Other Emerging and Enabling Technologies

Dimensional control of parts with robots and 2D vision
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Quality inspection in 2 and 3 dimensions: dimensional type (measuring dimensions and/or detecting burrs, lack of material, etc.) or of a superficial type, detecting defects such as cracks, scratches or any other type of poor

Autonomous navigation based on 2D and 3D slam
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2D Simultaneous Localisation and Mapping (SLAM) to indicate that robots explore the environment in which they are located using sensors, providing maps that will be used to locate them at all times by means of

Manufacturability tests
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Manufacturability tests of specific products: evaluation of the feasibility of using Binder jetting additive manufacturing to obtain specific products.

Prototyping and small pre-series production to validate the technology for specific components production.
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Design and production of small series of functional prototypes. Experimentation and validation of the designed solutions according to criteria established by the client such as efficiency, quality, cycle, etc.

Development of new products for Binder jetting additive manufacturing
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Design of new products with increased performance specifically designed to be manufactured using binder jetting technology: use the design freedom given by the technology to create new products with better characteristics. The design limitation will

Business case Feasibility
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Evaluation of new applications of components obtained by BJ: Study on the techno-economic feasibility for the manufacture of components using BJ.

Force/compliance-based robot guidance
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Traditionally, robots are capable of repeatedly positioning a tool to perform tasks that do not require contact and/or a priori knowledge of the arrangement of the objects with which the robot must interact (picking up

Model Training Service
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General hardware & software services for model training can be provided to reduced datasets, just to show the potential to current industrial needs. Notice that pre-trained models will be provided by default, and specifically related

Data Augmentation/Annotaion Service
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General hardware & Software services for data augmentation can be provided to reduced datasets, just to show the potential to current industrial needs. To be applied to big datasets or production environments, a specific consultancy

Time Series Forecast (TBD)
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Procedures that, integrating AI/ML algorithms, make it possible to check the predictive potential of a time series. It will speed up and reduce risk when delving into more complex AI/ML-based projects. A benchmark of different

Systematic pattern extraction
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Service that allows extracting its characteristic (systematic) patterns from a data set of individual patterns. The applications are very diverse from consumption analysis, machine behaviour analysis, etc. This will allow claimants to identify systematic behaviour

Confidence AI explainability service
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General hardware & software services for using explainability libraries in specific industrial use cases can be provided to reduced datasets, just to show the potential to current industrial needs. Notice that pre-trained models will be

AI technological services associated to industrial use cases to show potential use cases
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The goal is to facilitate the understanding of key AI technologies within clear industrial use cases (e.g. reinforcement learning applied to robotics (arm or drones), explainability applied to anomaly detection, damage detection and assessment, ROI

Proof-of-concept for technology providers
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Support to Hardware/Software technologies development and validation through integration support and testing.

Didactic and virtual environment testing.
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Provisioning of access to AIMEN´s digital infrastructure (storage and computing capabilities) for the deployment of digital tools and solutions and their testing under virtual scenarios (cybersecurity solutions, distributed approaches, validation of decentralised tools -DPP-, etc.).

Data preparation and curation, interoperability pipelines provisioning.
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Data interoperability and digital threading (closed-loop digital pipelines provisioning) services through open-standard protocols allowing asset interoperability and maintaining cross references and data integrity, among different manufacturing domains (IT/OT convergence), avoiding the dependence on proprietary solutions

Proof-of-concept for technology providers
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Support to digital solutions development and validation (cybersecurity solutions, platform modules, services, etc.) through integration support and testing (interoperability, connectivity, compatibility) in the AIMEN digital infrastructure.

