Rajesh Kumar Porwal

Bio: Rajesh Kumar Porwal is an academic researcher from Memorial University of Newfoundland. The author has contributed to research in topics: Electrical discharge machining & Machining. The author has an hindex of 2, co-authored 11 publications receiving 7 citations.

Experimental Modeling of EDMed Aluminum Metal Metrix Composite: A Review

Abstract: Electrical discharge machining is uttermost exploited material removal process broadly used in manufacturing industries for variegate shapes and difficult-to-machine electrically conductive materials. The nascent materials such as metal matrix composites, ceramic composites, duplex stainless steels, and titanium alloys have a vast demand in the area of automobiles, aircraft, aerospace, railways, and micro industries. The machining of these materials using conventional machining process is bonded to linear cutting to overcome this problem EDM was introduced. Many researchers have presented a vast work to understand the material removal mechanism of EDM and conclude that machining performance is mostly affected by process parameters. The machining performance can predict in appropriate way using process modeling techniques. The process modeling of materials like carbon nano-tube reinforced MMC is still needed a lot of research work. This paper includes review of AMC machining and experimental modeling using various methods such as RSM and ANN.

Modeling and optimization of cutting forces and effect of turning parameters on SiCp/Al 45% vs SiCp/Al 50% metal matrix composites: a comparative study

Abstract: In this study, the proposed experimental and second-order model for the cutting forces were developed through several parameters, including cutting speed, feed rate, depth of cut, and two varying content of SiCp. Cutting force model was developed and optimized through RSM and compared for two different percentages of components SiCp/Al 45% and SiCp/Al 50%. ANOVA is used for Quantitative evaluation, the main effects plot along with the evaluation using different graphs and plots including residual analysis, contour plots, and desirability functions for cutting forces optimization. It provides the finding for choosing proper parameters for the machining process. The plots show that during increment with depth of cut in proportion with feed rate are able to cause increments in cutting forces. Higher cutting speed shows a positive response in both the weight percentage of SiCp by reducing the cutting force because of higher cutting speed increases. A very fractional increasing trend of cutting force was observed with increasing SiCp weight percentages. Both of the methods such as experiment and model-predicted results of SiCp/Al MMC materials were thoroughly evaluated for analyzing cutting forces of SiCp/Al 45%, and SiCp/Al 50%, as well as calculated the error percentages also found in an acceptable range with minimal error percentages.

Multi-response Optimization and Effect of Alumina Mixed with Dielectric Fluid on WEDM Process of Ti6Al4V

Abstract: Titanium and titanium alloys (Ti6Al4V) are functional materials that have various uses in the marine, chemical, biomedical, aerospace fields because of their unique combination of mechanical and physical properties. Conventional machining of Ti6Al4V is difficult owing to its high hardness, higher chemical reactivity, and lower thermal conductivity. Non-contact operation between tool and work material such as wire electrical discharge machining (WEDM) process was found to be most effective. In the current study, the effect of different input machining parameters of the WEDM process has been studied for Ti6Al4V. Selected input WEDM process parameters based on past literature include pulse on time (Ton), pulse off time (Toff), and current while material removal rate (MRR) and surface roughness (SR) as the response variables. Grey relational analysis (GRA) technique along with Taguchi’s design was used for attaining multiple objectives simultaneously. A validation study was conducted to verify obtained results from optimization. Lastly, results obtained by GRA at optimal parameter settings were compared with nano-alumina powder mixed with dielectric fluid at a concentration of 1 g/l. Improvement in the value of MRR and SR was found by 22.08% and 16.25%, respectively, for Ti6Al4V.

Augmented Reality Visualization of Modal Analysis Using the Finite Element Method

Abstract: Modal analysis provides the dynamic behavior of an object or structure, and is often undertaken using the Finite Element Method (FEM) due to its ability to deal with arbitrary geometries This article investigates the use of Augmented Reality (AR) to provide the in situ visualization of a modal analysis for an aluminum impeller Finite Element Analysis (FEA) software packages regularly use heat maps and shape deformation to visualize the outcomes of a given simulation AR allows the superimposition of digital information on a view of the real-world environment, and provides the opportunity to overlay such simulation results onto real-world objects and environments The presented modal analysis undertaken herein provides natural frequencies and the corresponding deformation of an aluminum impeller The results indicate the ability for the design part and finite element analysis results to be viewed on the physical part A mobile AR-FEA-based system was developed for Modal Analysis result visualization This study offers designers and engineers a new way to visualize such simulation results

Evolutionary algorithm for the prediction and optimization of SiCp/Al metal matrix composite machining

Abstract: This article attempts the optimization study of machining of SiCp/Al metal matrix composite (MMC) material to analyze the most suitable cutting parameters on tool life and surface quality. The research study integrated the effects of three machining parameters, cutting speed, feed rate, and depth of cut with carbide cutting tools. The optimization prediction model of machining parameters was established, and the influence of machining parameters on tool life and surface roughness and their interaction were studied. Through analysis, the key factors affecting tool life and surface roughness are determined. Combining the process parameters, advanced computation method was employed to predict responses and to compare it with the experimental data. The results show that, in this study, machining indexes such as tool life and surface roughness are mainly affected with increasing feed rate followed by the depth of cut. However, surface roughness reduces as the cutting speed increases slightly. Statistical methods have a level to a certain extent to determine its ability as a powerful method for analyzing SiCp/Al composite material processing.