?
Использование усеченного нормального распределения при планировании страховых запасов в промышленности
The study examined the properties of the normal distribution of the values of shipments of stocks of various categories from warehouses of large industrial companies. As a result, it was revealed that the use of the classical normal distribution, in some cases, may give incorrect results, since the values of stock shipments are positive values, the distribution of which cannot cover the area of negative values. The purpose of the study is to assume that for resources of a rare and chaotic nature of consumption, the use of a truncated normal distribution, when planning insurance stocks, will give more correct results, which will be able to reduce losses from downtime of production and logistics infrastructure facilities, as well as increase the profitability of industrial companies. For the purposes of the study, statistics were used on the receipt and shipment of reserves from the warehouses of mining companies engaged in the extraction of coal and iron ore, according to an enlarged nomenclature of operating resources in the amount of about 15 thousand items for the period 2018-2023. The initial data covered spare parts, as well as consumables and auxiliary materials for quarry equipment used in open-pit mining. The main sources of information were the Federal State Statistics Service of the Russian Federation and the reports of mining enterprises published on the Internet and other open sources. The methods of system, economic and financial analysis, reliability theory, as well as mathematical statistics were used in the processing of the initial data. According to the results of the study, it was proved that the estimated need for stocks, when using a truncated normal distribution, turns out to be less than the classical Gaussian distribution, which may be of practical interest in the development of optimization solutions in logistics. The findings can be used for inventory planning, not only in the mining industry, but also in other manufacturing companies, as well as in trade and service organizations