Authors:
C. Navya,M. Chandra Sekhara Reddy,DOI NO:
https://doi.org/10.26782/jmcms.2026.09.00003Keywords:
WEDM,MMC,Taguchi Design,Analysis,MCDM,Grey Theory,ANFIS,Abstract
The present investigation entails the integrated optimization and modelling of the Wire Electro-Discharge Machining (WEDM) process for the stir-cast AA7050 alloy reinforced with graphite particles, forming metal matrix composites. Because of the composite's high strength and heterogeneous nature with a very fine microstructure, machining parameters must be carefully controlled for an improved process capability. A Taguchi-based design is practically followed so that important process variables-pulse-on time, pulse-off time, and peak current are effectively evaluated for their effects on important performance measures such as material removal rate (MRR), surface roughness (SR), and Dimensional Deviation (DD), and form/orientation tolerances. Grey Relational Analysis (GRA) techniques optimize the multi-objectives to analyse the best possible settings that will maximize overall performance. For modelling and prediction of the process behaviour, an Adaptive Neuro-Fuzzy Inference System (ANFIS) was developed with the Grey Relational Grade (GRG) as the output response. The ANFIS model is developed to capture the nonlinear interactions between the input variables and has a very high prediction accuracy, proving its usefulness for modelling the WEDM process. The synergistic application of Taguchi, Grey, and ANFIS modelling is a robust structure for improving the machinability of AA7050-graphite composites and aiding intelligent decision-making in advanced manufacturing applications.Refference:
I. Bharathi, P., and T. S. Kumar. “Mechanical Characteristics and Wear Behaviour of Al/SiC and Al/SiC/B4C Hybrid Metal Matrix Composites Fabricated through Powder Metallurgy Route.” Silicon, vol. 15, no. 10, 2023, pp. 4259–4275. 10.1007/s12633-023-02347-0.
II. Chawla, G., and V. K. Mittal. “Experimental Investigation and Optimization of Process Parameters of Hybrid Al/SiC/B4C–MMCs Finished by MAFM Process Using RSM Modeling with Supervised Machine Learning Algorithm.” S?dhan?, vol. 48, no. 2, 2023. 10.1007/s12046-023-02106-2.
III. Gay, D. Composite Materials: Design and Applications. 4th ed., CRC Press, 2022.
IV. Gnanavelbabu, A., K. Rajkumar, and P. Saravanan. “Investigation on the Cutting Quality Characteristics of Abrasive Water Jet Machining of AA6061-B4C-hBN Hybrid Metal Matrix Composites.” Materials and Manufacturing Processes, vol. 33, no. 12, 2018, pp. 1313–1323. 10.1080/10426914.2018.1453146.
V. Inegbenebor, A. O., et al. “Influence of the Grit Size of Silicon Carbide Particles on the Mechanical and Electrical Properties of Stir Casting Aluminum Matrix Composite Material.” Silicon, vol. 8, no. 4, 2016, pp. 573–578. 10.1007/s12633-015-9305-8.
VI. Ji, C., et al. “Recent Advances and Future Trends in Processing Methods and Characterization Technologies of Aluminum Foam Composite Structures: A Review.” Journal of Manufacturing Processes, vol. 93, 2023, pp. 116–152. 10.1016/j.jmapro.2023.03.015.
VII. Josyula, S. K., and S. K. R. Narala. “Machinability Enhancement of Stir Cast Al-TiCp Composites under Cryogenic Condition.” Materials and Manufacturing Processes, vol. 32, no. 15, 2017, pp. 1764–1774. 10.1080/10426914.2017.1303151.
VIII. Khalid, M. Y., R. Umer, and K. A. Khan. “Review of Recent Trends and Developments in 7075 Alloy and Its Metal Matrix Composites (MMCs) for Aircraft Applications.” Results in Engineering, vol. 20, 2023, article 101372. 10.1016/j.rineng.2023.101372.
IX. Khan, M. A., et al. “Application of a Hybrid Taguchi Grey Approach for Determining the Optimal Parameters on Wire Electrical Discharge Machining of Ti6Al4V.” The International Journal of Interactive Design and Manufacturing, vol. 18, no. 5, 2024, pp. 3059–3076. 10.1007/s12008-023-01440-3.
X. Maganti, N. V. R., and R. R. Potturi. “Investigation on Mechanical and Machinability Properties of Metal Matrix Composite Reinforced with Titanium Oxide (TiO2) and Graphite (Gr) Particles.” Trends in Sciences, vol. 20, no. 11, 2023, article 5682. 10.48048/tis.2023.5682.
XI. Manikandan, N., et al. “Investigations on Machinability and Evolution of Hybrid Artificial Intelligent Tools for Contemporary Machining of Nickel Alloy.” Materials and Manufacturing Processes, vol. 38, no. 12, 2023, pp. 1514–1530. 10.1080/10426914.2022.2157430.
XII. Manikandan, N., et al. “Machinability Analysis and ANFIS Modelling on Advanced Machining of Hybrid Metal Matrix Composites for Aerospace Applications.” Materials and Manufacturing Processes, vol. 34, no. 16, 2019, pp. 1866–1881. 10.1080/10426914.2019.1689264.
XIII. Manikandan, N., R. Raju, D. Palanisamy, and J. S. Binoj. “Optimisation of Spark Erosion Machining Process Parameters Using Hybrid Grey Relational Analysis and Artificial Neural Network Model.” International Journal of Machining and Machinability of Materials, vol. 22, no. 1, 2020, p. 1. 10.1504/IJMMM.2020.104007.
