 A condition- and age-based replacement model using delay time modellingT F Lipi, Lim J-H, M J Zuo and W Wang Journal of Risk and Reliability, 2012, vol. 226, issue 2, 221-233 Abstract: To make realistic maintenance decisions, it is important that maintenance managers make their preventive replacement decisions based on observations of the condition of their equipment. This study addresses a condition- and age-based replacement decision problem using the complete history of measured condition observations to minimize long-run average cost, maximize long-run average availability, or both. A stochastic filtering process (SFP) is used to estimate the residual lifetime distribution conditional on the history of observed condition information. A long-run average cost model and a long-run average availability model are analysed in order to determine the theorems necessary for calculating the optimum replacement time. To minimize the cost and maximize availability, a multiobjective decision frontier is proposed that will help maintenance managers deal with trade-offs between the two objectives. Finally, numerical examples are presented for each scenario to show the effectiveness of the methods proposed. Keywords: preventive maintenance; condition information; availability; cost; multiobjective replacement decision; stochastic filtering process (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:sae:risrel:v:226:y:2012:i:2:p:221-233 Access Statistics for this article More articles in Journal of Risk and Reliability |
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