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Smart PCBs - Initial Tests with Piezo Sensors in Printed Circuit Boards

Reference number
Coordinator Swerea IVF AB - Avdelningen Material
Funding from Vinnova SEK 145 780
Project duration November 2017 - January 2018
Status Completed
Venture The strategic innovation programme Electronic Components and Systems:

Important results from the project

The increasing complexity of electronics in systems used in safety critical applications requires new methods to assure the hardware reliability of the electronic assemblies. Prognostics and Health Management (PHM) that uses a combination of data-driven and Physics-of-Failure models is a promising approach to avoid unexpected failures in the field. PHM benefits from sensor data that measures the relevant environment loads. In this work, the feasibility to manufacture integrated vibration sensors in a printed circuit board (PCB) has been investigated.

Expected long term effects

Results showed a yield of approximately 30 % of the sensors after the reflow soldering process. The yield was also dependent on sensor shape and placement. Correct sensor design and placement would bring the yield to 50 % or better. The results show that embedded vibration sensors in electronic assemblies are possible to manufacture. In the future it may be possible to order PCBs with embedded sensors for continous measurements of environment loads. Such information could then be used in combination with other data to prognosticate the remaining useful life of the product.

Approach and implementation

A multilayered test board was designed in which piezoelectric sensors was included in one of the layers. Mounting of BGA676 full array packages and four 72 lead QFN packages were done in an industrial reflow soldering process. Polarization of the piezoelectric sensors was carried out before and after the high temperature steps in the manufacturing process to verify the functionality of the sensor material. Finally, analysis of the manufactured sensors inside the PCBs were made using scanning accoustic microscopy and microsectioning to investigate the sensor cross-sections.

The project description has been provided by the project members themselves and the text has not been looked at by our editors.

Last updated 25 November 2019

Reference number 2017-03552

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