scholarly journals Effect of Nano-coating on Molten Salts for Turbine Blades

2020 ◽  
pp. 54-63
Author(s):  
Abbas Khammas ◽  
Haider Hashim Abbas
Keyword(s):  
Analysis Of Variance ◽  
Master Alloy ◽  
Grey Relational Analysis ◽  
Turbine Blades ◽  
Diffusion Coating ◽  
Quality Characteristics ◽  
Pack Cementation ◽  
Relational Analysis ◽  
Nano Coating ◽  
Grey Relational

The purpose of this study is to optimize hot corroded pack coated Ni-based superalloy K417G using grey relational analysis. Optimization of the pack cementation parameters was performed using quality characteristics of diffusion coatings for pack cementation process, i.e., salt activator, Nano-powders master alloy powder, and wt.% Y2O3. Analysis of variance (ANOVA) was used for observing the most influencing pack cementation parameters on the quality characteristics, i.e., Na2So4-6% wt. V2O5 (kp1), 100 wt% NaSO4 (kp2), and 75 wt. % NaSO4-25 wt % NaCl (kp3).  The optimal process parameters were calculated using a grey relation grade and a confirmation test was performed. Based on the analysis of variance results, the wt.% Y2O3 is the most significant controllable diffusion coating factor for the hot corroded pack coated K417G at optimum setting conditions (A2, B3, C3) i.e., activator (NaCl), master alloy (94Cr-6Al), and wt.%Y2O3 (4%). according to the quality characteristics. Grey relational analysis was successfully applied to the optimization of hot corroded pack coated K417G using multi-performance characteristics.

Optimization of CNC Turning Operations with Multiple Performance Characteristics using Taguchi based Grey Relational Analysis

2017 ◽  
Vol 9 (4) ◽  
Author(s):  
P. Lakshmikanthan ◽  
B. Prabu
Keyword(s):  
Analysis Of Variance ◽  
Grey Relational Analysis ◽  
Cutting Speed ◽  
Cutting Parameters ◽  
Depth Of Cut ◽  
Machining Performance ◽  
Turning Operations ◽  
Cnc Turning ◽  
Relational Analysis ◽  
Grey Relational

This study investigates the optimization of CNC turning operation parameters for Al6061 nickel coated graphite (NCG) metal matrix composite using the Taguchi based grey relational analysis method. The turning operations are carried out with carbide cutting tool inserts. According to the Taguchi quality concept, 3-level orthogonal array was chosen for the experiments. The experiments are conducted at three different cutting speeds (125, 175, 225m/min) with feed rates (0.1, 0.15, 0.2mm/rev) and depth of cut (0.5, 1, 1.5mm) and different % of reinforcement (2.5%, 5%, 7.5%), signal to noise ratio and the analysis of variance are used to optimize cutting parameters. The effects of cutting speed, feed rate and depth of cut on surface roughness and MRR are analyzed. Mathematical models are developed by using the response surface method to formulate the cutting parameters experimental results shown that machining performance can be improved effectively by using this approach, the analysis of variance (ANOVA) is applied to identify the most significant factor for the turning operations according to the weighted sum grade of the GRG. The predict responses shows the models have more than 95% of confident level of R2 value, from the obtained confirmation experiment result, it is observed, there is a good agreement between the estimated value and the experimental value of the grey relational grade. This experimental study reveals that the grey-Taguchi and RSM can be applied successfully for multi response characteristic performances.

Multi-objective optimization of micro wire electric discharge machining parameters using grey relational analysis with Taguchi method

2011 ◽  
Vol 225 (7) ◽  
pp. 1742-1753 ◽  
Author(s):  
K P Somashekhar ◽  
J Mathew ◽  
N Ramachandran
Keyword(s):  
Analysis Of Variance ◽  
Process Parameters ◽  
Electric Discharge ◽  
Grey Relational Analysis ◽  
Performance Characteristics ◽  
Electric Discharge Machining ◽  
Relational Analysis ◽  
Wire Electric Discharge Machining ◽  
Grey Relational ◽  
Wedm Process

Micro wire electric discharge machining (µ-WEDM) is an evolution of conventional wire EDM used for fabricating three-dimensional complex microcomponents, microstructures, and intricate profiles effectively with high-precision capabilities. Being a complex process, it is very difficult to determine optimal parameters for obtaining higher material removal rate (MRR) with minimum overcut (OC), and surface roughness (SR) is a challenging task in µ-WEDM for improving performance characteristics. In this study, a new approach for the optimization of the µ-WEDM process with multiple performance characteristics based on the statistical-based analysis of variance (ANOVA) and grey relational analysis (GRA) is attempted. Analysis of variance was used to study the significance of process parameters on grey relational grade (GRG) which showed capacitance to be the most significant factor. A GRG obtained from the GRA is used to optimize the µ-WEDM process. Optimum process parameters are determined by the GRG as the overall performance index. The process parameters, namely gap voltage, capacitance, and feed rate are optimized by considering multiple performance characteristics including MRR, OC, and SR. To validate the study, confirmation experiment has been carried out at optimal set of parameters, and predicted results have been found to be in good agreement with experimental findings. This approach showed improved machining performance in the µ-WEDM process.

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