Instrumented PCB for predictive maintenance

Job description: The manufacturing of electronic equipment, and more specifically Printed Circuit Boards (PCBs), represents a significant share of the environmental impact of digital technologies, which must be minimized. Within a circular economy approach, the development of monitoring and diagnostic tools for assessing the health status of these boards could feed into the product’s digital passport and facilitate their reuse in a second life. In a preventive and prescriptive maintenance perspective, such tools could extend their lifespan by avoiding unnecessary periodic replacement in applications where reliability is a priority, as well as adapting their usage to prevent premature deterioration. This PhD proposes to explore innovative instrumentation of PCBs using ‘virtual’ sensors, advanced estimators powered by measurement modalities (such as piezoelectric, ultrasonic, etc.) that could be integrated directly within the PCBs. The objective is to develop methods for monitoring the health status of the boards, both mechanically (fatigue, stresses, deformations) and electronically. A first step will consist of conducting a state-of-the-art review and simulations to select the relevant sensors, define the quantities to be measured, and optimize their placement. Multi-physics modeling and model reduction will then make it possible to link the data to PCB integrity indicators characterizing its health status. The approach will combine numerical modeling, experimental validations, and multiparametric optimization methods.

Your profile: Physique et traitement du signal