Modeling of plasma spray coating process using statistical regression analysis

Modeling of Plasma Spray Coating Process Using Robust Solutions Based on New Intelligence Methods

“…(Datta et al, 2013). Operational data from the plasma spraying process included four input process variables (primary gas flow rate (G), stand-off distance (D), powder flow rate (P), and arc current (A)) and three output process variables (thickness (Th), porosity (Pr), and microhardness (H) of the coatings).…”

“…The nickel-based alloy metal powder and cermet materials deposition were intensive to conditions of processing. Datta et al (Datta et al, 2013) designed an examination by using central composite design (CCD) method and analyzed the experiment with regular regression analysis. The collected data such as primary gas flow rate, stand-off distance, powder flow rate and arc current conducted as input parameters under nonlinear regression analysis and three outputs namely thickness, porosity and micro-hardness of coating Parametric properties such as carrier gas flow rate, plasma power and etc.…”

Review of Multiresponse Process Optimisation Methods

“…RSM has been used in diverse applications for solving multiresponse optimisation problems, such as optimisation of numerical control machine (Berni and Gonnelli 2006), optimisation of various machining processes (Aggarwal and Singh 2005), modelling and analysis of laser drilling processes (Kuar et al 2006;Ghoreishi et al 2006), optimisation of laser shock peening process to improve performances of micro-electro-mechanical system (MEMS) (Zhu et al 2012), optimisation of laser welding of stainless steels (Khan et al 2012), predictive modelling and optimisation of Nd:YAG laser micro-turning of ceramics (Kibria et al 2013), optimisation of wire electric discharge machining (WEDM) in processing high strength low-alloy steel (HSLA) (Sharma et al 2013), optimisation of WEDM in processing a pure titanium , modelling of plasma spray coating process (Datta et al 2013), optimisation of selective laser sintering process used to produce PA12/MWCNT nanocomposite (Paggi et al 2013), and others (Tsui et al 2004;Kovach et al 2008;Timothy et al 2004;Robinson et al 2004).…”

Estimating the behavior of particles sprayed by a single-cathode plasma torch based on a nonlinear autoregressive exogenous model

“…However, one does not have such a basic model to represent the system; it must be inferred from experiments performed on the same system. Practically speaking, one builds a mathematical model at first, quantifies the model with experimental data at second and finally, some necessary changes should be carried out before the model validation [10][11][12]. Such a process is usually called system identification [13].…”