Nanophotonic Sensors Correct Errors in Automated Production Lines

Grants worth millions of pounds have been awarded to researchers from the University of Huddersfield for a five-year research project that will expedite a new industrial revolution by creating novel methods for ultra-precise measurement on the nanoscale.

Project leader Professor Dame Xiangqian (Jane) Jiang. Image Credit: University of Huddersfield.

A series of miniaturized sensors will allow automated production lines to detect and rectify errors in situ, without the need to remove parts for individual measurement. This sensor will offer much higher cost savings and efficiency as well as the potential to produce short runs of custom-made items on request, with unparalleled precision.

The so-called Industry 4.0 is the term employed to denote this subsequent phase of industrial advancement, which relies on automation powered by smart technology. The University of Huddersfield’s Centre for Precision Technology (CPT)—pioneers in metrology, or the science of measurement—is helping to realize this goal.

For this purpose, the CPT has collaborated with Professor Nikolay Zheludev FRS’s Nanophotonics and Metamaterials Group at the Zepler Institute for Photonics and Nanoelectronics in the University of Southampton.

Both the research teams will share funding of over £5million for a new program, called Next-Generation Metrology Driven by Nanophotonics, which will be performed under the guidance of CPT member Professor Dame Xiangqian (Jane) Jiang.

The project is financially supported by a Program Grant from the Engineering and Physical Sciences Research Council (EPSRC). Such highly esteemed awards are “intended to support world-leading researchers, bringing together ‘best with best’ teams to undertake a variety of activities focusing on one strategic research theme.” The University of Huddersfield has been awarded a program grant for the first time.

At Huddersfield, one of the CPT teams engaged in the new project is headed by Dr Haydn Martin. According to Martin, the extent to which traditional optics, like glass lenses, can be miniaturized and fitted in the sensors essential for Industry 4.0 to realize its potential is restricted.

However, by using nanophotonics, which is the study of light at the nanoscale, small, flat lenses can be developed from innovative meta-materials. Such lenses perhaps have a thickness of just tens of microns.

Traditional factories are very good at making lots of similar things, but the Industry 4.0 concept is all about automation and autonomous manufacturing, so that it is possible to send in a design and the manufacturing platform can then configure itself, with Artificial Intelligence supporting all the activity in the background.

Haydn Martin, Senior Lecturer, Department of Engineering and Technology, School of Computing and Engineering, University of Huddersfield

Dr Martin added, “In order to do this, you need a much greater incorporation of metrology, because you are asking the tooling to do many different things rather than the same thing over and over again.”

A long process of submission and appraisal was involved in achieving the EPSRC grant shared by the CPT at Huddersfield and the Zepler Institute at Southampton.

At the end of 2017, CPT’s Professor Jiang, along with Dr Martin and Dr Andrew Henning, started to consider the solutions to the sensor miniaturization challenge. Their focus was on the abundant latest advances in optical metamaterials, plasmonics, and nanophotonics, with the potential for a revolution in the development of sensors for optical metrology.

Professor Paul Scott who also joined the project will be designing new mathematics and machine-learning methods needed for the project.

According to Dr Martin, at present, the EPSRC grant will pave the way for a new field in nanophotonics for metrology.

We aim to transition nanophotonic devices from where they are now in the physics labs at Southampton all the way through to demonstrations of new ultra-miniaturized, ultra-compact sensors in real-world situations.

Haydn Martin, Senior Lecturer, Department of Engineering and Technology, School of Computing and Engineering, University of Huddersfield

Source: https://www.hud.ac.uk/

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