User - Manufacturing companies operating in high-mix, low-volume and high-complexity environments that need reliable part identification to automate post-processing
User - Manufacturing companies operating in high-mix, low-volume and high-complexity environments that need reliable parts handling and baggibg to automate post-processing
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• Validated AI-based pallet loading optimization tool
• Improved loading efficiency and resource utilization
• Adaptation of the tool to product variability
• Benchmarking results demonstrating performance and scalability
• Readiness for deployment in industrial environments
Deliverables: Comprehensive technical report (specification analysis, algorithm adaptation, dataset preparation and training approach, implementation and benchmarking results), validated optimization tool (prototype level), performance evaluation results and recommendations for industrial deployment
Manufacturing (e.g. aluminum products, discrete manufacturing) Logistics and warehousing Packaging and supply chain operations
Evaluation of ability to leverage existing technology for high variability of parts
User - Manufacturing companies operating in high-mix, low-volume and high-complexity environments that need reliable part post-processing automation for high-variation manufacturing
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.
User - Manufacturing companies operating in high-mix, low-volume and high-complexity environments that need reliable part identification and sorting to automate post-processing
Report (on prioritised use cases and a short evaluation for the top few).
All.
User - Manufacturing SME's seeking to improve product quality and efficiency of the inspection process
The service is meant to support the implementation of artificial intelligence and machine learning models for the continuous analysis of sounds and noises generated, for example, on production lines and in plants (such as vibrations, knocking, friction, airflow, and acoustic alarms). The expected result is a validated AI-based solution able to analyze audio for different purposes such as: (i) early identification of anomalies or faults through the recognition of “unexpected” acoustic patterns compared to normal operations; (ii) generating operational insights to improve personnel comfort and safety (e.g., noise reduction).
Manufacturing companies, Equipment provider, OEM
Report with analysis results and recommendations
Companies in the context of production systems and industrial manufacturing
A documented demonstration of the annotation tool, including evaluation of annotation functionality, dataset management, and synthetic data generation capabilities, with recommendations for further application in AI-based vision workflows.
Fremstillingsindustrien, Machine vision, Kvalitetskontrol og inspektion, AI-dataklargøring, Industriel software og digital engineering
Early detection of potential equipment failures, reduced maintenance costs, minimized unplanned downtime, improved predictive maintenance strategies, and enhanced operational continuity through proactive alerts.
Manufacturing & Automotive - Providers of AI based solutions for manufacturing
Deliverables: Consolidated data reports, AR/VR application demonstrations
Technology providers interested in testing their developed AI-based human-robot collaboration solutions with AR or VR tools. Industrial end-users wanting to improve flexible production using AI-based tools for operator guidance, personalization of instructions and interfaces.
Customer required infranstructure: use case scenario definition, operational constraints, equipment information, or existing models and algorithms