Data enrichment and dataset provisioning.
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Data elaboration based on existing manufacturing datasets and provisioning of industry-relevant collections of manufacturing datasets linked to the production systems and capabilities offered by AIMEN (Composites manufacturing, AM, welding, cutting, etc.) ready to be used

Characterisation of control and quality control systems (AI based) using real time Physically based digital twin (PBDT) of physico chemical processes (material transformation processes and surrounding environment) Virtual manufacturing facility and sinthetic process data sets
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Construction of physically based digital twins of material transformation processes (for instance: injection, extrusion, stamping, peen forming, forging, RTM, 3D printing, chemical reactors, etc) and surrounding production environment (for instance: ventilation, pollutants distribution, etc.) to

Characterisation of control and quality control systems (AI based) using physically based simulation (PBS) of physico chemical processes (material transformation processes and surrounding environment) Generation of domain knowledge and sinthetic process data sets
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Construction of physically based simulation models (continuous) of material transformation processes in manufacturing (for instance: injection, extrusion, stamping, peen forming, forging, RTM, 3D printing, chemical reactors, etc) and surrounding production environment (for instance: ventilation, pollutants

Automatic entity extraction from unstructured documents data
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- enriched database, structured company knowledge and automated knowledge-intensive processes.
Monitoring and diagnosis of AI-system for manufacturing
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AI-based solution able to: 1) Monitor properties or faults 2) Predict failures or estimate unobservable parameters 3) Identify root causes
Validation of Vision Based Systems for 2D/3D Dynamic Scene Understanding in Manufacturing
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- Validation of system performance, - highlighting weakness and suggesting possible improvement
Validation of Vision Based Systems for 2D/3D Dynamic Scence Understanding in Manufacturing
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- Validation of system performance, - highlighting weakness and suggesting possible improvement
Validation of Metrology Based Systems for Quality control in Manufacturing
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- Validation of system performance, - highlighting weakness and suggesting possible improvement
Characterization of active and passive sensors in a metrology lab
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- Validation of system performance, - highlighting weakness and suggesting possible improvement
Software Engineering process revision for AI applications in Manufacturing
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AI-based software suitable for manufacturing
Software Engineering process revision and validation of AI-based software solutions for manufacturing
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AI-based software suitable for manufacturing
AI-based software solution testing with automatic test case generation
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AI-based software for manufacturing where each application feature works as per the identified software requirements
Validation of AI models for time series forecasting and anomaly detection in manufacturing
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Optimized AI model for time series analysis and forecasting tailored on the specific industrial need
Monitoring and Optimization of AI-based application in the IoT – Edge continuum for Smart Manufacturing
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AI-based applications in the IoT-Edge continuum for smart manufacturing optimized
Synthetic data for training machine learning models
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Experimentation with the concept of training machine vision solutions with the use of synthetic training data. A set of reference parts will be used to train your machine vision solution. The result of the service

Provision of test data for electron micrographs of nanoscaled particles
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AI developers can use physics based test data to validate their image analysis methods, test report
Certification of the quality of AI-based compression of CT data
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AI developers can use test data to optimize their CT compression methods, test report
Identify relevant Tests, Experiments, and key partners towards enabling or prooving maturity of AI solutions for integration and deployment
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The service must enable the company to initiate further test or experimentation services
Testing vision based geolocalisation technologies in specific industrial context
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Verify that the technology meets the requirements in manufacturing context
Give acces to an environnement that enables SMEs to test and experiment their own AI-based solutions
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Supporting SMEs in the test of AI based solutions for manufacturing applications
Model Based Systems Engineering (MBSE) services to specify and design complex industrial systems.
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Supporting SMEs in the design of complex systems for manufacturing applications
Testbeds for mobility tasks
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Experiment with mobile platforms that might be used in a manufacturing hall to get products from point A to B across the shop floor.

Factory ML/ML ops
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technology evaluation
ML Data Pipeline Testing
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technology evaluation
Data and Feature Engineering for ML
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demonstrator
Intelligent sensing systems analyses, deployment and testing (advanced signal and data processing).
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1) Data collecting 2) model training
Assistance with power converters and industrial electrical drives setup.
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1) Requirements collecting 2) data processing 3) creation of models 4) decision automation
Control algorithms development support for electrical drives and power electronics.
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1) Improving system features 2) Increase system robustness to sensor failures or outages 3) Improve energy utilisation
Diagnostics of drives and machines
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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
5G industrial communications testing and development support
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1) proved applications of 5G communication for distributed computing environments ready for AI implementation 2) verified performance of comunication in distributed AI system
Edge-continuum apps testing and development support
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1) Analysis of suitability of different computational architectures for AI implementation br2) optimization of AI algorithms implementation for affordable use on industrial HW