Netherlands

Position measurement and tracking system
Node:

High-frequency and high-accuracy measurements can help to understand flexibibity/modeshapes of flexible products, or help to understand dynamic behaviour of products in a pile or on a moving conveyor belt.

Robot learning by demonstration
Node:

To minimize time spent in programming how to perform a task, the user can teach the robot by demonstration. This can be done by first stearing the robot by hand, while monitoring its state. Eventually

Single and dual arm cobot testbed
Node:

Experiment with one or two Panda cobots to investigate if they can add value in the production line. A single arm could be utilized for product singulation, e.g. in a bin- or heap picking task.

Testbeds for mobility tasks
Node:

Experiment with mobile platforms that might be used in a manufacturing hall to get products from point A to B across the shop floor.

Technology providers: Test with exchanging manufacturing information across the value chain
Node:
Technology evaluation, demonstratror
Manufacturing companies: Experiment with exchanging manufacturing information across the value chain to enable the transition towards remanufacturing
Node:
Technology evaluation, demonstratror
Experimenting with human robot interaction
Node:
Demonstrator
Experimenting with & deploying digital operator support technology to shorten learning time and increase employability & quality
Node:
Technology evaluation
A proof of concept of how to deploy the Digital Product Passport across the value chain
Node:
Category:
Technology evaluation, demonstratror
Selecting Digital & AR-MR operator support technologies
Node:
Technology evaluation
AI Factory Planner
Node:
Demonstrate that application of AI reinforcement learning can greatly improve efficiently and reduce costs as compared to conventional heuristic production planning
Increase speed, decrease cost, seize control of high mix, small series manufacturing characterized by infinite shape & material variation by end-to-end integration, digitalization, and factory and operator intelligence opportunities
Node:
Evaluation of ability to leverage existing technology for high variability of parts
Sorting of parts in order to reduce complexity, improve control of high mix, small series manufacturing characterized by infinite shape & material variation
Node:
- Evaluation of ability to leverage existing technology modules to cope a higher variety of parts beyond what is currently possible. - The gained knowledge and infrastructure applied to new segments of applications & SMEs
Increase quality assurance by 100% high speed inline dimensional inspection for manufacturing characterized by defects, variation, customization, and/or complex organic shapes
Node:
- Evaluation of ability to leverage existing technology modules to cope a higher variety of parts beyond what is currently possible. - The gained knowledge and infrastructure applied to new segments of applications & SMEs
Identification of parts in order to reduce complexity, improve control&traceability of high mix, small series manufacturing characterized by infinite shape & material variation
Node:
- Evaluation of ability to leverage existing technology modules to cope a higher variety of parts beyond what is currently possible. - The gained knowledge and infrastructure applied to new segments of applications & SMEs
Flexible Assembly with AI powered learning
Node:
Technology evaluation
Identification of the position and location and picking up of the unsorted parts
Node:
Demonstrate that the existing technology can be leveraged (adapted) to be used for different objects