SmartClean – Minimise the environmental impact of cleaning in place
Cleaning processes used in dairy production, called CIP (Cleaning in Place) processes have a significant environmental impact in terms of energy consumption, downtime in production, water usage, and use of chemicals. In practice, industrial fouling and cleaning processes are not well-characterized and current cleaning processes are designed using empirical approaches. Monitoring tools and advanced data analytics provide an opportunity that can be augmented by using models that capture the relevant physico-chemical phenomena. The aim of SmartClean is to develop validated models that will use measurements obtained at early stages of CIP processes to predict cleaning times.
By: Grith Mortensen
Despite the introduction of on-line monitoring and data driven approaches, in order to ensure hygienic conditions, the dairy industry is still “over-cleaning”. The project will focus on cleaning of typical dairy streams/processes, e.g. heat exchangers, and membrane filtration. One of the key challenges in minimising environmental impact of CIP without compromising quality and safety is understanding the kinetics of removal of traces of fouling and the resulting effect of any remaining material after repeated CIP cycles. The questions that SmartClean will address are: What is the level of acceptable cleaning, and what are the kinetics behind reaching a clean surface?
SmartClean will provide validated models, by developing:
(1) experimental methods to assess different CIP conditions, including cleaning kinetics of very thin fouling layers and characterization of fouling material remaining on the surface.
(2) validated models by further extending mechanistic models using statistical approaches to predict cleaning rates. Models will be validated against real case scenarios applicable to the wider dairy sector.
Once the models are established, it will be possible to use measurements obtained in early stages of CIP processes to predict cleaning times and better manage and minimize resource consumption.
Project period: September 2022 – September 2025
Budget: 4,995,432 DKK
Financing: Milk Levy Fund, funding from Arla Foods Ingredients, self-funding from University of Copenhagen
Project manager: Serafim Bakalis
Institution: Department of Food Science, University of Copenhagen
Participants: Department of Food Science, University of Copenhagen; Arla Foods Ingredients; School of Chemical Engineering, University of Birmingham
The results originating from the project will be published on this page when they become publicly available.