Logistics forecasting models requirements consumers railway

Abstract

The purpose. Is to identify sources of uncertainty when making logistics decisions in the management of material resources PPRT and the development of a methodology for determining the needs in terms of the uncertainties inherent in the transport and industrial production in market conditions. Methods. The proposed model includes two main stages: the stage of formation of the basic data needed to implement the process of forecasting of the consumption of a new and promising product; a step of calculation of the mentioned norms of expenditure of material resources. The Results. In the logistics material management system PST the main sources of uncertainty that arise when making planning decisions, are: the variability or complex with certainty the production program and the lack of norms of consumption of material resources on promising innovative product or to conduct different kinds of work. Methods of pattern recognition is most appropriate to use to solve those problems, the basis of perfection of which is the formation and the search for homogeneous aggregates. In most major PPRT tasks include the definition of norms of expenses of material resources into new and promising products, repair and reconstruction of buildings and facilities of railway transport. The implementation developed by the author of the logistic prediction model, based on the method of optimal classification, showed the promise of named areas of improvement planning in materials management PPRT. In General, the economic calculations have confirmed the correctness of the chosen logistic areas for improvement planning in materials management PPRT and relatively high economic efficiency of the proposed algorithms. Scientific novelty. A comprehensive approach to improving the planning system needs PPRT material resources on the basis of use of methods of mathematical statistics. Identified and analyzed the sources of uncertainty when making logistics decisions in the management of material resources PPRT. Developed the original model of forecasting of the consumption of material resources PPRT on new and upcoming products based on the methods of pattern recognition. The practical significance. The main results can be used to improve logistics system planning in the management of material resources PPRT.