Estimation of the optimal maintenance frequency of medical devices: A monte carlo simulation approach
This paper aims to implement and validate a Monte Carlo-based algorithm to determine the optimal interval of preventive maintenance of medical devices. The optimization criterion used was that which maximizes the equipment’s achieved availability. The Monte Carlo algorithm was implemented and tested using maintenance data from infusion pumps, electrocardiographs, and ECG monitors from both primary and secondary data source of information. The performance of the algorithm behaved well; it had a 65-sec response time for 10,000 simulations. The accuracy of the calculations did not exceed 1%. In addition to that, the implementation of the Monte Carlo algorithm was able to determine the better availability curve for the interval of preventive maintenance “tuned” with the mean time to failure for each medical devices population type. © Springer Nature Singapore Pte Ltd. 2017.
Bioinformatics ; Biomedical engineering ; Biomedical equipment ; Biophysics ; Frequency estimation ; Intelligent systems ; Maintenance ; Monte Carlo methods ; Optimization ; Achieved availability ; Mean time to failure ; Medical Devices ; Monte carlo algorithms ; Optimal maintenance frequency ; Optimization criteria ; Optmization ; Secondary data sources ; Preventive maintenance ; Biomedical engineering ; Component: Monte Carlo simulation ; Maintenance optmization ; Preventive maintenance frequency ;
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