THE METHOD OF MULTIVARIATE STATISTICAL ANALYSIS OF THE TIME MULTIVARIATE CRITICAL QUALITY ATTRIBUTES OF MANUFACTURE PROCESS WITH THE DATA FACTORIZATION
DOI:
https://doi.org/10.15588/1607-3274-2019-1-16Keywords:
quality-by-design, critical quality attributes, critical process parameters, design of experiment, multivariate statistical analysisAbstract
Context. This paper presents a method for solving the problem of product’s quality assurance at the stage of the initial
manufacture process design in accordance with the process-analytical technology for the design of modern certified manufacturing –
QbD. The method uses the information technologies of multivariate statistical analysis (MSA) to evaluate the influence of time
multivariate critical process parameters (CPPs) on the time product critical quality attributes (CQAs). Preparatory transformation of
clusters of critical process (manufacture process) parameters into factors of product critical quality attributes was carried out.
Objective. To disclose the method of multivariate statistical analysis for assessing the character and features of the influence of time multivariate critical process parameters on time multivariate critical quality attributes at the design stage of the manufacture process.
Method. The method consistently uses: statistical procedures of exploratory multivariate data analysis; transformation the homogeneous observed values matrices of CPPs and product CQAs into data frame (table) with factorized data; construction the regression trees of multivariate CPPs with a multivariate responses (CQAs). The method is implemented the R language packages software.
Results. Factorized time multivariate CPPs make it possible to use methods of multivariate statistical analysis for evaluating the influence of CPPs factors on the time multivariate CQAs.
Conclusions. This method of statistical analysis, together with statistical multivariate canonical analysis, represents an up-to-date information technology for detailed estimation the influence of time multivariate CPPs objects and some CPPs components on CQAs.
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