Processing, Please wait...

  • Home
  • 🔙 Back
  • 📚 Journals
    • ⚙️ IJIEC - Industrial Engineering Computations
    • 🌐 IJDNS - Data and Network Science
    • 🧪 CCL - Current Chemistry Letters
    • 💹 AC - Accounting
    • 🎯 DSL - Decision Science Letters
    • 🚛 USCM - Uncertain Supply Chain Management
    • 🏗️ JPM - Journal of Project Management
    • 🏥 HE - Healthcare Engineering
    • 📈 SCI - Scientometrica
    • 🔩 ESM - Engineering Solid Mechanics
    • 🌿 JFS - Journal of Future Sustainability
    • 💼 MSL - Management Science Letters
  • 📝 Submit Article
  • 📊 Statistics
  • 📋 About
    • 📄 About Us
    • 📰 Blog
    • 📢 News
    • 📧 Contact
  • 📺 Tutorial
  • Search:
  • Advanced Search

Growing Science » Engineering Solid Mechanics » A multi-faceted investigative approach to ram speed, extrusion temperature and die exit width effects on mechanical properties of extruded Al 6063 alloy

📚 Highly Cited Articles

  • Jaya Algorithm
  • Rao Algorithm
  • TLBO Algorithm
  • Discrete Firefly
  • ChatGPT and Blended Learning

Journals

  • IJIEC (805)
  • IJDS (992)
  • DSL (722)
  • ESM (434)
  • CCL (544)
  • JPM (323)
  • AC (562)
  • JFS (101)
  • MSL (2648)
  • USCM (1104)
  • HE (43)
  • SCI (46)

ESM Volumes

    • Volume 14 (30)
      • Issue 1 (9)
      • Issue 2 (8)
      • Issue 3 (7)
      • Issue 4 (6)
    • Volume 13 (32)
      • Issue 1 (12)
      • Issue 2 (7)
      • Issue 3 (7)
      • Issue 4 (6)
    • Volume 12 (41)
      • Issue 1 (10)
      • Issue 2 (9)
      • Issue 3 (12)
      • Issue 4 (10)
    • Volume 11 (39)
      • Issue 1 (10)
      • Issue 2 (10)
      • Issue 3 (9)
      • Issue 4 (10)
    • Volume 10 (35)
      • Issue 1 (9)
      • Issue 2 (8)
      • Issue 3 (10)
      • Issue 4 (8)
    • Volume 9 (36)
      • Issue 1 (9)
      • Issue 2 (9)
      • Issue 3 (9)
      • Issue 4 (9)
    • Volume 8 (36)
      • Issue 1 (8)
      • Issue 2 (10)
      • Issue 3 (9)
      • Issue 4 (9)
    • Volume 7 (28)
      • Issue 1 (7)
      • Issue 2 (6)
      • Issue 3 (7)
      • Issue 4 (8)
    • Volume 6 (32)
      • Issue 1 (8)
      • Issue 2 (8)
      • Issue 3 (8)
      • Issue 4 (8)
    • Volume 5 (25)
      • Issue 1 (7)
      • Issue 2 (6)
      • Issue 3 (6)
      • Issue 4 (6)
    • Volume 4 (25)
      • Issue 1 (5)
      • Issue 2 (7)
      • Issue 3 (7)
      • Issue 4 (6)
    • Volume 3 (27)
      • Issue 1 (7)
      • Issue 2 (7)
      • Issue 3 (6)
      • Issue 4 (7)
    • Volume 2 (32)
      • Issue 1 (6)
      • Issue 2 (8)
      • Issue 3 (10)
      • Issue 4 (8)
    • Volume 1 (16)
      • Issue 1 (4)
      • Issue 2 (4)
      • Issue 3 (4)
      • Issue 4 (4)

🔑 Keywords

Supply chain management(169)
Jordan(167)
Vietnam(154)
Customer satisfaction(124)
Performance(116)
Supply chain(113)
Artificial intelligence(99)
Service quality(98)
Competitive advantage(98)
Tehran Stock Exchange(94)
SMEs(92)
Sustainability(91)
optimization(88)
TOPSIS(85)
Trust(84)
Financial performance(84)
Job satisfaction(81)
Genetic Algorithm(80)
Knowledge Management(80)
Social media(79)


