National Institute of Technology, Silchar

About: National Institute of Technology, Silchar is a education organization based out in Silchar, Assam, India. It is known for research contribution in the topics: Computer science & Control theory. The organization has 1934 authors who have published 4219 publications receiving 41149 citations. The organization is also known as: NIT Silchar.

Resilient supplier selection under a fuzzy environment

Abstract: The aim of this research is to develop a quantitative approach for strategic supplier selection under a fuzzy environment in a disaster scenario. Disruption is a low probability high intensity event which causes long term system turbulence/unbalance. So resiliency planning is becoming a crucial strategic issue in the supplier selection process to keep pace with serving a globally competitive scenario. While crisp data are inadequate to model real life situations in fuzzy multiple criteria decision making, decision makers used linguistic variables to describe the importance of degrees of specific attributes. Triangular and trapezoidal linguistic data are used in determining supplier scores for various sub-criteria under general and resilient strategies, respectively. This paper presents an integrated fuzzy group decision making approach based on a fuzzy technique for order preference by similarity to the ideal solution integrated with the aggregate fuzzy weight method to rank the suppliers of a manufacturi...

Structural, electrical and optical studies on spray-deposited aluminium-doped ZnO thin films

Abstract: Thin films of zinc oxide (ZnO) were deposited on cleaned glass substrates by chemical spray pyrolysis technique using Zn(CH3COO)2 as precursor solution. Also, aluminium-doped thin films of ZnO were prepared by using AlCl3 as doping solution for aluminium. The dopant concentration [Al/Zn atomic percentage (at%)] was varied from 0 to 1.5 at% in thin films of ZnO prepared in different depositions. Structural characterization of the deposited films was performed with X-ray diffraction (XRD) studies. It confirmed that all the films were of zinc oxide having polycrystalline nature and possessing typical hexagonal wurtzite structure with crystallite size varying between 100.7 and 268.6 nm. The films exhibited changes in relative intensities and crystallite size with changes in the doping concentration of Al. The electrical studies established that 1 at% of Al-doping was the optimum for enhancing electrical conduction in ZnO thin films and beyond that the distortion caused in the lattice lowered the conductivity. The films also exhibited distinct changes in their optical properties at different doping concentrations, including a blue shift and slight widening of bandgap with increasing Al dopant concentration.

Optimization of process parameters of green electrical discharge machining using principal component analysis (PCA)

Abstract: The objective of this research is to solve the multi-response parameter optimization problems of green manufacturing. A combination of gray relational analysis (GRA) associated with principal component analysis (PCA) method has been developed and has optimized the process parameters of green electrical discharge machining (EDM). The major performance characteristics selected are process time, relative tool wear ratio, process energy, concentration of aerosol, and dielectric consumption. The corresponding machining parameters are peak current, pulse duration, dielectric level, and flushing pressure. Initially, Taguchi (L9) orthogonal array has been used to perform the experimental runs and the optimal process parameters using the GRA approach. The weighting values corresponding to various performance characteristics are determined using PCA. Thereafter, analysis of variance (ANOVA) is applied to determine the relative significant parameter and percentage of contribution of machining parameters; the peak current is the most influencing parameter having 52.87 % of contribution followed by flushing pressure, dielectric level, and pulse duration with 22.00, 21.52, and 3.55 %, respectively. Finally, multiple regression analysis is performed to determine the relationship between machining parameters and performance characteristics. The Fuzzy-TOPSIS and VIKOR methodologies have been used to compare the results of the proposed methodology, and the optimum process parameters obtained are peak current (4.5 A), pulse duration (261 μs), dielectric level (80 mm), and flushing pressure (0.3 kg/cm2).

Green synthesis of copper nanoparticles for the efficient removal (degradation) of dye from aqueous phase

Abstract: The present work reports the utilization of a common household waste material (fish scales of Labeo rohita) for the synthesis of copper nanoparticles. The method so developed was found to be green, environment-friendly, and economic. The fish scale extracts were acting as a stabilizing and reducing agents. This method avoids the use of external reducing and stabilizing agents, templates, and solvents. The compositional abundance of gelatin may be envisaged for the effective reductive as well as stabilizing potency. The mechanisms for the formation of nanoparticles have also been presented. The synthesized copper nanoparticles formed were predominantly spherical in nature with an average size of nanoparticles in the range of 25–37 nm. The copper nanoparticles showed characteristic Bragg’s reflection planes of fcc which was supported by both selected area electron diffraction and X-ray diffraction pattern and showed surface plasmon resonance at 580 nm. Moreover, the energy dispersive spectroscopy pattern also revealed the presence of only elemental copper in the copper nanoparticles. The prepared nanoparticles were used for the remediation of a carcinogenic and noxious textile dye, Methylene blue, from aqueous solution. Approximately, 96 % degradation of Methylene blue dye was observed within 135 min using copper nanoparticles. The probable mechanism for the degradation of the dye has been presented, and the degraded intermediates have been identified using the liquid chromatography-mass spectroscopy technique. The high efficiency of nanoparticles as photocatalysts has opened a promising application for the removal of hazardous dye from industrial effluents contributing indirectly to environmental cleanup process.