Hierarchical Equipment Health Index Framework

Chia Yen Lee, Zhao Hong Dong

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)

Abstract

In the semiconductor manufacturing industry the development of single index assessing the equipment health condition is urgent, and thus the dashboard can be used for monitoring thousands of equipment. This paper proposes a novel equipment health index (EHI) framework and a Hotelling T-squared index (HTI) to monitor equipment and support preventive maintenance in real time in the semiconductor manufacturing industry. The EHI framework consists of data preprocessing, statistical process control, analytic hierarchy process, and a comprehensive single index representing the health condition of equipment. It considers different types of the univariate control charts for each status variable identification (SVID), and aggregates the scores corresponding to the control charts throughout the hierarchical structure. The HTI considers the correlation among the selected SVIDs and builds a multivariate index by using Hotelling T-squared statistic. An empirical study of Taiwan's leading semiconductor assembly manufacturer finds that both the EHI and the HTI supported monitoring thousands of pieces of equipment in real time. In practice, firms can rapidly troubleshoot the root causes of failures by the decomposition of EHI.

Original languageEnglish
Article number8747393
Pages (from-to)267-276
Number of pages10
JournalIEEE Transactions on Semiconductor Manufacturing
Volume32
Issue number3
DOIs
Publication statusPublished - 2019 Aug

All Science Journal Classification (ASJC) codes

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Industrial and Manufacturing Engineering
  • Electrical and Electronic Engineering

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