Testing activities needed to validate the following features: – bottleneck identification – multi – scheduling scenarios proposition based on machine learning concept – test and validation of multi-objective optimization function.
Industrial scheduling platform activities
Demonstrate that application of AI reinforcement learning can greatly improve efficiently and reduce costs as compared to conventional heuristic production planning
AI-User - manufacturing companies that want to improve efficiency of production planning and resource management.
Validation of the industrial simulation model for the selected process
Test of the information flow among the physical and digital and virtual world.
Manufacturing companies and asset providers - Software solution providers for digital twins
. 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
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
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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
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
User - Manufacturing SME's seeking to improve product quality and efficiency of the inspection process
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
Developers of 3D coordinate data evaluation algorithms can document level of agreement of their data fits with reference data
Developers of 3D coordinate data evaluation algorithms / Manufacturers of 3D coordinate measurement systems