The motion and heating of a single particle in a plasma jet is strongly influenced by the feedstock injection conditions and can be predicted using computational modelling as described in the literature. In practice, however, the size and initial velocity of a given particle are essentially random variables within the fairly wide limits of the injected feedstock population. This is compounded by the non-uniformity of the plasma jet. As a result, the motion and heating of particles take on a substantial random element. There are three independent variables that jointly affect the particle motion and heating in a given jet: the diameter, the radial coordinate and the azimuthal angle of a particle. Nevertheless, these parameters cannot be specified for every particle in the jet in a deterministic manner owing to the above complexities and so a simulation based on a single particle cannot provide a realistic prediction of the deposition process. In the present study, the random element present in practical spraying is simulated using a Monte-Carlo approach. The distributions of the motion and heating of a population of particles are simulated rather than those for a single particle. The statistical method presented in this paper gives more detailed information on the effects of processing parameters and the assessment of process quality. The results show that this is able to provide a more accurate means of simulating the thermal spraying process.

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