Coordinating and Evaluating of Multiple Key Performance Indicators for Manufacturing Equipment: Case Study of Distillation Column

Li Zhu; Hongye Su; Shan Lu; YueWang; Quanling Zhang

doi:10.1016/j.cjche.2014.05.007

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Coordinating and Evaluating of Multiple Key Performance Indicators for Manufacturing Equipment: Case Study of Distillation Column

PROCESS MONITOR | Updated：2026-01-06

- Coordinating and Evaluating of Multiple Key Performance Indicators for Manufacturing Equipment: Case Study of Distillation Column
- Chinese Journal of Chemical Engineering Vol. 22, Issue 7, Pages: 805-811(2014)
- Affiliations：
  
  State Key Laboratory of Industrial Control Technology, Institute of Cyber-Systems and Control, Zhejiang University,Hangzhou,China,310027
- Author bio：
- Funds：
- DOI：10.1016/j.cjche.2014.05.007
  CLC：
- Published：2014
- Accepted：
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Li Zhu, Hongye Su, Shan Lu, YueWang, Quanling Zhang. Coordinating and Evaluating of Multiple Key Performance Indicators for Manufacturing Equipment: Case Study of Distillation Column[J]. , 2014, 22(7): 805-811.
DOI：

Li Zhu, Hongye Su, Shan Lu, YueWang, Quanling Zhang. Coordinating and Evaluating of Multiple Key Performance Indicators for Manufacturing Equipment: Case Study of Distillation Column[J]. , 2014, 22(7): 805-811. DOI： 10.1016/j.cjche.2014.05.007.

摘要

Abstract

Manufacturing equipment takes the task of operation and directly effects on the manufacturing process. One single Key Performance Indicator (KPI) is mainly employed to evaluate equipment inmost studies

neither integrating the KPIs into a completed evaluation system nor considering the impact and conflict among KPIs. In this paper

a KPI evaluation architecture is presented to define and analyze KPIs

and then a common structure for KPI to obtain the KPI set of manufacturing equipment is introduced. An available multi-KPI coordination model is proposed to discern and balance the relationship amongmulti-KPI. Finally

a case study is introduced to illustrate the applicability of the coordination model by using multi-objective optimization strategy and an efficient solution is obtained.

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