A tool for evaluating repairable systems based on Generalized Renewal Processes
- 1. Federal Institute of Education, Science and Technology of Ceará, Crato, CE (Brazil)
- 2. Center for Science and Technology, Federal University of Cariri, Juazeiro do Norte, CE (Brazil)
- 3. Department of Statistics & Informatics, Federal Rural University of Pernambuco, Recife, PE (Brazil)
Description
Highlights: • Review of Weibull-based Generalized Renewal Processes. • Mapping from Weibull-based Generalized Renewal to homogeneous Poisson processes. • Confidence intervals of the parameters of Generalized Renewal Processes. • Hypotheses testing for evaluating and comparing repairable systems. • Study of the usefulness of the proposed approach to simulated and real cases. -- Abstract: Generalized Renewal Processes -GRP- have been in the kernel of modelling repairable systems. Via a virtual age function, they extend classical reliability engineering formalisms, such as renewal and Poisson processes. Via point estimation, GRP practitioners have evaluated intervention crews as well as forecasted the occurrence of undesirable events underlying the system. Assuming an interval estimation perspective, this paper introduces a hypothesis testing framework for GRP. Thus, it makes possible to measure the uncertainty when inferring the stage of the system (e.g. whether stable or deteriorating) and the quality of the interventions. The approach focus on the Weibull-based GRP, notably the main GRP found in the literature. The usefulness of the method is illustrated via real world cases involving offshore, windshield, and transformer facilities. Simulated cases are also studied.
Additional details
Identifiers
- DOI
- 10.1016/j.ress.2018.11.025;
- PII
- S0951832018308391;
Publishing Information
- Journal Title
- Reliability Engineering and System Safety
- Journal Volume
- 183
- Journal Page Range
- p. 281-297
- ISSN
- 0951-8320
- CODEN
- RESSEP
INIS
- Country of Publication
- United Kingdom
- Country of Input or Organization
- International Atomic Energy Agency (IAEA)
- INIS RN
- 55017076
- Subject category
- S42: ENGINEERING;
- Descriptors DEI
- ASYMPTOTIC SOLUTIONS; COMPUTERIZED SIMULATION; MAPPING; MAXIMUM-LIKELIHOOD FIT; TESTING; TRANSFORMERS
- Descriptors DEC
- ELECTRICAL EQUIPMENT; EQUIPMENT; MATHEMATICAL SOLUTIONS; NUMERICAL SOLUTION; SIMULATION
Optional Information
- Copyright
- Copyright (c) 2018 Elsevier Ltd. All rights reserved.