Tesfa Guadie Ayaliew
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Subjects
Tesfa Guadie Ayaliew has a total of 12 co-authors. Here are the top co-authors by number of shared publications:
- Melese Shiferaw Kebede
Department of Mechanical Engineering, Institute of Technology, University of Gondar, Gondar, Ethiopia
2 shared publications Robinson Gnanadurai Rengiah
Department of Mechanical Engineering, Sree Sakthi Engineering College, Coimbatore, Tamil, Nadu, India
2 shared publicationsSamuel Tesfaye Mekonone
Department of Mechanical Engineering, Institute of Technology, University of Gondar, Gondar, Ethiopia
2 shared publicationsBelete Ambachew Mekonen
Department of Mechanical Engineering, Institute of Technology, University of Gondar, Ethiopia
1 shared publicationFikadu Mequant Kidie
Department of Industrial Engineering, Institute of Technology, University of Gondar, Gondar, Ethiopia
1 shared publicationKassahun Abebe Workneh
Department of Mechanical Engineering, Institute of Technology, University of Gondar, Ethiopia
1 shared publication
Latest Publications
- Open Access
- 23 September 2026
- Published by SAGE Publications in Advances in Mechanical Engineering
- Vol. 18 (9)
Optimization of machining parameters in CNC end milling for surface roughness and material removal rate on AISI 4130 low-alloy steel using a Taguchi-based Gray Relational Analysis
This study applies an integrated Taguchi-Gray Relational Analysis (GRA) method to optimize CNC end milling parameters for AISI 4130 low-alloy steel, aiming to simultaneously maximize Material Removal Rate (MRR) and minimize surface roughness (Ra). Experiments were designed using an L9 orthogonal array, varying spindle speed (1200, 1400, 1600 rpm), feed rate (0.009, 0.014, 0.019 mm/tooth), and depth of cut (0.1, 0.15, 0.2 mm) under dry conditions with a high-speed steel end mill. The multi-response data were converted into a single Gray Relational Grade (GRG) for optimization. Analysis identified the optimal parameter set as 1600 rpm spindle speed, 0.019 mm/tooth feed rate, and 0.2 mm depth of cut. Analysis of Variance (ANOVA) on the GRG indicated spindle speed as the most statistically significant factor, accounting for 83.73% of the performance variation, followed by feed rate (10.11%) and depth of cut (2.25%). Confirmation experiments at the optimal settings validated the results, achieving a GRG improvement of 10.7% over the initial best run, with MRR of 31.65 cm 3 /min and Ra of 0.37 µm. The findings provide a practical framework for enhancing productivity and surface finish in the machining of AISI 4130 steel components.
- 23 September 2026
- Published by SAGE Publications in Advances in Mechanical Engineering
- Vol. 18 (9)
Open AccessOptimization of machining parameters in CNC end milling for surface roughness and material removal rate on AISI 4130 low-alloy steel using a Taguchi-based Gray Relational Analysis
This study applies an integrated Taguchi-Gray Relational Analysis (GRA) method to optimize CNC end milling parameters for AISI 4130 low-alloy steel, aiming to simultaneously maximize Material Removal Rate (MRR) and minimize surface roughness (Ra). Experiments were designed using an L9 orthogonal array, varying spindle speed (1200, 1400, 1600 rpm), feed rate (0.009, 0.014, 0.019 mm/tooth), and depth of cut (0.1, 0.15, 0.2 mm) under dry conditions with a high-speed steel end mill. The multi-response data were converted into a single Gray Relational Grade (GRG) for optimization. Analysis identified the optimal parameter set as 1600 rpm spindle speed, 0.019 mm/tooth feed rate, and 0.2 mm depth of cut. Analysis of Variance (ANOVA) on the GRG indicated spindle speed as the most statistically significant factor, accounting for 83.73% of the performance variation, followed by feed rate (10.11%) and depth of cut (2.25%). Confirmation experiments at the optimal settings validated the results, achieving a GRG improvement of 10.7% over the initial best run, with MRR of 31.65 cm 3 /min and Ra of 0.37 µm. The findings provide a practical framework for enhancing productivity and surface finish in the machining of AISI 4130 steel components.
