AI-PRISM

#AIPRISM25: Use case – VIGO Photonics

The AI-PRISM consortium holds the necessary expertise to strategically improve the EU Smart manufacturing value chain in four domains: collaborative environment, robot perception and recognition, robot programming and human factors. We are working to achieve the right trade-off between complementary and overlapping among the industrial partners.

In the industrial category, we count on use case partners with experience in actual market product development and industrial activities such as VIGO Photonics. Together with the other four use cases, we generate a broad range of user-centred requirements, deployment blueprints, integration plans, testing scenarios, and performance monitoring to assess preliminary designs and feed the next iterations.  

VIGO Photonics pilot site covers the electronics (semiconductors) manufacturing sector in Vigo, Poland. They area European manufacturer of semiconducting materials and instruments for photonics and microelectronic, specialized in MWIR and LWIR detectors and modules, produced with the use of internally developed technology. With 35 years of experience, the company produces over 15000 devices per year, including 5000 detectors with unique hyper hemisphere lens (with growth tendency). 

Today, this industrial partner shared a video to explain more details about their company and mission to provide fast and convenient, easy to use IR detectors at any wavelength from 2 to 16 µm, reaching fundamental BLIP limits without cryocooling. Modules are available with different spectral response ranges, time response characteristics and gains. At their facilities in Poland, there is room for AI-PRISM innovations and the automatic positioning of the electronic component against the wire, to be glued, with the support of electromechanical or/and pneumatic effectors. 

Due to the delicate nature of the components and variable production volume, the automatization of the production with classic solutions is very difficult and could be uneconomical. However, by applying a human-robot collaboration ecosystem, the operations would be more efficient and precise. For instance, in the production of semiconductors such as GaAs the benefits will be very high.  

This use case aims to reduce environmental pollution with waste from production of semiconductors. Thanks to the AI-PRISM ecosystem, they will reduce wasted structures, time of their operators who normally correct alignments manually with the help of a microscope, increasing the precision of assembly as well as the time taken to teaching new workers.  

 

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