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Автоматизация сбора информации технологических процессов на предприятии

Автоматизация сбора информации технологических процессов на предприятии

Abstract

The article discusses the problems of production management, the key of which is the poor connectivity of control and industrial structures. It is proposed to resolve this problem by introducing an integrated production management system, which consists of three components: production scheduling system, intelligent module of supervisory reports analysis and decision support system. Production scheduling system is designed to form and fill in databases dispatch information in real-time mode; intelligent module converts the database to the knowledge base by analyzing the data based on the Data Mining technology; decision support system uses this knowledge base to inform management about bottlenecks and the options to eliminate them.

В статье рассматриваются проблемы управления производством, ключевой из которых является плохая связанность управляющих и производственных структур. Подобную проблему предлагается решить с помощью внедрения комплексной системы управления производством, которая состоит из трех компонентов: системы диспетчирования производства, интеллектуального модуля анализа диспетчерской информации и системы поддержки принятия решений.

Keywords

ТЕХНОЛОГИЯ DATA MINING,СИСТЕМА ПОДДЕРЖКИ ПРИНЯТИЯ РЕШЕНИЙ (СППР),СИСТЕМА УПРАВЛЕНИЯ ПРОИЗВОДСТВОМ

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    influence
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
gold