DocumentCode
2635106
Title
The Forecasting Models for Spare Parts Based on ARMA
Author
Jiafu, Ren ; Zongfang, Zhou ; Fang, Zhang
Author_Institution
Sch. of Manage. & Econ., Univ. of Electron. Sci. & Technol. of China, Chengdu, China
Volume
4
fYear
2009
fDate
March 31 2009-April 2 2009
Firstpage
499
Lastpage
503
Abstract
According to the historical data of timestimes Factory, we use ARIMA time series to model how to predict the demand for spare parts of timestimes Factory. The forecast model test results show that the model can better predict, with high accuracy. On this basis, this article predicts the demand for spare parts of next year.
Keywords
autoregressive moving average processes; demand forecasting; maintenance engineering; time series; ARMA time series; spare part demand forecasting model; timestimes factory; Computer science; Decision making; Demand forecasting; Economic forecasting; Mathematical model; Power generation; Predictive models; Production facilities; Time series analysis; White noise; ARIMA; Demand forecast; Time Series;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Science and Information Engineering, 2009 WRI World Congress on
Conference_Location
Los Angeles, CA
Print_ISBN
978-0-7695-3507-4
Type
conf
DOI
10.1109/CSIE.2009.315
Filename
5171046
Link To Document