Machine Learning Techniques in Scrap Management System
Year: 2025
Type: article
Abstract: The application of machine learning methods on scrap management systems is discussed in this literature review. ML methods have been used in recycling process optimisation, predictive maintenance, and sorting scrap. This research looks at several machines learning methodologies, including computer vision, clustering, and classification. It also discusses practical applications and challenges in implementing machine learning in this domain. The results prove that machine learning is able to enhance sorting accuracy, reduce operational costs, and enable more eco-friendly recycling practices. Waste materials have dramatically risen due to the rapid growth of urbanization and industrial processes, making it harder to control, dispose of, and recycle them efficiently. Traditional scrap management methods often lack user convenience, effectiveness, and transparency. In scrap management, this literature review discusses several existing systems and technology advancements.
Author: Prof. S. P. Veer, Harshal Linge, Aditya Zade, Parikshit Urkande, Mrunali Nimbulkar, Nutan Sayankar, Payal Khedekar
Institution: Bapurao Deshmukh College of Engineering, Sevagram
Language: English
Subfield: Waste Management and Disposal
Field: Environmental Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W6893288268
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