Experimental Analysis of the Machinability of AISI 1.2738 Steel by Sinking EDM Based on Voltage, Pulse-Off Time, and Tool Feed Rate

Abstract

The aim of this study is to investigate the effects of voltage, pulse-off time (Toff), and tool feed rate on the machinability of AISI 1.2738 mold steel in die-sinking electrical discharge machining (EDM). Experimental studies were carried out using a full factorial design with 3³ = 27 test conditions, and the material removal rate (MRR) and surface roughness (Ra) were evaluated as the main performance indicators. The results showed that increasing the voltage raised the MRR from 6.29 g/min to 9.13 g/min (approximately 45% improvement), while Ra increased from 5.19 µm to 8.88 µm, indicating a deterioration in surface quality. Increasing the pulse-off time improved the surface roughness by about 25% but caused an 18% reduction in MRR. Raising the tool feed rate from 6 mm/s to 10 mm/s had a limited influence, with a 6% increase in MRR and a 4% improvement in Ra. The findings revealed that MRR reached a saturation level at higher voltage values, with the optimum machining performance achieved around the 2–3 V range. These results provide an original contribution to the literature as one of the few systematic studies focusing on the effect of tool feed rate in the EDM processing of AISI 1.2738 steel.

Keywords

• Electrical discharge machining
• AISI 1.2738
• Voltage
• Tool feed rate
• Pulse-off time
• Material removal rate
• Surface roughness

Thanks

The authors would like to express their gratitude to POELSAN Plastic Industry and Trade Inc. for their support in terms of material supply, experimental facilities, and machine access. We also extend our thanks to the laboratory staff for their technical assistance during the experimental studies, and to the Faculty of Engineering workshop team for their help with equipment operation. This research did not receive direct funding from external agencies, but it was carried out with the support of the university’s infrastructure and institutional resources.

AISI 1.2738 Çeliğinin Dalma Erozyonla İşlenebilirliğinin Voltaj, Darbesiz Süre ve Takım İlerleme Hızına Bağlı Deneysel Analizi

Abstract

Bu çalışmanın amacı, AISI 1.2738 kalıp çeliğinin dalma erozyonla işlenmesinde voltaj, darbesiz geçen süre (Toff) ve takım ilerleme hızının işlenebilirlik üzerindeki etkilerini belirlemektir. Deneysel çalışmalar, 3³ = 27 koşuldan oluşan tam faktöriyel tasarım yöntemiyle gerçekleştirilmiş ve malzeme işleme hızı (MİH) ile yüzey pürüzlülüğü (Ra) ana performans kriterleri olarak değerlendirilmiştir. Sonuçlar, voltaj artışının MİH değerini 6.29 g/dk’dan 9.13 g/dk’ya yükselttiğini (%45 artış), buna karşılık Ra değerinin 5.19 µm’den 8.88 µm’ye çıkarak yüzey kalitesini olumsuz etkilediğini göstermiştir. Toff süresinin artışı yüzey pürüzlülüğünde yaklaşık %25 iyileşme sağlarken MİH’te %18 azalmaya neden olmuştur. Takım ilerleme hızının 6 mm/sn’den 10 mm/sn’ye çıkarılması, MİH’te %6 artış ve Ra’da %4 iyileşme ile sınırlı bir etki yaratmıştır. Bulgular, voltaj artışına bağlı olarak MİH değerlerinin yüksek seviyelerde doyuma ulaştığını ve optimum işlem koşulunun 2–3 V aralığında elde edildiğini ortaya koymuştur. Bu sonuçlar, AISI 1.2738 çeliğinin DEİ ile işlenebilirliğinde takım ilerleme hızının etkisini sistematik biçimde inceleyen nadir çalışmalardan biri olarak literatüre özgün bir katkı sunmaktadır.

Keywords

• Dalma erozyon
• AISI 1.2738
• Voltaj
• Takım ilerleme hızı
• Darbesiz geçen süre
• Malzeme işleme hızı
• Yüzey pürüzlülüğü

Thanks

Bu çalışma, deneylerin gerçekleştirilmesi, malzeme temini ve tezgâh kullanım imkânları açısından destek sağlayan POELSAN Plastik Sanayi ve Ticaret A.Ş.’ye teşekkürlerimizi sunarız. Ayrıca, deneysel çalışmalar sırasında teknik destek sağlayan laboratuvar personeline ve cihaz kullanımında yardımcı olan mühendislik fakültesi atölye ekibine teşekkür ederiz. Bu araştırmaya doğrudan fon sağlayan bir kuruluş bulunmamakla birlikte, üniversite altyapısı ve kurumsal destek sayesinde gerçekleştirilmiştir.

