B.P. Sadkovsky, N.E. Sadkovskaya, O.V. Knyazev

The objectives of management of the complex radioelectronic industry require specially organized systems to make better use of possibilities of human intelligence in conjunction with powerful information processing principles and techniques of modern mathematics, cybernetics and systems engineering. The effectiveness of management decisions depends on the quality of the set of indicators, including the quality of the information received and the quality of the analysis of this information. The most acute problem is development of software systems that automate human activities in order to increase its effectiveness.Over the past two decades, the concept of engineering production management has evolved from traditional automated MIS class to integrated solutions based on systems of several classes. This system classes are: ERP (Enterprise resource planning), APS (AdvancedPlanning & Scheduling Systems), MES (Manufacturing Execution Systems),SCADA (Supervisory Control And Data Acquisition), PDM/PLM (Product Data Management/Product Lifecycle Management), DSS (Decision Support System), BRMS (Business Rules Management System). Currently used in enterprises radioelectronic industry information systems often have a simplified approach, tools, and methods used in the development and implementation of systems and do not have the desired effect on the formation of managment decisions. This fact has led to the emergence of a new class of systems - decision support systems (DSS). A distinctive feature of these systems is that the results of the decision-making qualitative approach to the decisions taken by man, but by the speed of obtaining solutions is considerably higher than the response time of man (especially in the unpredictable and unforeseen situations.) For quality and reliable form-making under uncertainty should be an analysis of various production data. In this regard, needs tools to make data mining using advanced mathematical techniques. This task served as the emergence of intelligent decision support systems (IDSS). In these systems, in the decision, various methods of intellectual and statistical data analysis. Examples of these methods can serve as regression analysis, genetic algorithms, neural networks. Implementation of IDSS in enterprises radioelectronic industry involves different types. From a practical point of view proved to be a layered approach to the institutional architecture IDSS. The main idea of this approach is to partition the logical structure of the system at various levels. In this case, usually separately allocate integration level, providing interconnection of components. If choice of system architecture is correct, implementation IDSS the company allows to optimize the production processes of decision making.