ANR-DFG - Appel à projets générique 2022 - DFG

Explainable Quality Assurance and Diagnosis in Manufacturing Processes – XQuality

Submission summary

French and German manufacturing companies are known for their high-quality production and their orientation towards smart factories. Quality assurance and control of complex production systems is a major challenge and is further exacerbated by the shortage of skilled labour in this domain. Quality problems must be detected and eliminated quickly. When a quality problem is detected, it is necessary to quickly understand the multiple possible causes for it (which can sometimes be contradictory to each other) in order to propose the most appropriate corrective actions to return the manufacturing process to its normal operating mode.

The XQuality project is researching hybrid and explainable AI approaches to help manufacturing companies implement intelligent and automated quality assurance. The project combines data-based machine learning, semantic technologies and expert knowledge to monitor and explain product and process quality targets in a company. The goal is to develop an AI-based system that will assist the staff in identifying the main and earliest causes of quality issues, thanks to new models to be proposed to the reliability engineering domain.

Project coordination

Habib ABDULRAB (LABORATOIRE D'INFORMATIQUE, DE TRAITEMENT DE L'INFORMATION ET DES SYSTÈMES - EA 4108)

The author of this summary is the project coordinator, who is responsible for the content of this summary. The ANR declines any responsibility as for its contents.

Partner

ICube Laboratoire des sciences de l'Ingénieur, de l'Informatique et de l'Imagerie (UMR 7357)
HS Furtwangen HS Furtwangen
CETIM CETIM
LITIS LABORATOIRE D'INFORMATIQUE, DE TRAITEMENT DE L'INFORMATION ET DES SYSTÈMES - EA 4108

Help of the ANR 855,598 euros
Beginning and duration of the scientific project: February 2023 - 36 Months

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