Abstract: In order to avoid the possible distortion of process capability index (C_pk) currently applied to the assessment of tobacco primary processing, a new index model was developed for characterizing the consistency of the process parameters. Taking the massive historical data of circulated hot air temperature in the loosening and conditioning cylinder as a sample, on the basis of the developed model, via introducing maximum range constraint and zero point constraint conditions, an assessment index, QI, for characterizing process parameter consistency was proposed by means of multivariate nonlinear regression analysis and Minitab 16 software. The QI was validated and analyzed with the data of circulated hot air temperature in more than 6 months, the results showed that:1) QI was competent for characterizing process parameters without distortion. 2) QI presented lower distortion probability and misjudgment risk in evaluating a deviative and discrete process. 3) The numerical value resolution of assessment results of QI was higher than that of C_pk.