scholarly journals An Experimental Investigation into the Amalgamated Al<sub>2</sub>O<sub>3</sub>-40% TiO<sub>2</sub> Atmospheric Plasma Spray Coating Process on EN24 Substrate and Parameter Optimization Using TLBO

2016 ◽  
Vol 04 (06) ◽  
pp. 51-65
Author(s):  
Thankam Sreekumar Rajesh ◽  
Ravipudi Venkata Rao
Keyword(s):  
Experimental Investigation ◽  
Parameter Optimization ◽  
Plasma Spray ◽  
Spray Coating ◽  
Atmospheric Plasma Spray ◽  
Atmospheric Plasma ◽  
Coating Process ◽  
Plasma Spray Coating

scholarly journals MODELING OF PLASMA SPRAY COATING PROCESS USING ROBUST SOLUTIONS BASED ON NEW INTELLIGENCE METHODS

2017 ◽  
Vol 39 (3) ◽  
pp. 553
Author(s):  
Mehdi Abedi-Varaki ◽  
Shahram Mollaiy- Berneti
Keyword(s):  
Neural Network ◽  
Flow Rate ◽  
Plasma Spray ◽  
Spray Coating ◽  
Support Vector ◽  
Group Method ◽  
Coating Process ◽  
Micro Hardness ◽  
Plasma Spray Coating ◽  
Polynomial Neural Network

This study adopts two computational intelligence techniques namely least-squares support vector machine (LS-SVM) and group method of data handling (GMDH) type polynomial neural network to model the plasma spray coating process. The coating qualities were evaluated by determining its thickness, porosity and micro-hardness. Four parameters including primary gas flow rate, stand-off distance, powder flow rate and arc current that affecting the coating properties were chosen as input variables in model development. The performances of the developed models were evaluated by calculating the deviations between the predicted and the actual values based on the  performance indices of mean absolute error (MAE), root mean  square  error  (RMSE) and coefficient of determination (R2). The results demonstrate thehigh capability of the LS-SVM and GMDH-type polynomial neural network for prediction of thickness and micro-hardness values with lowest MAE, RMSE and highest R2. Due to the high non-linearity behavior of porosity in coating process, the results obtained by these models for porosity are not very well.

scholarly journals The influence of powder feed rate on mechanical properties of atmospheric plasma spray (APS) Al-12Si coating

2019 ◽  
Vol 58 (1) ◽  
pp. 75-81
Author(s):  
Mihailo Mrdak ◽  
Bojan Medjo ◽  
Darko Veljić ◽  
Miodrag Arsić ◽  
Marko Rakin
Keyword(s):  
Mechanical Properties ◽  
Plasma Spray ◽  
Spray Coating ◽  
Fracture Morphology ◽  
Optical Microscope ◽  
Atmospheric Plasma Spray ◽  
Atmospheric Plasma ◽  
Powder Feed ◽  
Feed Control ◽  
Powder Particles

Abstract In this paper, structural and mechanical properties of APS - atmospheric plasma spray coating Al-12Si are presented. The aim of the research was the optimisation of the flow of powder to produce layers with optimal mechanical and structural properties that will be applied to the worn out parts of airplanes. Three groups of samples were produced, by utilising three powder feed rates: 30 g/min, 45 g/min and 60 g/min. Evaluation of layers’ microhardness was done using HV0.3 method and the bond strengthwas determined by testing of tensile strength. Surface morphology of the deposited powder particles was examined on SEM (Scanning Electron Microscope). The microstructure of the coating with the best measured mechanical properties was subsequently examined in etched condition on optical microscope and SEM (in accordance with the standard PN 585005, Pratt & Whitney). Also, fracture morphology of this coating in deposited state was examined using SEM. It was found that powder feed control with atmospheric plasma spraying can produce dense layers of Al-12Si coating with good bond strength.

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