The present application relates to
big data analysis technical field, specifically to a kind of mineral
fertilizer production quality control method based on
big data, comprising the following steps: reading
phosphorus ore
diphosphorus pentoxide content and
potassium ore
impurity calcium magnesium content, generating incoming
material quality correlation coefficient set, the numerical values in the incoming
material quality correlation coefficient set are weighted combination mapping, and incoming material comprehensive characteristic parameter matrix is generated.The present application introduces finished product
granulation pulverization rate, acid-base
neutralization consumption determination value into the inversion process of significant dynamic threshold, so that front-end
raw material fluctuation and middle section operation fluctuation can accept the reverse check of end quality boundary, thereby obtaining stronger quality causal through capability, abnormal positioning capability and interception specificity, which can not only compress the
path length of
raw material difference transmission to finished
product defect, but also reduce the misjudgment risk caused by empirical threshold, and can also enhance the identification accuracy of batch fluctuation, working condition drift and quality
instability precursor.