STAM and VISKA will deploy a machine vision method based on NIR and RGB data on products proposed by Composite Industries, aimed at classifying faulty CFRP parts, allowing the automation of the quality inspection process of the components. Composite Industries will benefit from an automatic and more accurate manufacture of CFRP components: they will increase productivity, save material and money waste. STAM and Viska will benefit by commercializing engineering and consultancy services for the deployment of machine vision systems in various manufacturing scenarios

The experiment implements a data analytic stack that supports process control and optimization of Human-Robot-Collaboration (HRC) workplaces through synchronous data stream processing and machine learning. Possible benefits of the solution are Improving efficiency of HRC processes: decreasing cycle time 5-10%Improving quality of products in HRC industrial tasks: decrease the number of post-processed products 20% Empowering human safety and ergonomics in HRC: reduce the number of employees suffering from musculoskeletal disorders up to 90%

BRILLIANT pursues two main objectives towards autonomous uptake of collaborative solutions by SMEs by (i) developing smart, orchestrated and reconfigurable collaborative work cells to reduce adoption barriers of collaborative solutions for SMEs; (ii) combining the flexibility and dexterity of humans with repeatability of cobots towards artisanal manufacturing 4.0. The BRILLIANT solution will be implemented in the I-TEK’s tweezers production system. Possible benefits of BRILLIANT are -30% of the production time needed to perform the selected activities; +40% of the variability of workers’ jobs thanks to both extrinsic and intrinsic job variations and -20% scraps.

The mold with the prepreg ply is placed in front of the robot by an operator. The CAM software generates the lamination trajectories based on piece CAD and mold position, that can be adjusted through the HMI. The trajectories are translated into a robot program, that is performed by the robot arm using the designed lamination tools and their changer. The operator replaces the mold with the laminated piece and the process starts again.

The consortium (WOP and ABB AS) strives to demonstrate an alternative agile manufacturing technology in the laser micromachining industry based on the integration of the collaborative robotic solution with machine vision, force detector, and custom software into the micro-machining workstation. Possible benefits: 24/7 fabrication (4 times increase in production quantity with the same personnel); increase in production yield by ~200%; accuracy increased up to 50x.

The general objective of the project is to develop a novel computer vision guided collaborative control solution for mobile manipulator. The project will improve the manufacturing techniques of several industrial sectors, introducing a novel collaborative environment where robots interact with human workers.

During a proccess of touch-feeling analysis, a cobot with a multiple sensors (force, vibrations, displacement, some time sound, etc) is used. The results are comparedtoa human panel (number of persons that give an personal evaluations) experience that provides subjective evaluations. Possible benefits: Standardization of execution of testing methods with cobots. Possibility to reproduce in a optimal way the human movement and touch feeling with possibility to measure physical parameters (force, vibration, dimensions, etc).

The demonstrator will set up and demonstrate a CPPS for milling using the IOT platform Detact in an real working environment. It shows the smooth interaction of data acquisition from machine and process, data management and simulation modelsinto a CPPS. Possible benefits: The demonstrator implements a consistent, low-cost approach for a complete system, thus contributing to user acceptance and expanding the field of application of CPPS.

The biggest challenge of the positioning task for robots is getting the accuracy needed that is inside 1-2 cm constantly. To achieve this a combination of different sensors is necessary. Moreover, the achieved redundancy helps maintaining the integrity of the positioning information for continuous job in the lack of one of the signal sources (e.g. failure of one sensor). Possible benefits of this solution are that current manual methods can be replaced with digital technology, and this provides up to 7 times faster work process.

RAISE addresses the Robots as a service (RaaS)growing business model that allows companies to lease robots and tap into a cloud-based marketplace for technical (e.g. predictive maintenance and other service-tech offerings) and non-technical (e.g. fintech, insurtech, regtech,..) services to be delivered to the end user via connected equipment. RAISE will add an open and interoperable information model based on the OPC UA standard to interoperate the Equipment model with 3rdparty service providers (Insurers, Payers and Maintainers. RAISE aims to demonstrate potential eServices to be offered onto connected Robots accessible in the demo room of Mitsubishi Electric™ in Milan, one of the world leading Robots Manufacturers.Services will enable to monitor connected equipment, detect anomalies and insure productions.

