Postdoc in Mechanical Engineering - Pr. Franck Andrés GIROT MATA - LTC AENIGME (# of pos: 1)

A postdoctoral position in Towards data driven models for advanced machining processes is available in the research group of Advanced Manufacturing at the Laboratories for Trans-border Cooperation - LTC AENIGME. This is an initiative between the Department of Mechanical Engineering of the Faculty of Engineering of Bilbao and the Institute of Mechanics and Engineering of Bordeaux. It brings together researchers from UPV / EHU, UBx, ENSAM and INP Bordeaux.

Digital Twins are currently being stablished for integration of physical and data-driven models. The relation between process features and the machining status can be effectively accomplished by using this strategy. This approach enables predictive modelling of process stages to have a sound prediction of the quality of final products. Within this context, the development of accurate and feasible numerical models of the most important removal processes becomes a critical step towards practical Digital Twins. Advanced simulation tools such as Discrete Element Modelling provide an effective solution for modelling material removal processes. Key processes, but not limited to, will be considered, namely grinding, milling, turning, drilling, etc.

For example, within the advanced machine tool sector, grinding is one of the operations with the highest added value in the manufacture of mechanical components and has a very important presence in high-tech companies in the Basque Country and Nouvelle Aquitaine. It is a finishing operation in which dimensional and surface tolerances cannot be achieved by other manufacturing processes. The tool, the abrasive wheel, is a very complex composite that undergoes wear and very high temperatures at the interface when interacting with the very hard workpiece. The wear leads to loss of tolerances and finishes on critical parts in industries such as aerospace, wind power, etc. In addition, this process, often used in the finishing step of the process, leaves residual stresses in the part. The study and prediction of wear and stresses left in the material require, in the current state of knowledge, strategies of experimentation and trial and error, which limits the competitiveness of our companies. The proposed work should lead to the development of a digital twin of the grinding wheel behavior, optimized by means of a new generation of mechanical tests for quasi-brittle composites. The work should build on the previous knowledge of the groups involved in the process, such as machining. Thus, the basis for the work combines the know-how of the UPV / EHU and I2M groups in Machine Tools, in Discrete Element models (DEM) and advanced mechanical tests.

Hybrid approaches will also be taken into account, which will be especially useful for the machining of advanced materials, amongst which next generation composites are included. The final objective is to implement the knowledge into zero-defect production chains.

The aim of the research line where the postdoctoral researcher is hiring is to