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Identification of parts in order to reduce complexity, improve control&traceability of high mix, small series manufacturing characterized by infinite shape & material variation

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Service description

“By using this Identification Service SMEs can learn how to deal with the complexity of the infinite variety of parts and/or application of new manufacturing processes which they will encounter while transforming to digital and/or small series manufacturing. Services accelerate the complete journey, from first demonstration up to final business-casing, with the goal to reduce complexity, improve control&traceability of high mix, small series manufacturing characterized by infinite shape & material variation. This identification service is using the vision-based object recognition solution to quickly identify based on geometry each part after each manufacturing and logistical step. The artificial intelligence capabilities are used to make the match between the digital 3D file and what is ‘seen’. “
Expected results: ‘- 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 – Technology modules enhanced to the most prominent cases.
Methodology: ‘- Demonstration of current capabilities – Feasibility study assessing SME specific processes – Testing and Experimentation with different types of parts, e.g. metal parts or parts of different colors – Customization to address new and impactful use cases
Target: User
  • Type: Experiment
  • SUT/E: Manufacturing workflow automation in high-mix industry
  • Contact: contact@ai-matters.eu

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Co-Funded by the European Union Under grant agreement number 101100707

Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or the Directorate-General for Communications Networks, Content and Technology. Neither the European Union nor the granting authority can be held responsible for them.

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