THE PREDICTION MODEL OF ELECTROMOTION SPARE PARTS DEMANDS

1 KAČMÁRY Peter
Co-authors:
1 FUTEJ Martin 1 PLEŠKOVÁ Petra 1 PAŠKA Martin 1 FARKAŠ Csaba 1 STRAKA Martin
Institution:
1 Technical University of Košice, Faculty BERG, Institute of Logistics, Letná 9, 04001 Košice, Slovakia, EU, peter.kacmary@tuke.sk, martin.futej@student.tuke.sk, pleskova.petra@gmail.com, mpaska@centrum.sk, csbfrks92@gmail.com, martin.straka@tuke.sk
Conference:
CLC 2018 - Carpathian Logistics Congress, Wellness Hotel Step, Prague, Czech Republic, EU, December 3 - 5, 2018
Proceedings:
Proceedings CLC 2018 - Carpathian Logistics Congress
Pages:
521-526
ISBN:
978-80-87294-88-8
ISSN:
2694-9318
Published:
18th April 2019
Proceedings of the conference were published in Web of Science.
Metrics:
400 views / 125 downloads
Abstract

This paper describes the design of a simple model and its practical application to predict the need for a spare part. Such a proposed model can be a part of the purchase planning of spare parts within the company's logistics system. The described model was designed for a small enterprise performing service and distributing spare parts. That is why the material flow of spare parts is dominant element in terms of logistics costs in this enterprise. Its management is therefore important for cost optimization, customer satisfaction and market sustainability in a competitive environment. The paper, in its introductory part, provides an overview of similar practical solutions within the research of this topic, but many models are designed to be applied in a global market environment and predict the amount of spare parts needed in different industries. However, these models are difficult to use for the needs of this small enterprise, as the main problem lies in the time of a spare part need rather than its quantity. If there is a need for a specific spare part, which costs several hundred or thousands of euros, but the consumption is only a few pieces per year or more than a year, the time prediction of required spare parts is therefore crucial.

Keywords: Spare parts, prediction, model, forecast methods

© This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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