The University of Nottingham is currently developing an artificially-intelligent sensor system to clean food manufacturing equipment more precisely.
It has been estimated that the AI-driven monitoring system could save £100 million (AUD $177 million) a year for the UK industry and lead to greater production capacity, therefore cheapening consumer food prices.
‘As current technologies cannot accurately determine exactly how dirty food and drink processing equipment is inside, cleaning can last up to five hours a day to minimise food safety risks’.
‘Cleaning in the UK currently accounts for 30 per cent of energy and water use and leads to excessive productivity down time and over-use of chemicals, which is a huge cost to manufacturers and the environment’.
“To prevent product contamination, many food and drink manufacturers use a non-invasive, Clean-in-Place (CIP) system to wash inside food processing equipment without disassembling it,” explained assistant professor and chemical engineer Dr Nik Watson, who is leading the University of Nottingham team.
“As CIP has to operate ‘blind’, it is designed for the worst case scenario. In daily use this often results in the over-cleaning of production lines.”
‘The University of Nottingham research team will design and build a lab-scale experimental rig that will reproduce common industrial cleaning problems in a typical food-processing plant’.
They will then ‘assess the potential for an artificial intelligence inspection system to measure precisely how much food residue and microbial debris is left inside the rig’.
The year-long study will involve developing software that can process the sensor data results and generate algorithms for an AI-based monitoring system. ‘This use of AI cognitive decision-making for a novel Self-Optimising-Clean-In-Place (SOCIP) system will be world-first’.
“Due to the technical complexity of sensor integration such a solution does not yet exist,” said Dr Watson. “The aim of the SOCIP project is to overcome these technical barriers and reduce cleaning time and resource use by approximately 20 to 40 per cent.”