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A Hierarchical structure of key performance indicators for operation management and continuous improvement in production systems

Ningxuan Kang, Cong Zhao, Jingshan Li, John A. Horst

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

Abstract

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. © 2016 Informa UK Limited, trading as Taylor & Francis Group.
Original languageEnglish
Pages (from-to)6333-6350
JournalInternational Journal of Production Research
Volume54
Issue number21
DOIs
Publication statusPublished - 1 Nov 2016
Externally publishedYes

Bibliographical note

Publication details (e.g. title, author(s), publication statuses and dates) are captured on an “AS IS” and “AS AVAILABLE” basis at the time of record harvesting from the data source. Suggestions for further amendments or supplementary information can be sent to [email protected].

Funding

This work is supported in part by NIST [grant number 70NANB14H260]; NSF [grant number CMMI-1063656].

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 7 - Affordable and Clean Energy
    SDG 7 Affordable and Clean Energy
  2. SDG 9 - Industry, Innovation, and Infrastructure
    SDG 9 Industry, Innovation, and Infrastructure
  3. SDG 12 - Responsible Consumption and Production
    SDG 12 Responsible Consumption and Production

Research Keywords

  • continuous improvement (CI)
  • dependency
  • ISO 22400
  • key performance indicator (KPI)
  • manufacturing operation management (MOM)
  • production systems
  • relationship

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