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Process optimization for hot forging of difficult parts by computer experiments and response surface analysis

Year 2022, Volume: 3 Issue: 2, 33 - 45, 11.01.2023

Barış Kabataş Haydar Livatyalı , Birgül Aşçıoğlu Temiztaş

Abstract

Closed die hot forging of 304L stainless steel is difficult compared to carbon and micro-alloyed steels in terms of higher forming force and defects. An appropriate combination of design and process factors including cross-section diameter, initial billet temperature, and flash land thickness is crucial to minimize the forming force without causing any under-filling or folding defects. This paper aims to develop an optimized closed-die hot forging process for long, thin, and tubular rail body components used in gasoline direct injection systems. The effects on the forging load are investigated using computer experiments containing the finite element method under a full factorial array of three factors at three levels to obtain the main and interaction effects. Linear and quadratic surface response analyses are performed to define the relation between forging load and input factors, and finally, the simulations are validated with some limited experiments. The simulation results that fit the nonlinear regression model were in close agreement with the experiments, and an optimal set of parameters is conveniently proposed for industrial production.

Keywords

Computer experiments hot forging surface response methodology.

Year 2022, Volume: 3 Issue: 2, 33 - 45, 11.01.2023

Barış Kabataş Haydar Livatyalı , Birgül Aşçıoğlu Temiztaş

Abstract

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Details

Primary Language English
Subjects Mechanical Engineering
Journal Section Research Articles
Authors

Barış Kabataş This is me 0000-0002-2160-3746

Haydar Livatyalı 0000-0002-9542-2390

Birgül Aşçıoğlu Temiztaş 0000-0003-2459-8708

Publication Date January 11, 2023
Published in Issue Year 2022 Volume: 3 Issue: 2

Cite

APA Kabataş, B., Livatyalı, H., & Aşçıoğlu Temiztaş, B. (2023). Process optimization for hot forging of difficult parts by computer experiments and response surface analysis. Journal of Advances in Manufacturing Engineering, 3(2), 33-45.
AMA Kabataş B, Livatyalı H, Aşçıoğlu Temiztaş B. Process optimization for hot forging of difficult parts by computer experiments and response surface analysis. J Adv Manuf Eng. January 2023;3(2):33-45.
Chicago Kabataş, Barış, Haydar Livatyalı, and Aşçıoğlu Temiztaş Birgül. “Process Optimization for Hot Forging of Difficult Parts by Computer Experiments and Response Surface Analysis”. Journal of Advances in Manufacturing Engineering 3, no. 2 (January 2023): 33-45.
EndNote Kabataş B, Livatyalı H, Aşçıoğlu Temiztaş B (January 1, 2023) Process optimization for hot forging of difficult parts by computer experiments and response surface analysis. Journal of Advances in Manufacturing Engineering 3 2 33–45.
IEEE B. Kabataş, H. Livatyalı, and B. Aşçıoğlu Temiztaş, “Process optimization for hot forging of difficult parts by computer experiments and response surface analysis”, J Adv Manuf Eng, vol. 3, no. 2, pp. 33–45, 2023.
ISNAD Kabataş, Barış et al. “Process Optimization for Hot Forging of Difficult Parts by Computer Experiments and Response Surface Analysis”. Journal of Advances in Manufacturing Engineering 3/2 (January 2023), 33-45.
JAMA Kabataş B, Livatyalı H, Aşçıoğlu Temiztaş B. Process optimization for hot forging of difficult parts by computer experiments and response surface analysis. J Adv Manuf Eng. 2023;3:33–45.
MLA Kabataş, Barış et al. “Process Optimization for Hot Forging of Difficult Parts by Computer Experiments and Response Surface Analysis”. Journal of Advances in Manufacturing Engineering, vol. 3, no. 2, 2023, pp. 33-45.
Vancouver Kabataş B, Livatyalı H, Aşçıoğlu Temiztaş B. Process optimization for hot forging of difficult parts by computer experiments and response surface analysis. J Adv Manuf Eng. 2023;3(2):33-45.
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