Mechanical and Production Engineering

Mr. Rezaul Karim Nayeem

Research Interests

• Machining Parameter Optimization
• Hybrid Composite
• Machining of MMC & PMC
• Machining of Alloy
• Hard turning

Educational Background

• Master of Science (MSc), (IPE), BUET
• Bachelor of Science (BSc), (IPE), AUST

Honors and Achievements

Publications

1. Study of Surface Roughness and MRR in Turning of SiC Reinforced Al Alloy Composite Using Taguchi Design Method, ANN and PCA Approach under MQL Cutting Condition, Advanced Materials Research, 2020.

1. Mechanical characterization of mulberry silk reinforced hybrid composite for enhanced application, Results in Materials, 2024, Elsevier. URL
2. Exploring lean manufacturing drivers for enhancing circular economy performance in the pharmaceutical industry: a Bayesian best–worst approach, International Journal of Industrial Engineering and Operations Management, 2024, Emerald. URL
3. Machinability investigation of natural fibers reinforced polymer matrix composite under drilling: Leveraging machine learning in bioengineering applications, AIP Advances, 2024, AIP publishing. URL
4. Surface roughness and cutting force in turning of alkaline-treated banana fibre-reinforced polymer composite: Compressed air cutting, Journal of Reinforced Plastics and Composites, 2024, Sage. URL
5. Turning SKD 11 Hardened Steel: An Experimental Study of Surface Roughness and Material Removal Rate Using Taguchi Method, Advances in Materials Science and Engineering, 2023. URL
6. Assessing the barriers to lean manufacturing adoption in the furniture industry of Bangladesh: a fuzzy-DEMATEL study, International Journal of Industrial Engineering and Operations Management, 2023. URL
7. Environmental, Economical and Technological Analysis of MQL-Assisted Machining of Al-Mg-Zr Alloy Using PCD Tool, Sustainability, 2021. URL
8. Experimental Investigation of the effect of Cutting Parameters on Cutting Temperature using RSM and ANN in Turning AISI 1040, Global Scientific Journal, 2018.
9. Optimization of Machining Parameter for Surface Roughness in Turning GFRP Composite Using RSM-GA Approach, American Journal of Materials Science and Engineering, 2018.
10. Predictive Modeling of Surface Roughness in MQL assisted Turning of SiC-Al Alloy Composites using Artificial Neural Network and Adaptive Neuro Fuzzy Inference System, Journal of Advanced Research in Manufacturing, Material Science and Metallurgical Engineering, 2018.

1. Investigation of Surface Roughness in MQL Aided Turning of AlCuZr Alloy using PCD Tool, Intelligent Manufacturing and Energy Sustainability, 2021. URL