Mehmet MimanEdward A. Pohl2025-10-06200902185393, 179364460218-53931793-644610.1142/S0218539309003289https://www.scopus.com/inward/record.uri?eid=2-s2.0-65249152996&doi=10.1142%2FS0218539309003289&partnerID=40&md5=f496043df54f21e1f45d369e21c26db7https://gcris.yasar.edu.tr/handle/123456789/10332This paper provides an approach for assessing the uncertainty associated with the estimate of the availability of a two-state repairable system. During the design stage it is often necessary to allocate scarce testing resources among various components in an efficient manner. Although there are a variety of importance and uncertainty measures for the reliability of a system there are limited measures for systems availability. This study attempts to fill the gaps on availability importance measures and provide insights for techniques to reduce the variance of a system-level availability estimate efficiently. The variance importance measure is constructed such that it provides a measure of the improvement in the variance of the system level availability estimate through the reduction of the variance of the various component availability estimates. In addition a cost model is developed that trades-off cost and uncertainty. The measure is illustrated for five common system structures. Monte Carlo Simulation is used to illustrate the use of the assessment tools on a specific problem. Observations conclude that results are consistent with reliability importance measures. © 2009 World Scientific Publishing Company. © 2009 Elsevier B.V. All rights reserved.EnglishAvailability, Importance Measure, Uncertainty Assessment, Variance, Assessment Tools, Cost Models, Design Stages, Importance Measure, Monte Carlo Simulations, Reliability Importances, Repairable Systems, Specific Problems, System Availabilities, System Levels, System Structures, Two State, Uncertainty Assessment, Uncertainty Measures, Variance, Large Scale Systems, Monte Carlo Methods, Quality Assurance, Reliability Theory, Systems Engineering, Uncertainty AnalysisAssessment tools, Cost models, Design stages, Importance measure, Monte carlo simulations, Reliability importances, Repairable systems, Specific problems, System availabilities, System levels, System structures, Two state, Uncertainty assessment, Uncertainty measures, Variance, Large scale systems, Monte Carlo methods, Quality assurance, Reliability theory, Systems engineering, Uncertainty analysisArticle