- 29 June 2026
- Published by Springer Nature in Computing
- Vol. 108 (7)
Machine learning for process optimization in manufacturing systems: a systematic review of algorithms, applications, and performance evaluation
- 29 June 2026
- Published by Springer Nature in Computing
- Vol. 108 (7)
Machine learning for process optimization in manufacturing systems: a systematic review of algorithms, applications, and performance evaluation
- Open Access
- 2 October 2025
- Published by Springer Nature in Discover Applied Sciences
- Vol. 7 (10) , 1-23
Optimization of process parameters for sisal fiber-reinforced cornstarch biocomposites in sustainable packaging applications
- 2 October 2025
- Published by Springer Nature in Discover Applied Sciences
- Vol. 7 (10) , 1-23
Open AccessOptimization of process parameters for sisal fiber-reinforced cornstarch biocomposites in sustainable packaging applications
- Open Access
- 1 January 2024
- Published by Wiley in Advances in Materials Science and Engineering
- Vol. 2024 (1)
Experimental Characterizing Mechanical and Physical Properties of Water Lily Polyester Matrix Composite Materials
The use of natural fibers (NFs) in polymer composites is a modern trend aimed at developing materials with numerous benefits, including low cost, environmental friendliness, biodegradability, and high specific mechanical performance. Ethiopia is abundant in NFs such as palm trees, sisal, water hyacinth, and the newly emerging water lilies. In areas like Lake Tana, Ethiopia, water lilies, much like water hyacinths, negatively impact water surfaces by covering them and reducing their surface area. Therefore, analyzing the mechanical and physical properties of composites reinforced with these fibers is crucial for diverse structural and industrial applications, considering factors such as tensile strength, flexural strength, and hardness. In this study, a composite material consisting of a water lily–polyester resin matrix was prepared with varying matrix‐to‐fiber weight ratios (90/10 wt%, 80/20 wt%, 70/30 wt%, 60/40 wt%, 50/50 wt%, and 40/60 wt%). The experimental data revealed that the optimal mechanical properties, including maximum tensile strength, flexural strength, and hardness, were achieved with a composition of 60% matrix material and 40% reinforcing material. These chopped water lily fiber–reinforced polyester composites demonstrate promising mechanical and physical properties, making them suitable for various applications, similar to other NFs like sisal and palm. Further studies, such as thermal analysis, could enhance the understanding and utilization of these composites. The fabricated water lily composite can serve as a viable alternative material for applications in automobile interior parts, building components, and electronic packages.
- 1 January 2024
- Published by Wiley in Advances in Materials Science and Engineering
- Vol. 2024 (1)
Open AccessExperimental Characterizing Mechanical and Physical Properties of Water Lily Polyester Matrix Composite Materials
The use of natural fibers (NFs) in polymer composites is a modern trend aimed at developing materials with numerous benefits, including low cost, environmental friendliness, biodegradability, and high specific mechanical performance. Ethiopia is abundant in NFs such as palm trees, sisal, water hyacinth, and the newly emerging water lilies. In areas like Lake Tana, Ethiopia, water lilies, much like water hyacinths, negatively impact water surfaces by covering them and reducing their surface area. Therefore, analyzing the mechanical and physical properties of composites reinforced with these fibers is crucial for diverse structural and industrial applications, considering factors such as tensile strength, flexural strength, and hardness. In this study, a composite material consisting of a water lily–polyester resin matrix was prepared with varying matrix‐to‐fiber weight ratios (90/10 wt%, 80/20 wt%, 70/30 wt%, 60/40 wt%, 50/50 wt%, and 40/60 wt%). The experimental data revealed that the optimal mechanical properties, including maximum tensile strength, flexural strength, and hardness, were achieved with a composition of 60% matrix material and 40% reinforcing material. These chopped water lily fiber–reinforced polyester composites demonstrate promising mechanical and physical properties, making them suitable for various applications, similar to other NFs like sisal and palm. Further studies, such as thermal analysis, could enhance the understanding and utilization of these composites. The fabricated water lily composite can serve as a viable alternative material for applications in automobile interior parts, building components, and electronic packages.
- 11 October 2021
- Published by Springer Nature in Transactions of the Indian Institute of Metals
- Vol. 75 (2) , 351-360
Effect of Fabrication Parameters on the Mechanical Properties of Water Hyacinth Fiber-Reinforced High-Density Polyethylene Composite
- 11 October 2021
- Published by Springer Nature in Transactions of the Indian Institute of Metals
- Vol. 75 (2) , 351-360
Effect of Fabrication Parameters on the Mechanical Properties of Water Hyacinth Fiber-Reinforced High-Density Polyethylene Composite