References

1. Rachman, F., Purnomo, D. A., Fajardini, R. A., & Umami, R. R. (2021). Optimization of surface roughness of AISI P20 on electrical discharge machining sinking process using Taguchi method. JTAM (Jurnal Teori dan Aplikasi Matematika), 5(1), 50-59.
2. Rachman, F., Purnomo, D. A., Fajardini, R. A., & Umami, R. R. (2021). Optimization of surface roughness of AISI P20 on electrical discharge machining sinking process using Taguchi method. JTAM (Jurnal Teori dan Aplikasi Matematika), 5(1), 50-59.
3. Eyercioğlu, Ö., Göv, K., & Aksoy, A. (2018). Abrasive Flow Machining Of Asymmetric Spur Gear Forging Die. Harran Üniversitesi Mühendislik Dergisi, 4(1), 12-20.
4. Kar, S., C A, N., NR, P., Majumder, T., Baroi, B. K., & Kebede, A. W. (2025). Experimental investigation and parametric optimization of machinability and surface characteristics in wire EDM of Inconel 718. Scientific Reports, 15(1), 33947.
5. Jagdale, M., Abdullah, M., Ambhore, N., Kulkarni, A., Chaudhari, R., Vora, J., & Menyhárt, J. (2025). Performance evaluation and multi-objective optimization of EDM parameters for Ti6Al4V using different tool electrodes. Scientific Reports, 15(1), 30239.
6. Pham, H. V., Nguyen, H. P., Shailesh, S., Nguyen, D. T., & Bui, N. T. (2024). Improving Micro-EDM machining efficiency for titanium alloy fabrication with advanced coated electrodes. Micromachines, 15(6), 692.
7. Duan, X., & Shi, Z. (2024). Sedimentary records of sea level fall during the end-Permian in the upper Yangtze region (southern China): Implications for the mass extinction. Heliyon, 10(10).
8. Samantra, C., Barua, A., Pradhan, S., Kumari, K., & Pallavi, P. (2024). Parametric investigation of die-sinking EDM of Ti6Al4V using the hybrid Taguchi-RAMS-RATMI method. Applied Sciences, 14(16), 7139.

