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

• 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 estimation 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.

Ämnesord

TEKNIK OCH TEKNOLOGIER  -- Naturresursteknik -- Mineral- och gruvteknik (hsv//swe)

ENGINEERING AND TECHNOLOGY  -- Environmental Engineering -- Mineral and Mine Engineering (hsv//eng)

NATURVETENSKAP  -- Data- och informationsvetenskap -- Datavetenskap (hsv//swe)

NATURAL SCIENCES  -- Computer and Information Sciences -- Computer Sciences (hsv//eng)

Nyckelord

ARIMA model

Data forecasting

Mining face drilling rig

Drift och underhållsteknik

Operation and Maintenance

Publikations- och innehållstyp

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