School of Mechanical, Electrical and Manufacturing Engineering

Research

Self-Optimising Cleaning-in-Place

Self-Optimising Cleaning-in-Place

The application of ultraviolet fluorescence imaging to reduce the water, energy and chemical demands of industrial process cleaning, whilst improving productivity and quality assurance.

Our Aim

The demand for industrial resource efficiency has never been so stark and this research supports the need for the manufacturing industry to reduce its environmental impacts through better monitoring of cleaning processes.

Food and drink production is the largest manufacturing sector in the UK and the highest industrial user of water at approximately 430 million litres a day. Much of this water is used in a process called clean-in-place, an automated cleaning cycle for process equipment. These cycles are designed to clean for the worst-case scenarios and so routinely over-clean production equipment. The result is that manufactures routinely waste water, energy and cleaning chemicals and also suffer from a loss of production time.

There are a range of sensors that are currently used to monitor cleaning processes, but they look at the end-of-pipe effluent and do not monitor directly the fouling that remains within the process vessels.

If more accurate sensors could be developed for clean-in-place systems, it is estimated that there could be savings of £100 million per year in the UK food industry alone.

Our Research

We are utilising ultraviolet fluorescence spectroscopy to directly image fouling remaining in process vessels in real-time and comparing these readings with other sensors (including ultrasonic) from around the process equipment.

The new application of technology allows accurate tracking of cleaning cycles, giving a better insight to the selection of cleaning variables and also allows better production scheduling as time-to-clean can be predicted. The system also facilitates more rigorous cleaning assurance of production equipment.

A range of artificial intelligence driven techniques supports the processing and eco-intelligent decision making within a facility.

Our Outcomes

If implemented on a wide scale, the technology is likely to lead to better protection against unintended allergens, a lower environmental impact from manufacturing processes and cheaper food process. The technology is also applicable to pharmaceuticals, the chemical industry and FMCG.

Dr Elliot Woolley - Senior Lecturer in Sustainable Manufacturing

"If fluorescence imaging for clean-in-place was used routinely in the food production industry, we would all benefit from safer, cheaper food that had a lower environmental impact."

Dr Elliot Woolley - Senior Lecturer in Sustainable Manufacturing

Athena Swan Bronze award

Contact us

The Wolfson School of Mechanical, Electrical and Manufacturing Engineering
Loughborough University
Loughborough
Leicestershire
LE11 3TU