Using Artificial intelligence for Recycling- A Case Study in Taiwan's Resource Recycling Industry

Abstract

Resource recycling industries are restricted by the mixed composition of waste, the ratio of recycled material dependent on experience, and the quality inspection relies on physical assessment, resulting in problems such as the inability to optimize manufacturing process parameters and unstable product quality. Artificial Intelligence (AI) has developed rapidly in recent years and adopted in various industries. From literature review, AI is being increasingly used in the resource recycling industry to optimize processes, improve efficiency, and enhance sustainability. This study used machine learning, an AI technology, to conduct model training and identify optimal model validation in Taiwan's resource recycling industry. A case example was implemented to reduce the cost by AI's recommendation of more accurate borax blending ratios. By accepting AI's recommendation of accurate borax blending ratios, it can reduce the non-compliance rate by 45% and at the same time reduce the raw material usage by approximately 2∼3%, saving approximately N.T.D. 1-2 million per year. This study pioneered artificial intelligence technology to improve manufacturing process efficiency and optimization of product quality in the resource recycling industry. The empirical results demonstrate that the application of AI technology contributes to the improvement of traditional manufacturing process problems and enhances the industry's overall production efficiency and quality.