Electrical Cable Demand Prediction Using ARIMA

Conference proceedings article

Authors/Editors

GANDA BOONSOTHONSATIT

Strategic Research Themes

Other (Strategic Research Themes)

Publication Details

Author list: Tonchiangsai, Kanokwan; Boonsothonsatit, Ganda

Publisher: Elsevier

Publication year: 2021

Start page: 111

End page: 114

Number of pages: 4

ISBN: 9781665435857

ISSN: 0928-4931

eISSN: 1873-0191

URL: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85113761428&doi=10.1109%2fICITM52822.2021.00027&partnerID=40&md5=39015eaa0d838cbe66332a1eb0c1b697

Languages: English-Great Britain (EN-GB)

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Abstract

In era of industry 4.0, manufacturing industry has become in highly competitive environment. This drives all businesses to adapt themselves. One of them is electrical cable manufacturing whose customer demand is uncertain. To deal with it, higher inventory is carried which returns higher cost of inventory carrying. Therefore, this paper aims to predict time-series electrical cable demand using autoregressive integrated moving average (ARIMA). Its accuracy is measured using mean absolute percentage error (MAPE) at less than 20 percent. As the result, inventory carrying cost is reduced which enable lower cost of logistics. © 2021 IEEE.

Keywords

demand prediction, electrical cable