» Show all keywords

✍️ Authors

Naser Azad(82)
Zeplin Jiwa Husada Tarigan(67)
Mohammad Reza Iravani(64)
Endri Endri(45)
Muhammad Alshurideh(42)
Hotlan Siagian(40)
Dmaithan Almajali(38)
Jumadil Saputra(36)
Muhammad Turki Alshurideh(35)
Ahmad Makui(33)
Barween Al Kurdi(32)
Hassan Ghodrati(31)
Basrowi Basrowi(31)
Sautma Ronni Basana(31)
Haitham M. Alzoubi(30)
Mohammad Khodaei Valahzaghard(30)
Shankar Chakraborty(29)
Ni Nyoman Kerti Yasa(29)
Sulieman Ibraheem Shelash Al-Hawary(28)
Prasadja Ricardianto(28)


» Show all authors

🌍 Countries

1. Algeria (52)
2. Angola (1)
3. Argentina (22)
4. Armenia (2)
5. Australia (52)
6. Austria (2)
7. Bahrain (26)
8. Bangladesh (57)
9. Belarus (4)
10. Belgium (3)
11. Benin (2)
12. Benin Republic (1)
13. Bhutan (1)
14. Bosnia and Herzegovina (1)
15. Botswana (8)
16. Brazil (39)
17. Brunei (1)
18. Bulgaria (1)
19. Burkina Faso (1)
20. Cameroon (1)
Total: 121 countries

Show all countries

Engineering Solid Mechanics

ISSN 2291-8752 (Online) - ISSN 2291-8744 (Print)
Quarterly Publication
Volume 13 Issue 4 pp. 363-372 , 2025

A multi-faceted investigative approach to ram speed, extrusion temperature and die exit width effects on mechanical properties of extruded Al 6063 alloy Pages 363-372 Right click to download the paper Download PDF

Authors: Temitayo M. Azeez, Humbulani S Phuluwa

📋 Author Affiliations:
T.M. Azeez, H.S. Phuluwa (Department of Industrial Engineering and Management, University of South Africa, Pretoria, South Africa)
doi 10.5267/j.esm.2025.8.002
Crossmark
1 Source: Scopus

🔑 Keywords: Die exit width, Optimisation, Extrusion, Speed, Mechanical properties

Abstract: This research focused on the die exit width, ram speed and temperature effects on extruded Al 6063 alloy mechanical properties. It is a multiple approach that involves numerical, experimental and simulation methods in optimizing the extrusion process. The Q-Form was used in extruded sample flow stress and strain distribution analysis. The result revealed die exit width as the parameter with the most significant influence on Al 6063 alloy tensile strength and hardness, followed by extrusion temperature and then ram speed. The die width increase from 6mm to 8mm yields 73.5 % and 75.8 % tensile strength and hardness increase. The optimized process parameters predicted by the model are a speed of 16.2567 mm/s, a temperature of 526.334 °C, and a die exit diameter of 7.1862 mm, which yields a tensile strength of 151.031 MPa and a hardness of 183.644 HB, respectively. Based on Qform findings, the sample extruded using these optimal parameters yielded uniform metal flow products with low stress concentration. The research enables deep knowledge into the extrusion parameters and mechanical properties relationship, leading to aluminum alloy hot extrusion process optimization. This research has contributed to the more effective and efficient extrusion process development that can be applied in many aluminum extrusion industries. The product quality can be improved through optimized process parameters, thereby reducing the cost of production and boosting the extrusion process's overall efficiency.

How to cite this paper
APA: Azeez, T & Phuluwa, H. (2025). A multi-faceted investigative approach to ram speed, extrusion temperature and die exit width effects on mechanical properties of extruded Al 6063 alloy. Engineering Solid Mechanics, 13(4), 363-372.
Chicago/Turabian: Azeez, T & Phuluwa, H. 2025. "A multi-faceted investigative approach to ram speed, extrusion temperature and die exit width effects on mechanical properties of extruded Al 6063 alloy." Engineering Solid Mechanics 13, no. 4 (2025): 363-372.
AMA: Azeez, T & Phuluwa, H. A multi-faceted investigative approach to ram speed, extrusion temperature and die exit width effects on mechanical properties of extruded Al 6063 alloy. Engineering Solid Mechanics. 2025;13(4):363-372.

