2014
DOI: 10.1002/qre.1650
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Maintenance Strategies and Failure‐Cost Model for Medical Equipment

Abstract: This paper proposes a mathematical maintenance model that analyses the effect of maintenance on the survival probability of medical equipment based on maintenance history and age of the equipment. The proposed model is simulated in Scilab using real data extracted from maintenance history of anaesthesia machine from Draeger. The analysis using survival approach reveals that conducting preventive maintenance on the selected medical equipment had a positive impact on survival of equipment. The model is then used… Show more

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Cited by 11 publications
(4 citation statements)
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“…Using field and usage data, the proposed CBM criteria helps to predict medical equipment deterioration allowing the relaxation of unnecessary PM. Khalaf et al (2015) proposed a mathematical model to analyze the effect of PM and CM on the survival probability of medical equipment. This model is used to analyze maintenance costs and choose the appropriate scenarios for medical maintenance.…”
Section: Pm Optimizationmentioning
confidence: 99%
“…Using field and usage data, the proposed CBM criteria helps to predict medical equipment deterioration allowing the relaxation of unnecessary PM. Khalaf et al (2015) proposed a mathematical model to analyze the effect of PM and CM on the survival probability of medical equipment. This model is used to analyze maintenance costs and choose the appropriate scenarios for medical maintenance.…”
Section: Pm Optimizationmentioning
confidence: 99%
“…Maintenance programs range from the very simple to the quite sophisticated ones. Perhaps, the simplest plan is to adopt a rigid maintenance schedule where predefined activities are carried out at fixed time intervals (Khalaf et al 2015).…”
Section: Previous Researchmentioning
confidence: 99%
“…However, many results were far from ideal (Cullum et al, 2018). Several factors determine the design of maintenance schedule, including the maintenance manager's decision, recommendations from manufacturers, and long-term experience (Khalaf et al, 2015). Expected life of components changes due to system aging, wear and tear (Soh et al, 2012).…”
Section: Introductionmentioning
confidence: 99%