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The Use of Statistical Models to Improve the Management of Production Cycles of Submersible Electrical Equipment for Oil Production

机译：使用统计模型改善石油生产用潜水电设备生产周期的管理

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The paper considers the problems of using statistical models of accidents of electrical oil production complexes with submersible electric motors (ECSEM) to improve the management of production cycles of submersible electrical equipment (SEE). For this, in particular, an analysis of operational physical effects (OPE) is carried out, as the main cause of aging and wear of the ECSEM and its elements and the formation of an information database (ID), which collects information about 8760 accidental failures in oil production enterprises (OPE) of the Volga region for the period 2014÷2018 years, as well as the determination of the probability distributions of failures of SEE according to the ID. These statistical models make it possible to predict the boundary states of typical sets and specific SEE electrical installations and, at a given operating time, determine the prerequisites, the main patterns of occurrence and the mean time to failure of elements and the ECSEM in general. The obtained results were used to substantiate a set of recommendations for improving the efficiency of operation of the ECSEM.
机译：本文考虑了使用带有潜水电动机的电气采油厂事故统计模型（ECSEM）来改善潜水电气设备（SEE）的生产周期管理的问题。为此，尤其要进行操作物理效应（OPE）的分析，这是ECSEM及其元件老化和磨损的主要原因，并形成了一个信息数据库（ID），该数据库收集了有关8760事故的信息。伏尔加河地区2014年至2018年期间石油生产企业（OPE）的故障，以及根据ID确定SEE的故障概率分布。这些统计模型可以预测典型机组和特定SEE电气设备的边界状态，并在给定的运行时间下确定元件和ECSEM的前提条件，主要的发生方式以及平均故障时间。获得的结果用于证实一组建议，以提高ECSEM的运行效率。

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