XIV. Manikandan, N., et al. “Applications of Artificial Intelligence Tools in Advanced Manufacturing.” Environmental Footprints and Eco-Design of Products and Processes, Springer Nature Singapore, 2024, pp. 29–42.
XV. Natarajan, M., et al. “Optimization of Spark Erosion Machining of Monel 400 Alloy for Automobile Applications.” SAE Technical Paper Series, SAE International, 2023.
XVI. Natarajan, M., et al. “Optimization of Wire Spark Erosion Machining of Grade 9 Titanium Alloy (Grade 9) Using a Hybrid Learning Algorithm.” AIP Advances, vol. 14, no. 1, 2024. 10.1063/5.0177658.
XVII. Nyanor, P., et al. “Microstructure and Mechanical Properties of Hybrid Nano-Titanium Carbide-Carbon Nanotubes (Nano-TiC-CNT) Reinforced Matrix Composite.” Advanced Composite Materials, vol. 33, no. 3, 2024, pp. 305–323. 10.1080/09243046.2023.2253097.
XVIII. Patel, K. M., P. M. Pandey, and P. V. Rao. “Study on Machinability of Al2O3 Ceramic Composite in EDM Using Response Surface Methodology.” Journal of Engineering Materials and Technology, vol. 133, no. 2, 2011. 10.1115/1.4003100.
XIX. Patil, S. P., et al. “Characterization and Machinability Studies of -Based Hybrid Metal Matrix Composites – A Critical Review.” Journal of Advanced Research in Fluid Mechanics and Thermal Sciences, vol. 101, no. 2, 2023, pp. 137–163. 10.37934/arfmts.101.2.137163.
XX. Prabu, S. B., L. Karunamoorthy, S. Kathiresan, and B. Mohan. “Influence of Stirring Speed and Stirring Time on Distribution of Particles in Cast Metal Matrix Composite.” Journal of Materials Processing Technology, vol. 171, no. 2, 2006, pp. 268–273. 10.1016/j.jmatprotec.2005.06.071.
XXI. Rajkumar, G., et al. “Parametric Optimization of Powder-Mixed EDM of AA2014/Si3N4/Mg/Cenosphere Hybrid Composites Using Fuzzy Logic: Analysis of Mechanical, Machining, Microstructural, and Morphological Characterizations.” Journal of Composites Science, vol. 7, no. 9, 2023, article 380. 10.3390/jcs7090380.
XXII. Rajmohan, T., and K. Palanikumar. “Experimental Investigation and Analysis of Thrust Force in Drilling Hybrid Metal Matrix Composites by Coated Carbide Drills.” Materials and Manufacturing Processes, vol. 26, no. 8, 2011, pp. 961–968. 10.1080/10426914.2010.523915.
XXIII. Sah, S., S. Sardar, A. Guha, and D. Das. “Electrical Discharge Machining of Hybrid Metal Matrix Composites: A Comprehensive Review.” The International Journal of Advanced Manufacturing Technology, 2024. 10.1007/s00170-024-14805-z.
XXIV. Sarmah, P., and K. Gupta. “A Review on the Machinability Enhancement of Metal Matrix Composites by Modern Machining Processes.” Micromachines, vol. 15, no. 8, 2024, article 947. 10.3390/mi15080947.
XXV. Seikh, Z., et al. “A Study on Various Applications of Metal Matrix Composites.” AIP Conference Proceedings, vol. 2899, AIP Publishing, 2023, article 070009.
XXVI. Singh, J., and A. Chauhan. “Characterization of Hybrid Aluminum Matrix Composites for Advanced Applications – A Review.” Journal of Materials Research and Technology, vol. 5, no. 2, 2016, pp. 159–169. 10.1016/j.jmrt.2015.05.004.
XXVII. Sivananth, V., S. Vijayarangan, and N. Rajamanickam. “Evaluation of Fatigue and Impact Behavior of Titanium Carbide Reinforced Metal Matrix Composites.” Materials Science and Engineering: A, vol. 597, 2014, pp. 304–313. 10.1016/j.msea.2014.01.004.
XXVIII. Suthar, J., and K. M. Patel. “Processing Issues, Machining, and Applications of Aluminum Metal Matrix Composites.” Materials and Manufacturing Processes, vol. 33, no. 5, 2018, pp. 499–527. 10.1080/10426914.2017.1401713.
XXIX. Thejasree, P., et al. “Application of ANFIS Approach for Prediction of Performance Measures in Wire Electric Discharge Machining of SAE 1010.” Interactions, vol. 245, no. 1, 2024. 10.1007/s10751-024-02030-9.
XXX. Thejasree, P., et al. “Development of an Artificial Intelligence Model for Wire Electrical Discharge Machining of Inconel 625 in Biomedical Applications.” IET Collaborative Intelligent Manufacturing, vol. 6, no. 4, 2024. 10.1049/cim2.70015.
XXXI. Vardhan, T. V., B. Yelamasetti, and D. V. V. Pavan Kumar. “Study on Characteristic Evaluation and Industrial Applications of Metal and Nano-Metal Matrix Composites.” Metal Matrix Composites, CRC Press, 2023, pp. 17–28.
XXXII. “Soft Computing in the Design and Manufacturing of Composite Materials: Applications to Brake Friction and Thermoset Matrix Composites.” [Publication information not provided].
XXXIII. Thejasree, P., et al. “Application of ANFIS Approach for Prediction of Performance Measures in Wire Electric Discharge Machining of SAE 1010.” Interactions, vol. 245, no. 1, 2024. 10.1007/s10751-024-02030-9.