Study on the Prediction Model of Paper Printability

Abstract

Paper printability is an essential property affecting printing technology and quality. In this research, a predictive model for paper comprehensive printability is presented based on a simple analytic expression. Five properties of two-sided offset paper are tested with smoothness(k1), whiteness(k2), glossiness(k3), ink absorption(k4) and surface strength(k5). Weights for the properties are calculated by principal components regression (PCR) with software SPSS. Then the expression M(k1 , k2 , k3 , k4 , k5) between paper properties and printability synthetic value is obtained. In the same way, weights for the printing quality performances including density(l1), hue error(l2), gray scale(l3) and saturation(l4) are calculated by PCR and the expression N(l1 , l2 , l3 , l4) between printing quality performances and synthetic value is got. Then the fitted curve Y(x) (x is paper printability synthetic value; Y is printing quality synthetic value) is derived and x is replaced by expression M(k1 , k2 , k3 , k4 , k5). As a result the predictive model for two-sided offset paper comprehensive printability can be developed by the paper properties tested. It is shown that the predictive model can provide a practical and quantitative method for evaluating the comprehensive printability of two-sided offset paper fast and can meet the industry analysis requirements with good precision.