Kang Ningxuan, Zhao Cong, Li Jingshan, Horst John A
Department of Industrial Engineering, Tsinghua University, Beijing, China.
Department of Industrial and Systems Engineering, University of Wisconsin, Madison, WI, USA.
Int J Prod Res. 2016;54(21):6333-6350. doi: 10.1080/00207543.2015.1136082. Epub 2016 Feb 1.
Key performance indicators (KPIs) are critical for manufacturing operation management and continuous improvement (CI). In modern manufacturing systems, KPIs are defined as a set of metrics to reflect operation performance, such as efficiency, throughput, availability, from productivity, quality and maintenance perspectives. Through continuous monitoring and measurement of KPIs, meaningful quantification and identification of different aspects of operation activities can be obtained, which enable and direct CI efforts. A set of 34 KPIs has been introduced in ISO 22400. However, the KPIs in a manufacturing system are not independent, and they may have intrinsic mutual relationships. The goal of this paper is to introduce a multi-level structure for identification and analysis of KPIs and their intrinsic relationships in production systems. Specifically, through such a hierarchical structure, we define and layer KPIs into levels of basic KPIs, comprehensive KPIs and their supporting metrics, and use it to investigate the relationships and dependencies between KPIs. Such a study can provide a useful tool for manufacturing engineers and managers to measure and utilize KPIs for CI.
关键绩效指标(KPI)对于制造运营管理和持续改进(CI)至关重要。在现代制造系统中,KPI被定义为一组反映运营绩效的指标,例如从生产率、质量和维护角度来看的效率、产量、可用性等。通过对KPI的持续监测和测量,可以对运营活动的不同方面进行有意义的量化和识别,从而推动和指导持续改进工作。ISO 22400中引入了一组34个KPI。然而,制造系统中的KPI并非相互独立,它们可能存在内在的相互关系。本文的目的是引入一种多层次结构,用于识别和分析生产系统中的KPI及其内在关系。具体而言,通过这样的层次结构,我们将KPI定义并分层为基本KPI、综合KPI及其支持指标,并利用它来研究KPI之间的关系和依赖性。这样的研究可以为制造工程师和管理人员提供一个有用的工具,用于衡量和利用KPI进行持续改进。