KPI-ML based integration of industrial information systems

M. H. Tahir, Mehdi Mahmoodpour, A. Lobov
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引用次数: 1

Abstract

In order to stay competitive in the global market, industrial manufacturers are implementing various methods to improve the production processes. This requires measuring important metrics and making use of performance measurement systems. Based on the data generated in manufacturing operations, various indicators can be defined and measured. These indicators serve as the basis for decision-making, control and health monitoring of a manufacturing process. In this paper an approach is presented that makes use of key performance indicators (KPIs). The KPIs used are defined in a standard known as, ISO 22400 Automation systems and integration-Key performance indicators (KPIs) that is usually applied for management of manufacturing operations. The approach uses the database of a production line to define KPIs and generates a tool for visualizing them. The KPIs are defined using a data model of Key Performance Indicator Markup Language (KPI-ML), which is an XML utilization of the ISO 22400 standard. The recommended approach paves a way for constructing generic KPI-ML visualization tools serving various industries to assess their performance with the same tool.
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基于KPI-ML的工业信息系统集成
为了在全球市场上保持竞争力,工业制造商正在实施各种方法来改进生产过程。这需要衡量重要的指标,并利用绩效衡量系统。根据制造操作中产生的数据,可以定义和测量各种指标。这些指标是生产过程决策、控制和健康监测的基础。本文提出了一种利用关键绩效指标(kpi)的方法。所使用的kpi在ISO 22400自动化系统和集成-关键绩效指标(kpi)标准中定义,该标准通常应用于制造业务的管理。该方法使用生产线的数据库来定义kpi,并生成用于可视化它们的工具。kpi是使用关键性能指标标记语言(KPI-ML)的数据模型定义的,它是ISO 22400标准的XML利用。推荐的方法为构建服务于不同行业的通用KPI-ML可视化工具铺平了道路,以便使用相同的工具评估它们的性能。
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