, it could be a drying machine. But you could also have all the options, all the variances for the same scooters, you could have different variances with mirror, no mirrors, colors, different body design, what you want. And all is right here in this tag. Okay. So, once the control is okay and we have entered all the characteristics in this memory, we will transfer the chasis directly on this automated guided vehicle that is autonomous and allows to remove the non added value to move one part from one station to another with a forked diver for example and so on. So, this kind of robot is very autonomous and is flexible for you to change to different flows of production if you want with a very easy programming. Okay. So, let's go to the next station. Let's go. So now, I would like to show you the first station where we will assemble the wheel of the scooter. So, the weight of the wheel is 15 kilograms so it's quite difficult for the operator to lift this kind of a load. So, we have decided to Implement a collaborative robot. So, a collaborative robot is in fact a classical one but it it could be different that will detect the contact with an obstacle or with the operator and stop immediately motion. So, it allows you to work very closely in a collaborative mode with the operator and the robot. So, first, during the introduction of the chasis, the robot will automatically take a wheel and to push the wheel across to the chasis and the operator will take manually the robot and finally adjust he position. Okay. Okay. So, the first part is completely autonomous, and then the operator is coming here only to adjust the last final details. Yes exactly. So, what is interesting with the collaborative robot in general is that due to this functionality to stop the motion in case of contact, you will be able to place a robot without having to implement fencing and safety cell. So, it allows you to implement this kind of robot on an existing plant without having to redesign the plant, and also to work together with the operator. And again, you told me that this is a programmable robot. So, you can program to take the wheel, but you can also program it to work with a dryer machine rather than a scooter. Yeah exactly. In fact, you can see at the first station we have the scooter and the robot will help the operator to assemble the wheel. But at the second station if we have a table dryer, the robot will take the sides of the table dryers because the robot is connected to the PLC and connected to the MES and will receive the order of production so he knows exactly what is the kind of product we have at this station. So, what is also very interesting is that with the corroborative robot, not only this one but all the other models also, the interface are very user friendly and you don't have to be an expert in robotics to program them. So, you just have to move the robot and press the button to the position, move the robot again in the second position, and so on, and so on, and the robot will repeat the motion. So, the operator can do the program by himself. Okay. I like it a lot. And I like this idea of how training is also transformed with different technologies, right? And I want to take us to the next station where training operators becomes also much faster than how we usually used to do it in plants. Yes. Can we go there? Yeah. So, now I will show you a sub-assembly station because we have to train our operators, we need to have a tool to guide them once again. And we'll show you how this new technology would help to train the operators. So, you will have all the work instruction directly be projected in the table but is not that sensitive. But the system will recognize my finger and allows me to change the step. Okay. Okay? So, you could have some ends with different lights that show you where to place the part, how big the parts directly with the lights, the big two lights and place the part at this position. And click next. So, you have a control on this part about the electronic components. Click next, see the arrow to place the part, okay? Next. You could do an inspection just by pressing the camera. We will take a picture. And if the assemble is okay, I could go to the next step. If the assemble is not okay, I would be blocked in this step and time, okay? So, this is where you have to train your operators and save time for the training because you will just train the operator to use the technology. Your trainer will not stay with the group of trainees all the day. The trainer will train how to use the technology and go to another group for example. And I liked when you told me that this is not really augmented reality, it's projected reality. Yeah exactly because we're not add a virtual element on the wheel view. This is quite different. Yes. And Regis there is one last thing that I would like to show here in the ICO which is additive manufacturing. Yeah. We have talked about it in the course, and I'd love to see what you're doing with it in here. Okay let's go. So, now we will see the additive manufacturing. In fact this is 3D printing. The first use is in fact the first prototyping where you could also it allows you to make different designs that are not possible to do with the classical machine, for example, or to create spare parts for the tools or for the product and so on. So, you have a multiple in fact usage. So, the idea here is that we're having the scooter, but we're not going to build all the spare parts with the scooter when it's first manufactured? We're going to build them once they're needed. Yeah sure. You can produce on demand. Fantastic. I love it. So, Regis, thanks a lot for having us here in our Paris ICO. And I'm looking forward to coming back for a longer and more extensive visit. Thanks for coming. Thank you.