References
Alejandro, F., Pablo, Z., David, B., Fernado, P., & Pedro, F. (2025). Evaluating the influence of machine type on surface roughness in material extrusion. International Journal of Advanced Manufacturing Technology, 8, 54-60. https://link.springer.com/article/10.1007/s00170-025-15595-8.
Ali, A., Laszlo, S. T., Mate, S., Mate, S., Surya, N.K., & Valeria, M. (2025). Deformation Field and Texture Analysis in Friction-Assisted Lateral Extrusion of Aluminium. Materials Characterisation, 223(4), 1-10. http://dx.doi.org/10.1016/j.matchar.2025.114920
ASTM, 2025 “All Standards and Publications. www.astm.org/standards/B221M.htm.
Atish, C., & Inamdar, K.H. (2016). A Review of Process Parameters Affecting Aluminium Extrusion Process. International Journal of Innovative Research in Science and Engineering, 2(12), 193-198. https://www.ijirse.com/wp-content/upload/2016/02/1425.pdf.
Azeez, T. M., Mudashiru, L. O., Asafa, T. B., Adeleke, A. A. Yusuf, A. S., & Ikubanni, P. P. (2021a). Mechanical Properties and Stress Distribution in Aluminium 6063 Extrudates Processed by Equal Channel Angular Extrusion Technique. Australian Journal of Mechanical Engineering, 14, 1–9.
Azeez, T. M., Mudashiru, L. O., Adeleke, A. A., Agboola, O., & Adeshina, O. A. (2021b). Effect of Heat Treatment on Micro-Hardness and Micro-structural Properties of Al-6063 Alloy Reinforced with Silver Nanoparticles (AgPNs). International Conference on Engineering for Sustainable World, 2021, pp. 1–8.
Dyi-Cheng, C., Der-Fa, C., & Shih-Ming, H. (2024). Applying the Taguchi Method to Improve Key Parameters of Extrusion Vacuum-Forming Quality. Polymers, 16(8), 113-121. https://doi.org/10.3390/polym16081113.
Francy, K. A., Sudheer, S.V., Krishna, N. N., & Gopalakrishna, P. (2023). Optimisation of Input Process Parameters for Al 2024 Alloy in Cold Extrusion Process. Materials Today, 5, 1-4. http://dx.doi.org/10.1016/j.matpr.2023.05.427.
Hoang, T.N., Jiri, P., Zbynek, S., & David, D. (2025). Effects of Extrusion Parameters on Filament Quality and Mechanical Properties of 3D Printed PC/ABS Components. MM Science Journal, 8453-8458. DOI: 10.17973/MMSJ.2025_06_2025058.
Krzysztof, F., & Marcin, B. (2014). Use of response surface methodology in characterisation of properties of recycled high-density polyethene/ground, tire rubber. Polymery, 59, 488–494. DOI: dx.doi.org/10.14314/polimery.488.
Marco, N., Lorenzo, D., & Adrian, H.A. (2025). Smart extrusion via data-driven prediction of grain size and peripheral coarse grain defect formation. Scientific Reports,15, 9518. https://www.nature.com/articles/s41598-025-94884-4.
Marek, H., Tukasz, D., Jan, M., Roger, T., Jacek, B., Grzegorz, F., Bartosz, J., & Jacek, Z. (2025). The Application of Numerical Simulations to Analyse the Forward Extrusion Process Along with the Verification of Results and Tuning of the Numerical Model. Computer Methods in Material Science, 25(2), 27-39. https://doi.org/10.7494/cmms.2025.2.1020.
Martins, H., Patricia, V., Millan, F., & Stepan, K. (2024). The effects of strain rate and anisotropy on the formability and mechanical behaviour of aluminium alloy 2024-T3. Metals, 41(1), 98- 106.
Mehul, L., Christoph, M., & Josef, K. (2025). Multi-physics Simulation of a Material Extrusion-Based Additive Manufacturing Process: Towards Understanding Stress Formation in The Printed Strand. Progress in Additive Manufacturing, 1, 1-15. https://doi.org/10.1007/s40964-025-01012-9.
Ming, F., Fuchu, L., Yuxiao, L., Miao, W., Yiwang, S.Z., & Hao, G.H. (2025). Effect of Four Process Parameters on Flexural Strength and Porosity of Metakaolin Ceramics Fabricated by Material Extrusion: Optimisation and Predictive Models via Orthogonal Experiments. Advanced Engineering Materials, 27(2), 1-8. https://doi.org/10.1002/adem.202401197.
Qiong, W., Nian, P., Yi-Du, D., Han-jun, G., & Jian, W. (2020). A Prediction Model of the Extrusion Deformation with Residual Stress on 6063 Aluminium Alloy Aeronautical Plate Considering Different Extrusion Parameters. The International Journal of Advanced Manufacturing Technology, 107, 671-1681. https://link.springer.com/article/10.1007/s00170-020-05102-6
Sindre, L.H., Johannes, K., Aurel, R.A., Dieter, H., Georg, K., & Johannes, A.O. (2024). Parameter Study of Extrusion Simulation and Grain Structure Prediction for 6xxx Alloys with Varied Fe Content. Materials Today Communications, 38, 108. https://doi.org/10.1016/j.mtcomm.2024.108128.
Sindre, L.H., Johannes K., & Amir, H. (2025). Simulation of the Evolution of Microstructure During Extrusion of an AA6082. Materials Research Proceedings, 54(9), 829-837. https://doi.org/10.21741/9781644903599-89.
Xiangrong, J. (2024). The Optimisation of Extrusion Process Parameters Utilising the Taguchi Method. International Journal of Frontiers in Engineering Technology, 6(4), 109-114. DOI: 10.25236/IJFET.2024.060418.
Zina, S. A., & Mohammed, N. A. (2024). Experimental Investigation of the Effect of Die Shape on Mechanical Properties of Aluminium Alloy by Hot Direct Extrusion Process. International Journal of Mechanical Engineering and Robotics Research, 13(3), 331-337. doi: 10.18178/ijmerr.13.3.331-337.
Zi-Ning, L., Xiao-Qing, T., Dingyifei, M., Shahid, H., Lian, X., & Jiang, H. (2025). Optimisation of extrusion-based silicone additive manufacturing process parameters based on improved kernel extreme learning machine. Chinese Journal of Polymer Science, 43, 848-862. https://link.springer.com/article/10.1007/s10118-025-3306-x
  • 0
  • 1
  • 2
  • 3
  • 4
  • 5

