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Time Series Forecasting using ARIMA Model A Case Study of Mining Face Drilling Rig

Authors:
Hussan Al-Chalabi
Yamur Al-Douri
Jan Lundberg

Keywords: ARIMA model; Data forecasting; Mining face drilling rig

Abstract:
This study implements an Autoregressive Integrated Moving Average (ARIMA) model to forecast total cost of a face drilling rig used in the Swedish mining industry. The ARIMA model shows different forecasting abilities using different values of ARIMA parameters (p, d, q). However, better estimated for the ARIMA parameters is required for accurate forecasting. Artificial intelligence, such as multi objective genetic algorithm based on the ARIMA model, could provide other possibilities for estimating the parameters. Time series forecasting is widely used for production control, production planning, optimizing industrial processes and economic planning. Therefore, the forecasted total cost data of the face drilling rig can be used for life cycle cost analysis to estimate the optimal replacement time of this rig.

Pages: 1 to 3

Copyright: Copyright (c) IARIA, 2018

Publication date: November 18, 2018

Published in: conference

ISSN: 2308-4499

ISBN: 978-1-61208-677-4

Location: Athens, Greece

Dates: from November 18, 2018 to November 22, 2018