Novel technologies or approaches necessary to create the next generation of sensors/systems

SECTION 3 Key Themes

Novel technologies or approaches necessary to create the next generation of sensors/systems

Trends & Drivers TD5 TD6 TD15 Research Themes RT1 RT2 RT3 RT4 RT7 Capabilities & Enablers CE1 CE3 CE4 CE5

Factors such as accuracy and precisions are of course still of primary importance to industrial metrology. However, as industry moves more towards fully autonomous manufacture and servitisation as a business model, integrated metrology solutions are increasingly in demand to meet these new challenges.

In order to adapt existing technologies to be suitable for in-process measurement, it is necessary to both miniaturise and enhance the ruggedness of sensors to be capable of operating within the manufacturing environment while minimising the impact on production capability. Optical measurement techniques are well suited to a wide variety of operating environments and are capable of achieving the speed and precision of measurement necessary. Ideally, to avoid disruption to the manufacturing process, methods for in-situ traceable self-calibration must be developed which require minimal user input or be capable of being completed automatically. There are limits to what can be achieved through the use of conventional sensors or measurement devices and new approaches which make use of novel technologies will be necessary to overcome fundamental physical barriers. These novel approaches may draw on technologies in other fields, such as semi-conductor manufacturing techniques to develop “on-a-chip” optical systems or making use of the unique optical properties of metamaterials to enable photonic integration.

In addition to the physical challenges of developing sensors which can be incorporated into manufacturing processes, the trend towards continuous monitoring generates substantially greater quantities of data. New approaches to how this data is handled, curated and processed will need to be developed to create software capable of dealing with vast quantities of synchronous data autonomously to produce an accessible and useable output. Achieving this will require expertise from a variety of disciplines such as mathematics, data science and cyber security.

Ultimately, the aim is to use metrology driven data to autonomously monitor and control manufacturing processes in real time. Even with advanced software, the challenge of monitoring all but the most basic manufacturing environment is beyond even highly skilled operatives. Artificial Intelligence (AI) and machine learning show the greatest potential to maximise the value of this data however there are significant challenges which must be overcome before AI can be a viable, widespread solution. Autonomous systems must be capable of dealing with uncertainty in the measured data and using it to make robust, traceable, informed decisions.

Key message

Industry can often be reluctant to move away from established technology and tends to “stick with what they know”. Meanwhile, translating novel approaches to metrology from lab based experiments into industry ready solutions is often as challenging as the fundamental science. Building strong links with academia should enable much more rapid access to cutting edge technology and yield a competitive advantage.

Key message

The field of metrology offers a wealth of opportunities to deploy novel science or technology into real world applications. Researchers in metrology should stay abreast of developments in scientific fields and actively recruit researchers from a diverse range of subjects by maintaining a broad network of connections.