Machinery & Energetics

In paper the developed mathematical dependence for determining the needs of livestock machinery in spare parts with variable factors is considered: the number of identical parts on the same machine; number of identical machines; the law of distribution of the resource of the parts and its parameters; the accuracy of determining the distribution parameters, which includes the size of the statistical sample and the confidence probability; forecasting time, which will provide consumers with a sufficient number of spare parts in order to maintain the equipment in working condition and qualitative performance of all agro-technical operations in accordance with the requirements of the technological process, taking into account the feature of the functional purpose and operation of mechanization and electrification facilities in livestock farms, consisting of ensuring the continuity of biotechnical connection in livestock: operator – machine – animal – environment. The dependence for determining the need for spare parts coefficient, which contains four variables, two of which are the parameters of the form and scale of two-parameter distributions, is given. In order to obtain final solutions and the possibility of interpreting the results obtained in the form of graphical dependencies, the two-parameter distribution of Weibull is reduced to a one-parameter type, consisting of an artificial method of transmitting the parameter of scale through the parameter of the form of distribution, and the flow time of the output – through the average value of the resource. The order of determination of the forecast time and the ratio for the calculation of the bounce function is given with the condition of bringing the two-parameter distributions to one-parameter type. The graphic dependences of the average resource on the scale and form parameters in the Weibull distribution, the scale of the Weibull distribution form to different notations, and the dependence of the coefficients of the two-way verifiers between the form of the Weibull distribution and the sample size with a confidence probability equal to 0.9 are obtained.

animal production, production, technological process, reliability, spare parts, distribution of Weibull, distribution parameters, probability, forecast time, average resource