Selection of condition monitoring techniques using discrete probability distributions: A case study

M C Carnero

Journal of Risk and Reliability, 2009, vol. 223, issue 1, 99-117

Abstract: The setting up of a condition monitoring program is considered a strategic decision owing to its influence on cost, safety, quality, and availability in an industrial plant. However, no previous structured analysis of the selection of condition monitoring techniques and their characteristics has been made, so further analysis is needed. This paper proposes a model for the selection of the most suitable condition monitoring technique to be set up in a subsidiary of a petrochemical plant. For this purpose, different criteria, indicators, and utility functions are defined; nine alternatives are proposed depending on the technological level of the condition monitoring program. The model applies the analytic hierarchy process to obtain a ranking of alternatives. Owing to the special characteristics of the decision, discrete probability distributions are defined. The final ranking is computed by applying the Monte Carlo method considering 2000 simulation trials. Finally, a sensitivity analysis is applied.

Keywords: condition monitoring; analytic hierarchy process; discrete probability distributions; Monte Carlo (search for similar items in EconPapers)
Date: 2009
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://journals.sagepub.com/doi/10.1243/1748006XJRR186 (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:sae:risrel:v:223:y:2009:i:1:p:99-117

DOI: 10.1243/1748006XJRR186

Access Statistics for this article

More articles in Journal of Risk and Reliability
Bibliographic data for series maintained by SAGE Publications ().