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Intelligent Information Support for Decision Making in Maintenance and Equipment Repair Management

机译:智能信息支持维护和设备维修管理的决策

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The concept of organization of intellectual information support for decision-making, including primary processing of data on failures and symptoms, is discussed. Determination of probabilities and verification of the most probable symptom with recalculation of values of all posterior probabilities is considered in this article. The formalization of knowledge and formation of production system rules in the form of recommendations are shown. Also authors discuss organizing decision-making information support using symptom-based failure detection technology. As well as classification of equipment and components based on key factors in order to identify the most “in-demand” components and components taking into account coefficients associated with class at planning purchases in order to ensure timely supply of components are discussed. The solution is made using Bayes method based on statistical information on relationship of signs with states and on frequency of manifestation of these states. In the process of knowledge formalization, authors proposed to use production system rules in procurement planning, classification of components/nodes using neuro-fuzzy systems, forecasting and optimization methods. New knowledge obtained in the process of data analysis allows expanding the information base. Practical realization is performed using analytical MATLAB platform and EXSYS Corvid developed in USATU.
机译:讨论了对决策的智力信息支持组织的概念,包括对失败和症状的数据的主要处理。在本文中考虑了重新计算所有后概率的最可能症状的概率和验证。显示了以建议的形式形式的知识和制作制度规则的形式化。作者还讨论了使用基于症状的故障检测技术组织决策信息支持。以及基于关键因素的设备和组件的分类,以便在规划购买时识别与课程相关的最“需求”的组件和组件,以便讨论及时提供部件。通过基于符号与状态的关系的统计信息和这些状态的频率的统计信息,使用贝叶斯方法进行解决方案。在知识规则化过程中,提出的作者提出使用生产系统规则在采购规划中,使用神经模糊系统,预测和优化方法分类组件/节点。数据分析过程中获得的新知识允许扩展信息库。使用Usatu开发的分析Matlab平台和Exsys Corvid进行实际实现。

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