A documented assessment of whether 3D CAD-based vision can solve the specific production task, including solution options, demonstration results, and a comprehensive report with recommendations for next steps.
Circular economy, Factory-Level Optimisation, Human-Robot Interaction, Computer vision, Other emerging and enabling technologies
Technology evaluation, demonstrator
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Full visibility into the product life cycle, improved transparency and compliance, reduced waste, more informed decision-making, and stronger sustainability efforts through complete traceability.
Manufacturing & Automotive
Test and validation of existing advanced AI-based solutions that can add health monitoring and predictive maintenance functions, with which the plant could predict potential failures before they occur and could provide the suggestion on how to solve them.
Tool, machinery and equipoment provider
Report with recommendations and profiles of identified solution elements
Industrial engineers, systems engineers, manufacturing companies
Tech provider benefit: Access to advanced RSW and monitoring testbed for assessing the feasibility of different sensing technologies, and the development/retraining of AI-based Quality Assurance solutions.
End User (Product) benefit: AI-based system for Quality Assessment of RSW applications with low data requirements.
Deliverables: Consolidated results reports, Performance assessment reports
Technology providers want to develop and validate AI-based quality assessment and monitoring processes for robotic systems.
Industrial end-users that are interested in enhancing welding quality and optimize processes using AI-based monitoring and sensing technologies.
Infranstracture customer needs to provide: Sample parts, materials, or components representative of their welding processes for testing and validation.
Report (on prioritised use cases and a short evaluation for the top few).
All.
The service must enable the company to initiate further test or experimentation services
SMEs needing a clear vision of the stages leading up to the industrialization of an AI-based solution
Reduced waste, improved identification of reusable components, enhanced resource efficiency, greater sustainability in production processes, and streamlined re-manufacturing through AI-powered assessments.
Manufacturing & Automotive - Providers of AI based solutions for manufacturing
Function prototype and evaluation report
SME with complex manufacturing systems or products
A validated anomaly detection performance report;
A risk and deviation analysis profile
Identified data gaps and model weaknesses
Optimization recommendations (technical & operational);
Evidence base for market uptake, certification, or regulatory dialogue;
Optional pilot validation in a near-real environment
Not specified
Collected, cleaned and processed industrial data suitable for further analysis
Assessment of data quality, completeness and suitability for the agreed AI or analytical use case
Identification of relevant patterns and relationships in production, quality, machine or maintenance data
Quality, production or maintenance prediction model where supported by the available data and agreed scope
Evaluation of prediction performance, limitations and relevant influencing factors
Recommendations for further data collection, model development or implementation of AI-assisted decision support
Technical report summarising the analysed data, applied methods, results and recommended next steps
Manufacturing companies, industrial technology providers and AI solution providers that already collect production, quality, machine or maintenance data and want to use these data for prediction, optimisation or AI-assisted decision support.
Evaluation report
Manufacturers and generally SME experimenting with heterogenous data sources typical for factories
A functional URCaps plugin or validated prototype with documented functionality, integration recommendations, and next steps toward further development or implementation.
Manufacturing, Factory-Level Optimisation, Human-Robot Interaction, Circular Economy, Robotics and automation
A validated vision and AI solution concept, prototype, or subsystem with documented performance, integration recommendations, and clear next steps for industrial deployment or further maturation.
Manufacturing (discrete and process), Circular economy applications (sorting, recycling, remanufacturing), Logistics and intralogistics, Other industrial sectors requiring robust automated visual inspection or perception.
Digital Prototype or Feasibility or evaluation report
Hardware provider (machinery, AMR, AGV) or user