Selection the Suitable Model for Forecasting MF399 tractor failure rate for different maintenance policy

Today, mechanized farming systems, on time performance of operations requires correct machine programming. For proper planning, it is necessary to know the exact downtime of machines. In this regard, the study was conducted to accurate predicting of MF399 tractor failure rate for the both of corrective and preventive maintenance policies in Khuzestan province. For this purpose, Models applied to forecast are Exponential and ARIMA. Results of Durbin-Watson tests, failure rate of corrective and preventive maintenance policies series were found non stochastic and predictable. Based on the lowest forecasting error criterion, ARIMA is the best model for forecast failure rate of CM and PM policies series. Hence, using the forecast method can affect on different policy about failure rate via forecasting the fluctuation variables. According to results of failure rate forecasting, it was found that there is not significant difference between statistical descriptive measures of forecasting and actual tractor failure rate that it represents high accuracy of forecasting via ARIMA model.