Md Sakibul Islam
International University of Business Agriculture and Technology
Papers
1
Total Citations
6
H-Index
1
About
Md Sakibul Islam is a materials and mechanical engineering researcher whose work focuses on enhancing the durability and performance of industrial steels through advanced surface engineering and data-driven analysis. His key research areas include tribology—the study of friction, wear, and lubrication—and the application of machine learning to predict and optimize material behavior. Islam’s most cited paper, “Effects of Self-Lubricant Coating and Motion on Reduction of Friction and Wear of Mild Steel and Data Analysis from Machine Learning Approach” (2021, 6 citations), addresses a critical industrial challenge: the premature failure of mild steel components under relative motion. By investigating self-lubricant coatings and their interaction with motion parameters, he demonstrates how these coatings can significantly reduce friction and wear, thereby extending the service life of steel parts. His innovative integration of machine learning for data analysis marks a notable achievement, offering a predictive framework that can guide coating selection and operational conditions. This work bridges traditional materials science with modern computational techniques, providing practical solutions for industries reliant on durable, low-friction steel components. Islam’s contributions are particularly valuable for students and researchers interested in sustainable manufacturing, surface engineering, and the growing role of AI in materials research.
Research Focus
Key Achievements
Top Papers
- 1