A Study on Image-Based Validation Methods for Robotic Cleaning Path Optimization

Automation pulls us through the global labour shortage, and equipment suppliers develop CIP system and other robotic cleaning for food machinery.For open equipment cleaning, the soil removal mechanism relies on the mechanical force, chemical reactions and soil types associated with precise cleaning path which serves as a direct influencing factor on cleanliness of non-flat surface.This study aims to develop a method that integrates chemical validation and image analysis techniques to evaluate the cleaning performance of different path plans.First, a standard soiling simulant was selected out of different recipes, and image analysis techniques are used to quantify residual soiling.Subsequently, various cleaning paths are programmed via computer software, followed by cleaning tests and image analysis.Result showed that unoptimized cleaning path has area of more than 40% soil residue compared to optimized one.By integrating data analysis, effective cleaning paths and removal rates are identified, enabling robotic arms to adaptively adjust their motion trajectories.This method can be applied to the optimization of robotic cleaning procedures in pharmaceutical and food processing equipment.