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CIP systems are critical for ensuring hygienic integrity in ultra-high temperature (UHT) food processing. However, conventional cleaning cycles are often rigidly timed and overdesigned, leading to unnecessary water, energy, and chemical use. This thesis presents a data-driven framework to evaluate and optimize the prerinse phase of UHT CIP cycles using pressure drop behavior as an alternative for