Journal: Engineering Solid Mechanics | Year: 2025 | Volume: 13 | Issue: 4 | Views: 281 | Reviews: 0

Related Articles:
  • Topological optimization design of aircraft landing gear door hinge frame
  • Effect of laser shock peening on the microstructure and mechanical property of AlSi10Mg alloy parts formed by SLM
  • Influence of process parameters for tensile test specimens printed on FDM by ABS material to attain sustainability
  • Effect of frictional boundary conditions and percentage area reduction on the extrusion pressure of Aluminum AA6063 alloy using FE analysis modelling
  • Experimental and numerical prediction of extrusion load at different lubricating conditions of aluminium 6063 alloy in backward cup extrusion

📝 Ready to share your research?

Engineering Solid Mechanics is accepting new submissions for upcoming issues. Join our community of authors and publish your work with us.

✓ Open access
✓ Rigorous peer review
✓ Fast publication
📤 Submit Your Manuscript →

📖 Author Guidelines


Add Reviews

Name:*
E-Mail:
Review:
Bold Italic Underline Strike | Align left Center Align right | Insert smilies Insert link URLInsert protected URL Select color | Add Hidden Text Insert Quote Convert selected text from selection to Cyrillic (Russian) alphabet Insert spoiler
winkwinkedsmileam
belayfeelfellowlaughing
lollovenorecourse
requestsadtonguewassat
cryingwhatbullyangry
Security Code: *
Include security image CAPCHA.
Refresh Code

® 2010-2026 GrowingScience.Com