A synergetic approach for assessing and improving equipment performance in offshore industry based on dependability

V. Ebrahimipour, K. Suzuki

Research output: Contribution to journalArticlepeer-review

18 Citations (Scopus)


The objective of this paper is to present a framework for assessing and improving offshore equipment performance based on dependability. The main idea is to employ principle component analysis (PCA) and importance analysis (IA) to provide insight on the equipment performance. The validity of the model is verified and validated by data envelopment analysis (DEA). Furthermore, a non-parametric correlation method, namely, Spearman correlation experiment shows a high level of correlation between the findings of PCA and DEA. The equipment of offshore industries is considered according to OREDA classification. The approach identifies the critical equipment, which could initiate the major hazards in the system. At first PCA is used for assessing the performance of the equipment and ranking them. IA is then performed for the worst equipment which could have most impact on the overall system effectiveness to classify their components based on the component criticality measures (CCM). The analysis of the classified components can ferret out the leading causes and common-cause events to pave a way toward decreasing failure interdependency and magnitude of incidents which ultimately maximize overall operational effectiveness.

Original languageEnglish
Pages (from-to)10-19
Number of pages10
JournalReliability Engineering and System Safety
Issue number1
Publication statusPublished - Jan 1 2006


  • Data envelopment analysis
  • Dependability
  • Effectiveness
  • Maintainability
  • Principle component analysis
  • Reliability

ASJC Scopus subject areas

  • Safety, Risk, Reliability and Quality
  • Industrial and Manufacturing Engineering


Dive into the research topics of 'A synergetic approach for assessing and improving equipment performance in offshore industry based on dependability'. Together they form a unique fingerprint.

Cite this