Intelligent Sensor Fusion for Sustainable Cleaning in the Food Industry

We are seeking a motivated and capable PhD researcher to undertake an exciting research project that promises to improve the sustainability of the food industry. 

The food and drink production sector is the largest manufacturing industry in the UK, consuming approximately 430 million litres of water per day – accounting for 10% of the country's total industrial water usage. This sector also ranks as the fourth largest industrial energy consumer in the UK, and on a global scale, the food industry is responsible for over a quarter of all carbon emissions, second only to the energy sector itself. 

One of the most resource-intensive processes within the sector is the cleaning of processing equipment. This operation is critical in industries such as food and drink, pharmaceuticals, and fast-moving consumer goods (FMCG), but it requires substantial amounts of water, energy, and chemicals. In food processing plants, it is estimated that cleaning typically represents 30% of a site's total water consumption and a similar proportion of energy consumption. These figures highlight the significant environmental costs of current cleaning practices, underscoring the need for more efficient, sustainable cleaning technologies within the sector.

Cleaning is generally performed using autonomous Clean-in-Place (CIP) processes, which often over-clean as suitable technologies do not exist to determine when fouling has been removed from the internal surfaces of processing equipment. To optimize the cleaning of food production equipment, there is the need for innovative technologies to monitor the removal of fouling from equipment surfaces. Similarly, post-process water streams are frequently reusable, but are discharged due to lack of intelligent monitoring and management capability.

This project will investigate the opportunity to use ultraviolet (UV) fluorescence imaging to monitor the removal rate of food fouling from the internal surfaces of tanks during CIP processes combined with in-line sensors to assess cleaning water quality for reuse or recycling. Most foods contain fluorophores and will fluoresce under suitable UV excitation. Detecting this fluorescence would allow in-process monitoring of fouling removal and hence support the control of cleaning processes. The application of water stream monitoring sensors (currently used for process control) for post-process water stream management will also be investigated.

The approach to combine optical monitoring of cleaning with intelligent process water management is novel and provides opportunities for reducing cleaning times, saving energy and maximising the use of process water to reduce demand.

Briefly this project presents a number of technological objectives: 

1. Develop high quality optical detection of fouling
2. Decipher water soil levels using existing process monitoring sensors by correlation with conventional water quality parameters
3. Develop decision support for cleaning and water management

The doctoral researcher will have access to existing state-of-the-art processing facilities and appropriate monitoring and analysis equipment. The project presents the opportunity to publish in top-tier journals and present at international conferences and the PhD student will receive comprehensive training in research practices, technical writing and many other relevant skills. 

The output of the project will be industrially relevant, and it is intended that collaboration with industry will be established during the project, with the opportunity for access to trials.

Candidates should have a strong background in engineering, applied physics, or related fields; knowledge or interest in sensor technologies, water chemistry, or data analytics; and excellent problem-solving skills with a passion for research innovation.