Peculiarities of modeling processes of technical condition change with a component of randomness
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Abstract
Under the current conditions of cargo ships' operation, the problem of maintaining and optimizing the technical condition of ship's technical facilities is of relevance. At the same time, one of the important aspects is to consider random factors that may affect the efficiency and reliability of ships. This becomes especially relevant when it comes to large cargo ships making long voyages, where the probability of accidental damage or failure is high. The present article is devoted to the study of methods for modeling the processes of changes in the technical condition of shipboard technical equipment of cargo ships. The importance of the topic is due to the need to forecast and plan ship maintenance, which includes various components, including engines, hull, propulsion, navigation equipment, power equipment, etc. Analytical and statistical modeling methodologies are considered, and random operational factors acting in the interval between maintenance of ship's technical means are considered. The article determines that the tasks of modeling the processes of technical condition change include the analysis of the rate of change of technical condition, which reflects the dynamics of changes in the technical condition of cargo ship equipment and is an important indicator for planning and conducting maintenance. The article provides a comparative analysis of analytical and statistical modeling methodologies used to detail the patterns of technical condition variability, form models of regularities of evolution and accumulation of damage. The influence of random operational factors on the processes of technical condition change between maintenance of ship's technical means is investigated. It was found that random operational factors can cover various sea conditions, loads, weather conditions and other factors that affect the condition of the ship and its equipment between scheduled maintenance. The results of the study can be used to optimize the maintenance schedule based on the actual condition of the ship's equipment.
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