9. Chaubey, S. K., & Gupta, K. (2025). Review of EDM-Based Machining of Nickel–Titanium Shape Memory Alloys. Quantum Beam Science, 9(4), 28.
10. Jagadish, H. V., Zindani, D., Selvam, A., Tejani, G. G., & Santhosh, A. J. (2025). Optimization of process parameter for green die sinking electrical discharge machining: a novel hybrid decision-making approach. Scientific Reports, 15(1), 13489.
11. Salvide-González, U., Puertas-Arbizu, I., & Luis-Pérez, C. J. (2024). Experimental Analysis of the Machinability of 94 WC–6 Co by Die-Sinking EDM. Materials, 17(24), 6032.
12. Ali, S., Aidossova, A., Begassilova, N., Gissa, A., Talamona, D., & Perveen, A. (2025). Investigating die-sinking EDM drilling performance on additively manufactured SS316L steel lattice structures. Manufacturing Letters, 44, 651-660.
13. Wei, H., Zhou, J., Shen, B., & Kang, X. (2025). Study of polarity effect on die-sinking EDM with graphite electrodes. Procedia CIRP, 137, 70-75.
14. Malo, Y. (2023). DIN 1.2344 çeliğinin elektro erozyon ile işlenmesinde işleme parametrelerinin optimizasyonu (Master's thesis, Amasya Üniversitesi).
15. Nas, E., Argun, K., & Zurnacı, E. (2018). AISI 1.2738 Çeliğinin Elektro-Erozyon Tezgahında Grafit Elektrot ile İşlenmesinde İşleme Parametrelerinin Yüzey Pürüzlülüğü Üzerine Etkisinin İncelenmesi. Düzce Üniversitesi Bilim ve Teknoloji Dergisi, 6(4), 1082-1093.
16. Mouralová, K., Bednar, J., Benes, L., Hrabec, P., Kalivoda, M., & Fries, J. (2020). The analysis of EDM electrodes wear in corners and edges. Archives of Civil and Mechanical Engineering, 20(4), 130.
17. Joshi, A., Saraf, A. K., & Goyal, R. K. (2020). EDM machining of die steel EN8 and testing of surface roughness with varying parameters. Materials Today: Proceedings, 28, 2557-2560.
18. Sahu, A. K., & Mahapatra, S. S. (2020). Surface characteristics of EDMed titanium alloy and AISI 1040 steel workpieces using rapid tool electrode. Arabian Journal for Science and Engineering, 45(2), 699-718.
19. Yahya, A., & Manning, C. D. (2004). Determination of material removal rate of an electro-discharge machine using dimensional analysis. Journal of Physics D: Applied Physics, 37(10), 1467.
20. Purohit, R., Rana, R. S., Dwivedi, R. K., Banoriya, D., & Singh, S. K. (2015). Optimization of electric discharge machining of M2 tool steel using grey relational analysis. Materials Today: Proceedings, 2(4-5), 3378-3387.
21. Świercz, R., & Oniszczuk-Świercz, D. (2017). Experimental investigation of surface layer properties of high thermal conductivity tool steel after electrical discharge machining. Metals, 7(12), 550.
22. Laxminarayana, P., & Aravindan, N. (2017). Study of surface morphology on micro machined surfaces of AISI 316 by Die Sinker EDM. Materials Today: Proceedings, 4(2), 1285-1292.
23. Prasad, L., & Gupta, A. (2017). An experimental investigation of machining parameters for EDM using copper electrode of Aisi P20 tool steel. Asian J Sci Technol, 8(01), 4106-4111.
24. Molinetti, A., Amorim, F. L., Soares Jr, P. C., & Czelusniak, T. (2016). Surface modification of AISI H13 tool steel with silicon or manganese powders mixed to the dielectric in electrical discharge machining process. The International Journal of Advanced Manufacturing Technology, 83(5), 1057-1068.
25. Singh, V., & Pradhan, S. K. (2014). Optimization of EDM process parameters: a review. International Journal of Emerging Technology and advanced engineering, 4(3), 345-355.
26. Sanghani, C. R., & Acharya, G. D. (2014). A review of research on improvement and optimization of performance measures for electrical discharge machining.
27. Khan, M. A. R., Rahman, M. M., Kadirgama, K., Maleque, M. A., & Bakar, R. A. (2011). Artificial intelligence model to predict surface roughness of Ti-15-3 alloy in EDM process. World Academy of Science, Engineering and Technology, 74, 198-202.
28. Joshi, S. N., & Pande, S. S. (2011). Intelligent process modeling and optimization of die-sinking electric discharge machining. Applied soft computing, 11(2), 2743-2755.
29. Somashekhar, K. P., Ramachandran, N., & Mathew, J. (2010). Optimization of material removal rate in micro-EDM using artificial neural network and genetic algorithms. Materials and Manufacturing processes, 25(6), 467-475.
30. Lee, D. H., Malhotra, N., & Jung, D. W. (2017, July). Multi characteristic optimization in die sinking EDM of En31 tool steel using utility concept. In 2017 8th International Conference on Mechanical and Aerospace Engineering (ICMAE) (pp. 166-170). IEEE.
31. Singh, N. K., Singh, Y., Kumar, S., & Sharma, A. (2019). Comparative study of statistical and soft computing-based predictive models for material removal rate and surface roughness during helium-assisted EDM of D3 die steel. SN Applied Sciences, 1(6), 529.
32. Kumar, B. K., & Das, V. C. (2023). Study and parameter optimization with AISI P20+ Ni in Wire EDM performance using RSM and hybrid DBN based SAR. International Journal on Interactive Design and Manufacturing (IJIDeM), 17(2), 679-701.
33. Kumar, B. K., & Das, V. C. (2024). Prediction and Optimization of Ultrasonic Vibration Assisted Wire EDM Process for AISI P20+ Ni Using COOT Optimization Algorithm Based Deep Neural Network. Journal of Vibration Engineering & Technologies, 12(Suppl 1), 613-632.
34. Erkan, Ö. (2025). Surface roughness optimization of new-generation WP7V tool steel in WEDM: a Taguchi and RSM approach. Multidiscipline Modeling in Materials and Structures.
35. Patil, S., Kulkarni, R., Patil, M., & Malik, V. R. (2024). Investigations on material removal and tool wear rate of silver nanoparticles coated copper electrodes for electric discharge machining. Advances in Materials and Processing Technologies, 10(4), 3067-3095.
36. Tezel, T., Topal, E. S., & Kovan, V. (2018). Hibrit imalat: eklemeli imalat ile talaşli imalat yöntemlerinin birlikte kullanılabilirliğinin incelenmesi. International Journal of 3D Printing Technologies and Digital Industry, 2(3), 60-65.
37. Üstündağ, M., & Varol, R. (2019). TM Titanyum Alaşımlarına Sinter-HIP Yönteminin Uygulanması. Harran Üniversitesi Mühendislik Dergisi, 4(1), 48-55.
38. Tiwari, R. K. (2015). Multi-objective optimization of electrical discharge machining process parameters using genetic algorithm. International Journal of Engineering Research and General Science, 3(3), 1411-1423.
39. Straka, Ľ., & Hašová, S. (2018). Optimization of material removal rate and tool wear rate of Cu electrode in die-sinking EDM of tool steel. The International Journal of Advanced Manufacturing Technology, 97(5), 2647-2654.
40. Straka, Ľ., & Hašová, S. (2018). Optimization of material removal rate and tool wear rate of Cu electrode in die-sinking EDM of tool steel. The International Journal of Advanced Manufacturing Technology, 97(5), 2647-2654.
41. Tosun, N., Cogun, C., & Inan, A. (2003). The effect of cutting parameters on workpiece surface roughness in wire EDM. Machining science and technology, 7(2), 209-219.
42. Singh, R., Dhami, S. S., & Rajput, N. (2022). Comparison of EDM and ECM machined AISI 304 steel: Surface roughness, hardness and morphological characteristics. Materials today: proceedings, 48, 965-974.