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Details of Grant 

EPSRC Reference: EP/V004654/1
Title: Programmable Sensing Composites
Principal Investigator: Stanley-Marbell, Dr P
Other Investigators:
Barbalace, Dr A Pattinson, Dr SWS
Researcher Co-Investigators:
Project Partners:
Max Planck Institutes (Grouped)
Department: Engineering
Organisation: University of Cambridge
Scheme: Standard Research - NR1
Starts: 01 June 2020 Ends: 31 May 2022 Value (£): 506,089
EPSRC Research Topic Classifications:
Manufacturing Machine & Plant
EPSRC Industrial Sector Classifications:
Manufacturing
Related Grants:
Panel History:  
Summary on Grant Application Form
Most man-made objects are still in the analog era: Few man-made physical objects contain sensors and fewer still have any embedded computation alongside sensors. This situation is much like analog cameras at the turn of the century. Embedding digital computation alongside sensing in object fabrication processes and in fabricated structures could enable in situ metrology, in situ analysis during real-world use, and valuable statistics from every individual physical object. Such in-situ-processed digital summaries of the physical histories of internals and usage of objects could enable a fundamental shift in how we design, fabricate, and use physical objects.

Synthesized digital summaries of the internal conditions within physical objects could enable a revolution at the same scale or greater than the revolution in data-driven methods for computer vision enabled by ubiquitous digital cameras. Because they will enable embedding sensing combined with local in situ signal processing, sensor-augmented fabrication processes and sensor-augmented fabricated objects could enable a revolution with potential far-reaching benefits to society (better products that are more fit for purpose) and the environment (products manufactured with less waste).

Embedded sensing and computation could also enable a future where materials properties adapt, under control of computation, to the modes of usage of objects. Embeddable sense-and-compute devices and the associated research results and methods from this project could allow us, for the first time, to monitor those phenomena autonomously over a physical object's lifetime, to perform fundamentally new forms of structural integrity analysis based on real-time data monitored throughout the volume of products, and to enable new structural capabilities and commercial product capabilities, such as sensed-stress-driven adaptive recalls and data-driven product customization.

Our goal in this project is to investigate new fundamental methods for embedding computation and sensing into additively-manufactured objects and to use sensor data, analyzed in situ, to improve their materials formulation, design, and manufacturing. Data from continuous in-object metrology during real-world use could enable fundamentally-new and potentially-disruptive methods for manufacturing high-value items. Today, unlike in other areas of engineering, where large amounts of data from real-world use are revolutionizing tasks such as computer vision and speech recognition, manufactured objects are still largely un-instrumented, data-poor, and missing out on opportunities for data-driven usage-informed design, materials formulation, and manufacturing.

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Organisation Website: http://www.cam.ac.uk