Scientific direction Development of key enabling technologies
Transfer of knowledge to industry

PhD : selection by topics

Additive manufacturing of a high temperature strain jauge







The Internet of Things brings intelligence and connectivity within industrial tools. It gathers a real-time knowledge of the equipment parameters, which allows optimizing the processes by a better control and monitoring of the manufacturing conditions. The accumulation of data allows statistical processing by machine learning to improve the process and control in real time thanks to more connectivity and embedded intelligence. At the heart of data collection in the tools, many sensors are designed based on a common sensing element: the strain gauge. However, the operating conditions in the industrial environment are extremely severe; the major degradation stimulus is temperature, with values commonly exceeding 400 ° C, eliminating the use of gauges that are performed exclusively on plastic substrates. The aim of this thesis is to develop high temperature gauge sensors, leveraging additive techniques for both the fabrication and integration of gauges on topologically optimized test bodies.

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