Journal of Engineering Sciences / Журнал інженерних наук
Permanent URI for this collectionhttps://devessuir.sumdu.edu.ua/handle/123456789/34326
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Item Model of parametric reliability of woodworking machine tools(Sumy State University, 2025) Dziuba, L.F.; Pylypchuk, M.I.; Chmyr, O.Y.; Pavliuk, R.V.The article aims to develop a model of the parametric reliability of woodworking machine tools based on the criterion of technological accuracy. For this purpose, a mathematical model of the operating time of a woodworking machine to parametric failure was created using a scheme for changing the size of the workpiece. A linear differential equation characterizing the change in the dimensions for the machined workpiece was obtained based on the assumption of a linear relationship between the wear rate of the machine tool components and its technological accuracy. The differential equation was solved analytically using a Bernoulli approach. As a result, an analytical dependence was obtained for changing the workpiece dimensions. This dependence characterizes the technological accuracy of the machine tool during the overhaul period. The operating time intervals for woodworking machines between parametric failures were also evaluated. The probabilities of failure-free operation were calculated by considering the alpha probability density function for operating time intervals to failure of woodworking machine tools. Finally, it was found that the probability of failure-free operation of machine tools significantly depends on the time-depending parameter, which characterizes the relative durability of the machine tool.Item The distribution pattern of machining errors on woodworking machine tools(Sumy State University, 2023) Pylypchuk, M.I.; Dziuba, L.F.; Mayevskyy, V.O.; Kopynets, Z.P.; Taras, V.I.The article aims to develop a methodology for calculating and predicting the distribution patterns of wood machining errors to assess the operating conditions of the machine tool according to the technological accuracy criterion. It was analytically proven and experimentally confirmed that Weibull’s law accurately describes the distribution pattern of machining errors on woodworking machines. Based on the results of experimental studies of the accuracy of machining on machines for lengthwise sawing and plano-milling of wood, it was found that the primary indicator of the Weibull distribution law is a shape parameter that takes values within 1.89–3.11. The computational algorithm was developed for statistical modeling of the pattern of the distribution of machining errors according to the Weibull distribution law. It allows for determining the main parameters of the error distribution law and evaluating the operating conditions for the machine tool according to the technological accuracy criterion. The statistical modeling results for the distribution pattern of machining errors are correlated with the experimental data with an accuracy of up to 5 %, which confirms the reliability of the obtained simulation results. The developed approach also minimizes the restoration cost for the machine’s operability.