1) Different type of optimalization
2) Data processing and collecting for AI assisted decision
Industrial plant Provider
1) Different type of optimalization
2) Data processing and collecting for AI assisted decision
Industrial plant Provider
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System or component model developed or adapted for the agreed HIL testing scope
Results of system, control and integration testing under agreed operating scenarios
Identification of unexpected system behaviour, integration issues or functional limitations
Evaluation of the tested control or AI-assisted functionality against agreed requirements
Recommendations supporting further development, integration and faster prototyping
Manufacturers, automation technology providers, control-system developers and system integrators developing control software, control algorithms or AI-assisted automation functions for industrial and manufacturing systems.
Verified scenario/components
Innovation manufacturing, integrators, component providers
Collected and processed sensing data relevant to the agreed industrial use case
Assessment of data quality and suitability for monitoring, optimisation or modelling
Identification of relevant patterns, operating conditions or potential anomalies in the measured data
Trained data-driven or machine-learning model where applicable to the agreed use case
Processed data and model outputs suitable for further optimisation, condition monitoring or virtual system development
Manufacturing companies, machine and equipment manufacturers, industrial technology providers and system integrators seeking to use sensing and production data for condition monitoring, process optimisation, predictive analysis or system modelling.
Verified LLM based system in desired operation environment
Not specified
1) proved applications of AI in mobile robots
2) verified safety of robots in human-robot cooperation
3) verified performance and reliability of human-robot cooperation systems
N/A
1) Production optimalisation
2) Time saving
Industrial plant Provider
Evaluation and validation of the monitored production process against agreed process and quality criteria
Identification of process weaknesses, anomalies and potential improvement opportunities
Assessment of the suitability of available data and monitoring infrastructure for AI-based quality assurance or process control
Recommendations for data acquisition, data processing and further implementation of AI-based monitoring or control methods
Technical report summarising the analysed process, applied methods, evaluation results, identified limitations and recommended improvements
Robot manufacturers, robotic cell providers and system integrators for manufacturing applications
Analysis of the existing production-planning problem, available data and relevant constraints
Optimised production plan or scheduling approach for the agreed manufacturing use case
Comparison of alternative production schedules against agreed planning criteria
Identification of opportunities to improve resource utilisation and reduce manual planning effort
Recommendations for further implementation or integration of the AI-based planning approach
Technical report summarising the planning model, evaluated scenarios, results, identified limitations and recommended next steps
Manufacturing companies, production-planning solution providers and system integrators seeking to optimise production schedules, machine and resource utilisation, production capacities or internal logistics using AI-based and optimisation methods.
Validation of system performance against agreed test scenarios and evaluation criteria
Identification of performance limitations, weaknesses and relevant failure cases
Recommendations for improvement of the AI algorithm, system integration or robotic cell operation
Validation report summarising the test setup, performed tests, results and recommended improvements
Robot manufacturers, robotic cell providers and system integrators for manufacturing applications
Technical validation dossier;
Performance benchmarking results;
Grid stability and optimisation assessment;
Identified bottlenecks and mitigation strategies;
Recommendations for scale-up to real factory deployment
IT, Energy
1) Production optimalisation
2) Time saving