The main objective is to increase the agility level of Composite Industries production line, by automating its quality inspection process of carbon fibre components by employing a machine vision system.
AURORA is a data stream processing experiment that supports process control and optimization of Human-Robot-Collaboration (HRC) workplaces through data stream processing and machine learning. The experiment is conducted on behalf of a finishing process for car exterior clay models.
BRILLIANT's objective include the creation of a testbed, a working cell, which selects the right technologies for the Ideal-tek work cell and optimises the process parameters for an automous uptake of collaborative solutions; and the promotin of an artisanal manufacturing 4.0, combining human flexibility with the repeatability of cobots.
The main objective of CANNIER is to develop a flexible robotic cell for the automatic lamination of carbon fibre reinforcements that have been pre-impregnated (prepreg) with activated resin, making the process more agile and sustainable. To achieve these results, tailored robotic end-effectors and a CAM software for the computing of the lamination trajectories will be developed.
The goal of the project is to create an alternative agile manufacturing technology that will increase production and will be based on a collaborative robotic solution, applying the machine vision, force detector, and custom software into the micro-machining workstation.
The mobile manipulator developed across this project will fill the gap between human and robots in industrial environments. The solution proposed integrates mobile manipulators into hazardous manufacturing lines, as the novel platform bring them with higher rates of flexibility to detect the environment and navigate through them.
The project aims to install a cobot with multiple sensors, which will be able to provide subjective evaluations similar to those of a human panel, reproduce human movement and touch feeling as well as measure physical parameters (force, vibration, dimensions, etc).
The aim of the demonstration is to develop a mobile demonstrator for a CPPS in the field of manufacturing, in particular milling. The demonstrator will show the smooth interaction of data acquisition from machine and process, data management and simulation models. The analysis of the process and the resulting quality of the machined part will be based on real process data, not only on simulated data.
The goal of the proposed experiment is to demonstrate the feasibility of an automated switching mechanism between indoor and outdoor positioning technology that yields transparency for the user in the use of positioning sensors. We have already selected the sensor set and we are working on the module.
RAISE is an interoperable information model, based on the OPC UA standard, that provides technical (e.g. predictive maintenance) and non-technical (e.g. fintech, insurtech, regulatory technology) services to the end-users through interconnected equipment, such as detecting anomalies or insuring productions.
The RECOPRODAS demonstrator's main achievement is the development and feasibility demonstration of a production assistant in the form of a mobile cobot unit dedicated to a cell. The cobotic production assistant (CPA) can be docked to any machine within the cell through an innovative docking mechanism ensuring mechanical alignment, electrical, and pneumatic power to the CPA and I/O signal exchange between machine and CPA. Inside the cell, the human operator decides which task the cobot should execute for the production batch at hand.
RoboCUT is an innovative robotic solution which automatically optimizes and maps the layout of packaging liners on standard cardboard sheets, cuts the layouts and prints the package codes ensuring a flexible and rapid product life cycle.
The purpose of the Robs4Steel demonstrator is to robotize the visual inspection in the refractory of the furnace after every tapping of liquid steel. This will allow operators to guide the robot around the furnace refractories remotely and assess them through the help of a heat resistant optical camera.
With SHAFTS, we demonstrate to shaft and axle manufacturers that bin picking cells are today reliable and that the installation time is limited (< one week). We do this by organizing local events for interested customers where we demonstrate 24/7 running bin-picking cells.
With the use of the "Dummy Tools" method, collaborative robots will perform the heaviest welding activities, thus preventing welding workers from exposing themselves to unnecessary risks, increasing aluminium capacity production and quality, as well as reducing delivery time.
SHIPWELD project has developed a robot programming system utilising a HTC Vive tracker as a user interaction wand. Preliminary welding tests with good results have been sompleted so far.
" The SpinEye project incorporates a human-robotic collaboration, premised on AI vision-system, which detects screw positions, provides Cloud inrastructure for training, monitoring and enhancement of the detection model. "
VisDeburr demonstration will illustrate the power of visual-guided deburring: measuring the location and size of the welding seams improves remarkably the quality of grinding and makes it much more flexible.
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