DATA CLUSTERING OF MANUFACTURE PROCESS MULTIDIMENSIONAL CRITICAL PARAMETERS FOR EVALUATING THE FACTOR'S INFLUENCE ON PRODUCT CRITICAL QUALITY ATTRIBUTES
Journal Title: Телекомунікаційні та інформаційні технології - Year 2018, Vol 123, Issue 2
Abstract
Nowadays, competitiveness and efficiency of companies must be continuously improved to face worldwide competitors therefore the product design process require new methodologies of computer-aided development. This article presents an approach for a model-based planning process for the early phases of manufacturing system planning (MSP). The main goals are a better integration of MSP with product development in the early design phases. The presented approach is based on object-oriented modeling and is supported by a modeling scheme which uses the object-oriented modeling language (R). The article suggests a method of multivariate statistical analysis of the affect of critical process parameters (CPPs) and its factors, on product critical quality attributes (CQAs) with data clustering. It is proposed to transform clusters of critical process parameters into influence factors, which increases the number of degrees of freedom for multivariate statistical research. Method propose the clustering of contingency data array based on multivariate statistical analysis (MSA) for evaluating the influence of critical process parameters factors on the time multivariate product critical quality attributes. Factorized multivariate CPPs increase the possibility to use methods of multivariate statistical analysis for evaluating the influence of CPPs on the multivariate CQAs. The proposed method presents an actual information technology for assessing the affect of time multidimensional data objects and separate components of critical process parameters on product critical quality attributes.
Authors and Affiliations
Oleh Kurchenko, Anton Tereshchenko
Keywords
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