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2000
Volume 18, Issue 4
  • ISSN: 2212-7976
  • E-ISSN: 1874-477X

Abstract

Background

The recent development of new and advanced materials has led to industry experiments, innovation, and patents. As a result, various alloys were developed and implanted for multiple applications in the space, automobile, chemical, steel, and manufacturing industries. Cobalt- and nickel-based alloys have been designed to cater to high-temperature and oxidation-resistance alloys.

Objective

Here, various literature reviews are investigated, and the machining of Haynes-25 is done using an electrical discharge machine with an optimization technique of the L orthogonal selection of Taguchi. The controllable input procedure constraints are Pulse On time (T), Duty factor (D), Current (I), Gap voltage (V), and Flushing pressure (F).

Methods

The performance characteristics output parameters considered are material removal rate, tool wear rate, and surface roughness values (R). Moreover, confirmation tests are conducted to determine the percentage error of the predicted model.

Results

The confirmation tests and results showed that the duty factor and current greatly influence the M.R.R, E.W.R, and Ra machining performance. The optimized condition is obtained at the implementation of the confirmation test and using the level of significance, ., ABCDE which can be used for the patent with the value of M.R.R..R as 0.05702, E.W.R. of 0.0091, and R of 2.34. Furthermore, regression models are developed to predict the material removal rate, tool wear rate, and surface roughness.

Conclusion

It is suggested that industries use these optimum conditions to lessen unused material and raise the productivity of Haynes-25 Electrical Discharge Machining, which can be patented.

© 2025 Bentham Science Publishers
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2025-09-24

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Multi-Response Optimization of Haynes-25 Using Taguchi Grey Relational Analysis with Die-Sinking Electric Discharge Machine
Recent Patents on Mechanical Engineering 18, 420 (2025); https://doi.org/10.2174/0122127976320500240716162425
/content/journals/meng/10.2174/0122127976320500240716162425
/content/journals/meng/10.2174/0122127976320500240716162425
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  • Article Type:     Research Article
Keyword(s): ANOVA; E.D.M.; grey relational analysis (G.R.A); Haynes; multi-objective optimization; non-conventional machining

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