1) proved applications of 5G communication for distributed computing environments ready for AI implementation
2) verified performance of comunication in distributed AI system
N/A
AI-based software suitable for manufacturing
Robot provider, tool Provider
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Verified AI agents in desired scenarios
Not specified
Result delivered varies according to selected use case, see the methodology list
Not specified
The results differ according to selected scenario, see the methodology list
Not specified
Documented application and system requirements relevant to drive and converter setup
Processed and evaluated operational or measurement data supporting parameter selection
Model or structured representation of the drive-system behaviour where required for the agreed scope
Recommended parameter settings or configuration strategy for the intended application
Where applicable, decision-support or automated parameter-selection approach to support repeatable drive configuration
Manufacturers, machine builders, industrial equipment operators and system integrators using power converters or electrical drives and seeking support with parameter setting, application-specific optimisation or automated configuration.
Simulation model representing the agreed manufacturing system, equipment or process scope
Results of the evaluated simulation scenarios and analysis of relevant system behaviour
Assessment of model assumptions, fidelity and limitations
Independent verification of the proposed technical solution where applicable
Model and processed data suitable as a basis for digital twin preparation or further AI-based analysis
Technical report summarising the model, evaluated scenarios, simulation results, identified limitations and recommendations for further development
Manufacturing companies, machine and equipment developers and system integrators that need to evaluate new systems, process modifications or operating scenarios virtually before physical implementation, or prepare models for digital twin, optimisation or AI applications.
Improved or newly developed control strategy for the agreed electrical drive or power-electronic application
Evaluation of system performance, reliability, robustness and energy efficiency against agreed criteria
Assessment of system behaviour under relevant sensor failures or outages were included in the test scope
Identification of technical limitations and opportunities for further optimization
Recommendations for further development, implementation or experimental validation
Technical report summarising the analysed system, applied methods, test results and recommended improvements
Manufacturers and developers of electrical drives, power converters, power-electronic systems and industrial equipment, as well as system integrators seeking to develop, improve or validate advanced or AI-assisted control algorithms.
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.
Industrial plant Provider
1) Exploitation of AI methods as enabler technology for reliable predictive maintenace
2) Increased reliability and availaility of industrial actuators and machines based on reliable diagnostics with AI methods use
3) Datasets for “offline” experiments with AI methods
N/A
Industrial plant Provider
1) analysis of suitability of different computational architectures for AI implementation
2) optimization of AI algorithms implementation for affordable use on industrial HW
N/A
System model developed or refined for the agreed testing scope
Results of system testing and experimentation, including evaluation against agreed requirements and operating conditions
Identification of relevant system behaviour, limitations and potential issues identified during testing
Recommendations for further development, integration or prototyping
Validated basis supporting faster and lower-risk prototyping
Manufacturers and suppliers of electrical components and systems for industrial energy applications that need to validate component behaviour, support system integration or reduce technical risks during development and prototyping.
Collected and processed drive-system data relevant to the agreed optimisation task
Evaluation of drive behaviour and identification of relevant optimisation opportunities
Recommendations for improving drive configuration, operation or performance for the specified application
Where applicable, data-processing or AI-assisted decision method supporting automated optimisation or parameter selection
Technical report summarising the analysed data, identified optimisation opportunities, evaluation results and recommended actions
Manufacturers of electrical drives and industrial machinery, system integrators and industrial users operating electric-drive systems that need to analyse drive behaviour, extend available measurements or optimise system configuration and operation.