Abstract and keywords
Abstract (English):
The purpose of this work consists in the presentation of the results of the theoretical generalization of the problem in the quality level definition in processes and objects of arbitrary origin with the use of a typological approach as a basis of control in organization systems. In the investigation there were used methods of a system analysis, a mathematical modeling of multi-parametric social objects, methods of a structural anal-ysis and also a methodology of a universal quality management (UQM). Investigation results. A multidimensional information object space of matrices of groups of quality indices is considered, a generalized model of a twodimensional matrix of relations of quality indices parameters in Cartesian coordinates is presented, quality indices are shown and their application for adaptive marketing control is shown, a procedure for the quality assessment of objects with the aid of models of a neuro-network typification is offered, and the expediency of basic directions realization in strategy of quality control regarding the set of objects and processes of an organization system under analysis is also substantiated. As an example there is considered a neuro-network approach at the typification of engineering positions in modern mechanical engineering and procedures on the basis of a competence approach of the identification process of young specialists with available vacant seats. Conclusions. The quality parameters are a com-plex category in control of objects/processes and can be considered as a general methodological approach to the control of different organization systems. At the same time there can be used simulators of quality me-tering and typification, and also clusterization and grouping quality indices with the aid of which it is possible to ensure efficiently enough the realization of the identification procedure of objects/processes on quality indices with the application of neuro-network models.

organization system, quality, control, objects, model, neuronic network, indices, groups
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