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

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.

Literature Survey about Elements of Manufacturing Shop Floor Operation Key Performance Indicators

“…A manufacturing industry is composed of a number of operational areas, for instance manufacturing, sales, marketing and many other related functional areas. Based on the operational areas, manufacturing industries can have diverse sets of KPIs [4].…”

“…Centred on the operational area, within the manufacturing industries functional hierarchy model: discrete, continuous or batch control of the manufacturing process is at level 1-2 [4]. Whereas, manufacturing operations management is at level 3 and business planning and logistics is at level 4.…”

Graphical analysis for overall effectiveness management: A graphical method to support operation and maintenance performance assessment

“…In addition, ISO 22400‐1 and ISO 22400‐2 specify an industry‐neutral framework for the definition, composing and use of KPIs for manufacturing operations management (MOM). And at this respect, Kang et al create a hierarchical structure defining relationships between the KPIs for MOM. However, the issue of having a suitable reporting system and the ability to represent the performance of a process by synthetic and graphical indicators has been poorly explored and analyzed.…”

“…The GAOEM method is built from a database related to the production process and concerning 3 types of data or supporting elements, namely, (1) intervention data (number of interventions, class of intervention, stop/no stop), (2) time data (cumulated time, duration of intervention), and (3) production data (cumulated production, cumulated defective products, nominal capacity of the asset). Importantly, the database concerning interventions responds to both maintenance interventions as well as interventions of an operational nature.…”

“…The GAOEM method is built from a database related to the production process and concerning 3 types of data or supporting elements, 28 Through the graphic analysis of these data, GAOEM allows controlling and diagnosing the overall effectiveness of the production equipment, shortening diagnosis and interpretation of historical time data, systematizing the process of identifying potential problems linked to the use of assets and thus increasing the productivity and profitability. Figure 1 summarizes the stages and flow information comprised by GAOEM methodology.…”