Print ISSN: 2394-2762
Online ISSN: 2394-2770
CODEN : JMRABX
Journal of Management Research and Analysis (JMRA) open access, peer-reviewed quarterly journal publishing since 2014 and is published under auspices of the Innovative Education and Scientific Research Foundation (IESRF), aim to uplift researchers, scholars, academicians, and professionals in all academic and scientific disciplines. IESRF is dedicated to the transfer of technology and research by publishing scientific journals, research content, providing professional’s membership, and conducting conferences, seminars, and award programs. With more...Original Article
Author Details :
Volume : 6, Issue : 2, Year : 2019
Article Page : 101-105
https://doi.org/10.18231/j.jmra.2019.019
Abstract
Spare part inventory will be forecasted at higher level if historical demand has spike in few of the months. These few months spiked order lines need to be removed or streamline if it is not genuine for better forecasting. But, in spare part inventory forecasting, number of parts & order lines are very high. It is not practical to remove these order lines one by one. These order lines have been generated mainly due to retro fitment, filed fix, one-time order etc. Means these demands are less probable to generate once again.
In this paper, researcher has shown new method of demand normalization which help to streamline the data instead of removing spiked order lines one by one. New method of demand normalization helps to improve the forecasting.
Researcher has applied new method on spare part inventory data which was received from one of the large automobile company & result of it shown improvement in forecast accuracy. Researcher mainly done the experiment on fast and medium mover parts as per company requirement.
Keywords: Spare part, Forecasting, Standard deviation, Average, Spike etc.
How to cite : Bhosale S V, New developed method of demand normalization improves spare part forecasting. J Manag Res Anal 2019;6(2):101-105
This is an Open Access (OA) journal, and articles are distributed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 License, which allows others to remix, tweak, and build upon the work non-commercially, as long as appropriate credit is given and the new creations are licensed under the identical terms.