Micromachined based Multi-Sensing Solution toward Digitalisation of Foundation Industries

Industry 4.0 and Industrial Internet of Things (IIoT) in the Foundation industries are driven by the expanding development of smart sensors offering new approaches to collect and post-process data to improve many areas of factory operation and lead to the digitalisation of the production process. Substantial technologies investment is
required to realise this digitalisation in the current and coming era, leading to the expansion of the global industrial sensors market, which is expected to reach USD 53.2 Billion by 2030 with a CAGR of 9.06%. The fundamental revolution in the UK’s Foundation industries lies in the broad integration of sensors technology. The above aims mainly to cost-saving through the production process optimisation, reduce equipment downtime through predictive maintenance by enabling machines to be self-monitored, and improve their reliability and maintenance cost. Such aims will likely be achieved by developing multifunctional smart sensors (i.e., sensors performing predefined actions according to collected data) with high precision, reliability, and fast response time. Particularly, it is vital to collect real-time data for workplace monitoring or predictive equipment maintenance, such as motion, temperature, gas concentration and humidity.

The proposed research aims to develop a novel, low-cost, multi-gas miniaturised sensor solution (with TRL~2-3) operating in a relatively harsh environment. The incremental development of the gas sensor would lead to the exaltation of the sensor design to be customised to simultaneously detect motion, temperature and humidity, which is limited at this stage due to the highly challenging environment in Foundation industries. Such a sensing solution will allow system operation in various Foundation industry sectors, mainly metal, cement and glass, to be more efficient, make predictive maintenance feasible, provide better sensitivity and fast time response (~100μs) and decrease the number of integrated sensors.

Dr. Amal Hajjaj

Loughborough University

a.a.hajjaj@lboro.ac.uk