Abstract
Modern industrial technologies call for the development of novel materials with improved surface properties, lower costs and environmentally suitable processes. Plasma spray coating process has become a subject of intense research which attempts to create functional layers on the surface is obviously the most economical way to provide high per- formance to machinery and industrial equipments. The present work aims at developing and studying the industrial wastes (Flay-ash, Quartz and illmenite composite mixture) as the coating material, which is to be deposited on Mild Steel and Copper substrates. To study and evaluate Coating deposition efficiency, artificial neural network analysis (ANN) technique is used. By this quality control technique, it is sufficient to describe approximation complex of in- ter-relationships of operating parameters in atmospheric plasma spray process. ANN technique helps in saving time and resources for experimental trials. The aim of this work is to outline a procedure for selecting an appropriate input vec- tors in ANN coating efficiency models, based on statistical pre-processing of the experimental data set. This methodology can provide deep understanding of various co-relationships across multiple scales of length and time, which could be essential for improvement of product and process performance. The deposition efficiency of coatings has a strong dependence on input power level, particle size of the feed material, powder feed rate and torch to substrate distance. ANN experimental results indicate that the projection network has good generalization capability to optimize the deposition efficiency, when an appropriate size of training set and network is utilized.
Highlights
The role of surface coatings has become increasingly demand for various engineering applications in industries because requirement of high efficiency and longer service life of the equipment [1,2,3,4]
The deposition efficiency of coatings has a strong dependence on input power level, particle size of the feed material, powder feed rate and torch to substrate distance
Thermal spraying holds a unique position in the spectra of surface modification technologies because it can provide thick coatings over 100 μm over a large area at a very high application rate compared with other coating processes such as PVD, CVD and electroplating [5,6].The conventional plasmaspraying process is commonly referred to as air or atmospheric plasma spraying (APS)
Summary
The role of surface coatings has become increasingly demand for various engineering applications in industries because requirement of high efficiency and longer service life of the equipment [1,2,3,4]. Thermal spraying holds a unique position in the spectra of surface modification technologies because it can provide thick coatings over 100 μm over a large area at a very high application rate compared with other coating processes such as PVD, CVD and electroplating [5,6].The conventional plasmaspraying process is commonly referred to as air or atmospheric plasma spraying (APS). In this APS technology, the coating materials used with well-defined melting point ranging from metallic and ceramic materials to polymeric material [7].
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