Improvement Of Quality and Wastes Control Of Soap Manufacturing Using AI

Abstract

This research examines the use of artificial intelligence (AI) to enhance quality standards and eliminate wastage in soap products. Conventional manufacturing practices are known to incur challenges like variation in the quality of the product, considerable loss in the rejection of the products, and abundant wastage of the materials. In order to develop or manufacture their soap with the absence of these issues, AI systems were embedded in the soap manufacturing system processes for controlling variables such as the saponification temperature, mixing speed, and time for curing in real time. Other machine learning techniques such as random forests and neural networks were utilized for defect prediction, prevention, and optimization of resource usage and waste reduction. The factors affecting energy consumption trends were also investigated and it was established that the processes reduced energy since there was high product quality. Evaluation of the 20 production batches produced comparable results through the enhancement of the existing manufacturing with the use of AI technologies which reduced the defects and waste production during the operations while improving the efficiency of operations. This study adds to the literature as well as the practice of AI in manufacturing by providing insights into the use of the innovative technology in the soap making industry and thus sets the stage for process improvement of other industries that is driven by artificial intelligence. The implications of production through AI in the manufacture of soap rest on efficiency, waste reduction, and environmentally friendly production processes.

Keywords: Artificial Intelligence (AI), Soap Manufacturing, Quality Control and Waste Management