Description

Established in 1968 in Zaragoza (Spain), Fersa Bearings S.A is a company specialized in the design, manufacturing and commercialization of bearings. More than 96% of sales are devoted to exports worldwide: 35% Europe, 10% Africa, 27% Asia and 28% America. Fersa currently employs 160 people. Since its setup, Fersa has shown a huge interest in Innovation and has collaborated in several R&D projects. Furthermore, Fersa has obtained several regional prizes for business excellence and logistics management. Its product portfolio is composed by tapered roller bearings, ball bearings and cylindrical bearings. It is mainly oriented to the automotive market (car, light duty, heavy duty and off-highway) with a minor percentage dedicated to the industrial market.

Website: https://www.fersa.com/en

Main Tasks in MAS4AI

Main tasks/activities to in the project:
Definition of industrial requirement and specifications for the implementation of new AI tools on the production line to improve current equipment performance, developing quality measuring stations and collecting data to perform predictions of quality problems based on metamodels or subrogated models. Definition of influence in bearing quality of factors such as temperature and variation of raw material, to predict product dimensions and design adjustment rules to improve quality. Definition of optimal production routes for that conditions, grinding wheels, tooling and parameters in those machines to be monitored and collected in AI
tools to improve process with best output. Connection of AI with ERP to adapt routes, send information to warehouse to coordinate materials to be used in time, ensure tooling and grinding wheels by automatic systems, as well as support to implement tools to adapt machines to optimal parameters. Evaluation of model-based control solutions in a production line for bearings.

Competences/skills for accomplishing work:
World leader in manufacturing of tapered roller bearings and other types of bearings for more than 50 years, T1 supplier of OEMs manufacturer leaders. Experience in process research projects, including H2020, and Spanish funding programs. Knowledge of real-time process adjustments with quality measurements, high-technology quality stations developing, machine communication to collect parameters. IT experience in process data storage, own software development to connect ERP to shopfloor tools, as well as BI development.