Comment:

Concerning Microsemi use case: Firstly, the knowledge and physical equipment already in place will have a lasting legacy within the MICROSEMI facility at Caldicot. This understanding and equipment will continue to be used on the original use case and expanded upon as explained in the next section.

There was a large lack of understanding at the beginning of this project about what could be achieved by the type of approach being undertaken within the project and whether it could produce results in a manufacturing environment. Now we have an answer, and the Z-Fact0r approach has been a great success.

NECO, as end user, has contributed to the estimation of the benefits Z-Fact0r platform would provide to the manufacturers. In the NECO case:

  • the direct losses for defective product manufacturing at the special flute grinding operation are between 10.000 and 12.000 €/year
  • considering a 25% scrap reduction at this very same operation (technical KPI set for Z-Fact0r, and objectively achievable), some 2.500-3.000€ would be saved yearly in the particular WALTER pilot grinding machine
  • inferring the same defective quantity reduction for all CNC machines due to the implementation of the Z-Fact0r solution, we might be talking about 15.000-20.000€ saved every year (this should be the final estimated figure window for the full implementation of Z-Fact0r at NECO facilities).

 

For bringing the Z-Fact0r solution to TRL 9, NECO would definitely support the Consortium intention of trying to find other funding opportunities for the future, especially in the form of other calls from the European Commission.

For manufacturing of metallic parts with less stringent dimensional requirements, the 3D scanning equipment is a fundamental part of the solution, especially if there are many parts being produced daily with the same geometry. This would allow for an automated inspection to be put in place and, if the production rate is too high, a significative number of samples could still be controlled and used for the PREDICT and PREVENT modules to be used. Of course, sensors in the machines need to be installed for enough data to be available in the machine learning processes. Then, the results could be applied not only to the samples but to all parts being produced. For products with larger added value, the robot deburring is a compulsory tool to use, as it eliminates the need of human intervention in rather sensitive tasks as are the elimination of defects originating in the production line.

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