2409-1634Research result. Economic Research2409-163410.18413/2409-1634-2019-5-2-0-11717MAIN FEATURECroston's method in the modification of Syntetos and Boylan for forecasting inventoriesCroston's method in the modification of Syntetos and Boylan for forecasting inventoriesMelnikovaOlga AleksandrovnaMelnikovaOlga Aleksandrovnanewfarmacia@mail.ru20195200

This paper discusses the problem of forecasting the demand for spare parts for medical equipment using the original Croston method in the modification of Sintetos and Boylan. Forecasting in inventory management for products for which demand is unstable is the main problem, both in the production and in the search for spare parts for equipment under operating conditions. Croston's method is not fully reliable, due to the restrictions imposed. In this regard, forecasting methods associated with its modification are of particular relevance. In the present work, a modification of Sintetos and Boylan is considered with reference to forecasting the demand for spare parts for medical equipment. In contrast to the original method, a modified formula is used in the work, in which the interval between the cases of replacement of parts is excluded, and the smoothing parameter is used, and therefore the formula acquires the greatest accuracy. The presented formula was tested as a result of using experimental data. In conclusion, the obtained data is compared with the data obtained by the usual Croston method.

This paper discusses the problem of forecasting the demand for spare parts for medical equipment using the original Croston method in the modification of Sintetos and Boylan. Forecasting in inventory management for products for which demand is unstable is the main problem, both in the production and in the search for spare parts for equipment under operating conditions. Croston's method is not fully reliable, due to the restrictions imposed. In this regard, forecasting methods associated with its modification are of particular relevance. In the present work, a modification of Sintetos and Boylan is considered with reference to forecasting the demand for spare parts for medical equipment. In contrast to the original method, a modified formula is used in the work, in which the interval between the cases of replacement of parts is excluded, and the smoothing parameter is used, and therefore the formula acquires the greatest accuracy. The presented formula was tested as a result of using experimental data. In conclusion, the obtained data is compared with the data obtained by the usual Croston method.

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