Parametric analysis, modeling and optimization of the process parameters in electric discharge machining of aluminium metal matrix composite

Engineering Research Express, Год журнала: 2024, Номер 6(2), С. 025542 - 025542

Опубликована: Май 14, 2024

Abstract Optimizing electric discharge machining (EDM) for aluminum/SiC p metal matrix composites poses challenges due to intricate machine parameters and process complexity, impacting economy elevating product costs. The research aims find the optimal combination of which include pulse on-time, current, duty cycle (%), gap voltage, sensitivity flushing pressure EDM Al/SiC -MMC using a copper electrode selected response factors such as material erosion rate surface roughness, R . experiments were designed central composite design methodology an advanced optimization technique known Teaching–learning-based (TLBO), is applied obtain maximum subject desired range roughness (SR), high on-time (i.e. 150 μ s) current 12A) results in removal with deep craters on machined clearly visible SEM images contrasting minimized at lower values (50 (4A). Pulse - time (T ) found be most significant factor percentage contribution 70.86 54.9 respectively response. regression models developed 95% confidence level 2 value 0.93 0.95 signifying degree accuracy predicting Confirmation tests conducted check adequacy established revealed that error between predicted experimental responses within acceptable levels. Electron aluminium optimized conditions could provide economical aspect aerospace automobile industry.

Язык: Английский

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Multi-objective optimization to enhance surface integrity in WEDM for Al-matrix composite: a comparative assessment of self-weight adjusting MCDMs and objective weight integrated hybrid TOPSIS methods

Results in Surfaces and Interfaces, Год журнала: 2025, Номер unknown, С. 100467 - 100467

Опубликована: Фев. 1, 2025

Язык: Английский

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Tribomechanical, and microstructural morphological analysis of nitride ferrous powder metallurgy composites for enhanced automotive valve guide performance

Journal of Materials Research and Technology, Год журнала: 2024, Номер 31, С. 6 - 25

Опубликована: Июнь 2, 2024

The growing challenges of reducing exhaust emissions and improved fuel economy has triggered automotive engineers to design manufacture engine parts with superior mechanical properties dimensional accuracies. Valve guides are cylindrical structures supporting inlet valve stems during operation. Conventionally made grey cast iron material, guide suffers from severe wear losses leading loss increased due improper stem seating. Here, the synthesis a novel ferrous powder metallurgy composite is presented characteristics have been studied at varying loads 30 N, 40 N 50 sliding speeds 0.5 m/s, 1 m/s 2 under lubricated conditions. samples undergone nitriding heat treatment 1150 °C improve surface hardness 700 Hv. shown negative rates high capillary action lubricating oil exhibited stable friction coefficient values. This attributed formation hard phases Fe2N, Fe3N, Fe4N Fe(Mn)3C twinning-induced plastic compounds like (Fe24Mn) 0.08 as evident XRD analysis. morphological analysis worn out was done SEM Coupled EDS it showed micro-cutting, Ploughing, delamination main phenomenon.

Язык: Английский

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Surface roughness and cutting force in turning of alkaline-treated banana fibre-reinforced polymer composite: Compressed air cutting

Journal of Reinforced Plastics and Composites, Год журнала: 2024, Номер unknown

Опубликована: Янв. 22, 2024

Banana fibre-reinforced polymer (BaFRP) composite can ensure environmentally friendly decomposition of waste material and reduction cost in comparison with traditionally used fibre material. This article emphasizes the influence various machining constraints on surface roughness (R a ) cutting force (P z turning alkaline-treated banana (T-BaFRP) composite. 30% weight fraction yields satisfactory mechanical properties. Taguchi orthogonal array L25 is to design experiments optimization using DFA TOPSIS. An experimental investigation was conducted under compressed cooling air-cutting conditions where pressure kept at 8 bar. Analysis variance depicts that depth cut feed rate are most prominent factors for force. The predicted values error 0.517% 1.181% TOPSIS reported optimal cut, speed, 0.362 mm, 55 m/min, 0.113 mm/rev, 0.8 154 0.12 respectively. R 2.594 µm P 14.258 N by 3.02 25.83 method have been attained. Moreover, confirmation test suggests both response parameters (surface force) close alignment results from

Язык: Английский

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Predicting Specific Wear Rate of Laser Powder Bed Fusion AlSi10Mg Parts at Elevated Temperatures Using Machine Learning Regression Algorithm: Unveiling of Microstructural Morphology analysis

Journal of Materials Research and Technology, Год журнала: 2024, Номер unknown

Опубликована: Сен. 1, 2024

Язык: Английский

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Machine Learning-Based Assessment of the Influence of Nanoparticles on Biodiesel Engine Performance and Emissions: A critical review

Archives of Computational Methods in Engineering, Год журнала: 2024, Номер unknown

Опубликована: Июнь 13, 2024

Язык: Английский

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Surface Integrity Characteristics and Multi-response Optimization in Wire-EDM of Al–Al3Fe Composites

Arabian Journal for Science and Engineering, Год журнала: 2024, Номер 49(11), С. 15289 - 15324

Опубликована: Апрель 16, 2024

Язык: Английский

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Machine learning-enabled powder-spreading process

Elsevier eBooks, Год журнала: 2025, Номер unknown, С. 107 - 130

Опубликована: Янв. 1, 2025

Язык: Английский

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Artificial intelligence based prediction and multi-objective RSM optimization of tectona grandis biodiesel with Elaeocarpus Ganitrus

Scientific Reports, Год журнала: 2025, Номер 15(1)

Опубликована: Янв. 30, 2025

Язык: Английский

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Enhanced Mechanical Properties and Machinability of Al-Cu-SiC-GNP Smart Hybrid Composite Using Machine Learning Optimization

Arabian Journal for Science and Engineering, Год журнала: 2025, Номер unknown

Опубликована: Фев. 5, 2025

Язык: Английский

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