Point and Interval Evaluation of Nanoparticles Censored Sample in Spray Process

Document Type: Research Paper


1 Lahijan Azad University

2 Mechanical Engineering Department, Engineering College, Payame Noor Univerity.


A good nano coating depends on the quality of the collision and spreading behavior of nanoparticles. In many cases, nanoparticle spreading data has not been recorded for some reason. In this paper, we have extended the evaluation model to estimate and predict the unavailable or censored maximum spreading diameter of nanoparticle data. Different point and interval methods have been considered for this problem. In Bayesian evaluation, the Monte Carlo Markov Chain (MCMC) has been proposed as an efficient procedure for estimating the predictive inference for future observation. An important implication of the present study is that the censored maximum diameter data can be predicted well using the proposed methods. The proposed point predictions are close to real data and the predictive intervals contain the real values and it verifies the applicability of the prediction techniques for real problems.