Editor Profile
Dr. Sherwan Mohammed Najm, Ph.D.
Lecturer
Present
Northern Technical University
Mosul
Iraq
Dr. Sherwan Mohammed Najm is Head of the Mechanical Power Techniques Engineering Department at the Kirkuk Technical Engineering College, Northern Technical University, Iraq. He holds a PhD in Mechanical Engineering from the Budapest University of Technology and Economics.
His academic work covers several engineering fields, including:
- Incremental sheet forming
- Artificial intelligence and neural networks
- Numerical simulation and finite element analysis
- Material formability and metal forming technologies
Dr. Sherwan’s research focuses on unconventional sheet metal forming processes and the integration of artificial neural networks in intelligent manufacturing systems. He has participated in national and international research initiatives in these areas.
- Metal Forming
- Sheet Metal Forming
- Incremental Sheet Forming
- Mechanical Simulation
- Numerical Simulation
- Mechanical Properties
- Experimental and Numerical Investigations of the Fatigue Life of AA2024 Aluminum Alloy-Based Nanocomposite Reinforced by TiO2 Nanoparticles Under the Effect of Heat Treatment. 2024.
- Application of the Gradient-Boosting with Regression Trees to Predict the Coefficient of Friction on Drawbead in Sheet Metal Forming. 2024.
- Analysis of the friction performance of deep-drawing steel sheets using network models. 2024.
- Current Trends in Metallic Materials for Body Panels and Structural Members Used in the Automotive Industry. 2024.
- Applications of Incremental Sheet Forming. 2024.
- Minimizing the Main Strains and Thickness Reduction in the Single Point Incremental Forming Process of Polyamide and High-Density Polyethylene Sheets. 2023.
- Analysis of the Frictional Performance of AW-5251 Aluminum Alloy Sheets Using the Random Forest Machine Learning Algorithm and Multilayer Perceptron. 2023.
- Investigation and machine learning-based prediction of parametric effects of single point incremental forming on pillow effect and wall profile of AlMn1Mg1 aluminum alloy sheets. 2023.
- Modeling and parameter identification of coefficient of friction for deep-drawing quality steel sheets using the CatBoost machine learning algorithm and neural networks. 2023.
- Recent Developments and Future Challenges in Incremental Sheet Forming of Aluminum and Aluminum Alloy Sheets. 2022.
- Application of Artificial Neural Networks to the Analysis of Friction Behavior in a Drawbead Profile in Sheet Metal Forming. 2022.
- Current Concepts for Cutting Metal-Based and Polymer-Based Composite Materials. 2022.
- Incremental Sheet Forming of Metal-Based Composites Used in Aviation and Automotive Applications. 2022.
- Parametric effects of single point incremental forming on hardness of AA1100 aluminum alloy sheets. 2021.
- New advances and future possibilities in forming technology of hybrid metal–polymer composites used in aerospace applications. 2021.
- Emerging trends in single point incremental sheet forming of lightweight metals. 2021.
- Predict the Effects of Forming Tool Characteristics on Surface Roughness of Aluminum Foil Components Formed by SPIF Using ANN and SVR. 2021.
- Artificial neural network for modeling and investigating the effects of forming tool characteristics on the accuracy and formability of thin aluminum alloy blanks when using SPIF. 2021.
- Experimental and numerical investigation of the single-point incremental forming of aluminum alloy foils. 2020.
- Lubricants and parameters affecting hardness in SPIF of AA1100 aluminium. 2020.
- Study on influencing parameters of flat and hemispherical end tools in spif of aluminum foils. 2020.
- Heat transfer and fluid flow over a bank of circular tubes heat exchanger using nanofluids: CFD simulation. 2020.
- Experimental Investigation on the Single Point Incremental Forming of AlMn1Mg1 Foils using Flat End Tools. 2018.