The consortium wants to demonstrate the technological and economic feasibility of reconfigurable mobile cobotic production assistants (CPA) that can flexibly be used at the different workstations/machines to take over certain repetitive tasks of the operator. The operator responsibility will hence shift to ownerschip of the cell focusing amongst others on quality control and time-based planning of the cell to assure ultra-short leadtimes (quick response manufacturing). Possible benefits: The implementation of reconfigurable cobotic production assistants allows Malmar to 1) Automate certain repetitive/manual tasks (target at least 50%) such that operators can focus on value-adding tasks (improving quality: at least 25% scrap rate reduction), 2) Create a human-centered work environment where job content is more attractive, and 3) Produce small series of products in a cost/time efficient way (target: 10% order increase).

During this project we will demonstrate an innovative robot 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 human-machine interface for pre-programming the tasks and an integration with the ERP system. Possible benefits: Reduce the time spent on packaging preparation for production by 30%. Reduce packaging costs at least by 20%. .Reduce the required space for the packaging processes by 25% 4.Completely eliminate the dependence on the packaging suppliers. Only the raw materials will be required for the packaging production.

The proposed solution is expected to address human safety related challenges in steel industry, by proposing the automation of a demanding process that is currently performed by humans: High temperature robotized inspection system; Remote control, robotic operations assisted by human decision and supervision system; AR human operator support for maintenance tasks. Possible benefits are: 20% reduction of the time required to inspect a furnace during operation; improved quality of the final product, through the improved process of inspection and CO2 emissions saved thanks to material saving.

Together with Pickit, wo partners in the CEE region will setup local demonstrator cells for Bin picking of billets, shafts and axles with a focus on big parts (> size of your hand), big bins, big robots. Pickit wants to sell 50-100 shaft & axle systems in the next 2 years in the whole CEE region

Metal structures will be welded using the innovative "Dummy Tools" method (6DoF Measuring), preventing welding workers from exposing themselves to unnecessary risks. Collaborative robots will perform the heaviest welding activities, following the data provided by the dummy tools. Possible benefits: Current welded aluminium brands production capacity will be increased in 50%, delivery time reduced in 25%, reductiononthe scraps and quality defects in 30%. Will allow the human-robot collaboration to improve the operators work quality in 50% and reduce the injuries and labour illnesses in 80%.

The main objective of the ShipWeld project is to establish an integrated robotic solution that performs autonomously welding tasks in shipbuilding, leading to an increase in end-user’s revenues and welding quality while eliminating the need for human operators undertaking hazardous tasks. The project aims to reduce manufacturing costs for shipbuilders, and will increase worker safety by preventing their exposure to harmful welding radiation and toxic fumes. This opportunity will generate more than 302 new jobs within 5 years after market launch and will push the industry into the Shipbuilding 2.0 era

SpinEye - Methodology: HRI that enables humans to “teach” the cobot where to insert screws based on visual inputs from a camera, fast changeover between screw assembly tasks in agile manufacturing, accurately detecting screw holes utilizing the power of AI.ObjectivesO1: To create an AI-enabled vision-based system for robust detection of screw positions.O2: To build a teach-in interface for human-robot collaboration.O3: To build an Edge device for machine vision task incl. a Cloud infrastructure for trainingO4: To build a web-based UI for monitoring and continuous enhancement of the hole detection model.O5: To produce a machine vision product with a TRL 7 or higher.O6: To develop a business plan for co-exploitation and a dissemination plan for SpinEye to enter the market.

Deburring of welded seams by help of simulation, offline programming tools and vision to achieve flexibility and excellent quality. Possible benefits: Time to program new parts for robotic deburring will reduce over 50% which means also producing short series will become economically feasible.