Q-INSTINCT
Quality Inspection, Traceability and Interaction within Clothing and Textil industry
Scheda del progetto
Novasis s.r.l.
Q-INSTINCT will allow us to optimize the image acquisition processes and will therefore be able to extend the intervention cases in the field of tissue quality control, by typology, by type of defects or characteristics to be detected, and by operating conditions. The improvement of control processes, thanks to the use of AI, will increase the efficiency of detection and limit subsequent correction interventions, leading to a reduction in time and costs. The project will also use Blockchain technology to archive and certify the Quality Control report, which will allow the traceability of processes and goods, and will prepare the supply chain for the upcoming implementations of the Digital Product Passport and digital labeling in the textile sector. With video communication in live mode at high resolution and quality, it will finally be possible to have remote collaborative sessions, capable of providing the detail and colorimetric rendering necessary for quality assessments.
Contacts:
Mattia Platini
Quality Biella's objective is to improve (in terms of efficiency and methods of intervention) its business processes. The use of AI will increase the efficiency of quality control systems: the aim will be to extend the ability to recognize defects and respect distinctive characteristics (color designs, etc.), thanks to the improvement of the acquisition and pre- processing (thanks to Novasis) and the refinement of recognition models and techniques (thanks to Fondazione Links).
The project intends to substantially innovate the current quality control processes of fabrics and the current methods of communicating the results to customers, allowing faster execution times of checks, greater precision in identifying defects, guaranteed and certified traceability of results obtained, more effective communication with the customer.
The adoption of new digital technologies and the implementation of the processes associated with them will be a precious opportunity to relaunch the dynamics of value and to recover adequate levels of productivity, despite the context of employment contraction. The expected impact on the production chain is therefore extremely high in terms of increasing production efficiency and therefore quality offered to end users.