Fouling modelling in a UHT unit based on plant data.

Abstract

Heat treatment of dairy products is essential for food safety, one way to perform this is ultra-high temperature (UHT) processing. During the process, macronutrients and minerals form fouling deposits which impairs heat transfer. Eventually the fouling needs to be removed chemically by alkaline and acidic detergents. Fouling buildup and removal are dependent on both internal parameters such as the physical properties of the product and external parameters such as time, flow rate, temperature, and concentration. Modelling fouling development and removal on an industrial scale is valuable from an economical and environmental perspective. By optimizing how long production and cleaning cycles should be the productivity can be increased and the chemical waste as well as the energy consumption can be decreased. Although many models for fouling have been developed, each model is highly dependent on the type of heat exchanger, the product, and the operational parameters. Furthermore, they do not account for upstream and downstream processes which can affect the operator’s decision. This thesis takes a data-driven approach to construct fouling development and removal models from 27 months’ worth of data that was retrieved from a specific heat exchanger. The raw dataset was divided into production and cleaning in place (CIP) cycles. Each cycle had specific requirements that had to be fulfilled e.g., for production they should be longer than 5 hours. CIP cycles were further divided into caustic and acidic cycles. However, due to deviations from standard operating procedures (SOP) and unreliable conductivity meters, caustic and acidic cycles could not be reliably differentiated, therefore 10 reliable CIP cycles were used instead. Regression models were developed for the production and cleaning cycles, where the fouling during production increased linearly with time while cleaning cycles had a more complicated relationship with fouling.

Popular Abstract

Dairy products need to be heat-treated to be safe for consumption, one way to do so is by using ultra high temperature (UHT) treatment, which involves heating products to temperatures of 135°C. This ensures that harmful bacteria are eliminated and allows for storage at room temperature, in contrast to pasteurization. However, at this temperature large deposits of minerals, fats, carbohydrates, and proteins form which is known as fouling. As a fouling layer is created between the hot and cold fluid, the pressure drop increases which leads to a deteriorated performance. To compensate for the increased pressure drop, the flow rate of the heating medium can be increased but after a certain point the fouling layer becomes too thick and chemical cleaning is required. Chemical cleaning is performed using alkaline and acidic solutions to dissolve the proteins and minerals respectively.
In a UHT plant there are many heat exchangers and other units, each with their own sensors. Each sensor takes a measurement every minute which results in a very large dataset. Based on Tetra Pak know how, one specific heat exchanger which had the highest amount of fouling was chosen. The sensors selected was the temperature of the product and heating medium, the flow rates, and the conductivity. In general, higher temperatures lead to more fouling because more reactions can occur between carbohydrates, protein, minerals, and fat, while higher flow rates lead to less fouling due to the forces exerted on the fouling layer by the liquid. Other factors that affect fouling is time and concentration of the detergents. The conductivity was selected to monitor which detergent is used: acid or base.
There are different approaches to modelling fouling: data driven models or physical models. Data-driven models is a pure statistical approach while physical models use mass and energy balances. It is often difficult to find a physical model that is appropriate for industrial applications due to variations in equipment, cleaning solution, product, and operational parameters. A data driven approach has been taken here but this approach also has difficulties such as customers not adhering to the recommended standard operating procedure (SOP) given by Tetra Pak. Another issue is that operator errors might occur. Hence, the data must be cleaned and filtered.
The primary goal of this thesis was to model fouling development during milk production and the secondary goal was to model fouling removal. Fouling development increased linearly over time while fouling removal was close to linear during alkaline treatment and exponential during acidic treatment. Understanding how quickly fouling builds up and how readily it can be removed, can decrease the chemicals used during cleaning and the energy consumption which would improve the sustainability of the process.

• author: Lam, Thai
• supervisor: Andreas Håkansson; Hamid Ghanbari
• organization: Food Technology and Nutrition (M.Sc.)
• course: KLTM05 20231
• year: 2023
• type: H2 - Master's Degree (Two Years)
• subject: Technology and Engineering; Agriculture and Food Sciences
• keywords: UHT, dairy, tubular heat exchanger, fouling development, fouling removal, food engineering
• language: English
• id: 9138860
• date added to LUP: 2023-09-26 10:00:38
• date last changed: 2023-09-26 10:00:38