. Testing the immersive interaction in a digital twin environment of a real scenario.
. Evaluation of AI-provider capabilities of automatically creating source code and 3D environments
. Evaluate and visualize in 3D data of the AI-provider neural network
Manufactuirng companies and asset provider - Software solution provider for digital twin and XR services
Report with recommendations and profiles of identified solution elements
Industrial engineers, systems engineers, manufacturing companies
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Feasibility report, measurement results
WPT technology provider
Feasibility report, measurement results
Robotics / Intralogistics technology provider
Feasibility report, measurement results
Robotics / Intralogistics technology provider / user
Feasibility report, measurement results
Robotics / Intralogistics technology provider / user
Feasibility report, measurement results
WPT technology provider
AI – based solution: 1) Automated workflow of production planning activities; 2) Automated data collection from market and specific clusterization of customer requirements; 3) Intelligent forecasting of market demand
Industrial Company – S&O planning tool provider
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
• 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
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