Document Type : Research Paper

Abstract

The management of machine replacement (specifically tractors) is one of the most critical factors for performing field operations on time. Therefore, tractor repair and maintenance costs must be accurately predicted. This research was carried out to evaluate the use of the regression technique in predicting tractor repair and maintenance costs. The study was conducted using empirical data on 60 two-wheel drive tractors from Astan Ghods-e Razavi agro-industry. Regression analyses were carried out. The response variable was repair and maintenance cost value and the independent variable was cumulative hours of use. Different second and third-order polynomial models and exponential and power models of age were examined. The results showed that the cubic regression model was the best model for predicting repair, oil and fuel costs based on the coefficient of determination and significance of regression coefficients. The performance cubic regression model performed much better in the test phase for the prediction of repair costs with a mean absolute percentage error of 3.72 in comparison to oil and fuel costs with a mean absolute percentage errors of 5.21 and 9.51, respectively.

Keywords

Almassi, M. and Yaganeh, H. R. 2002. Determining a suitable mathematical model to predict the repair and maintenance costs of farm tractors in Karoon agro-industry Co. IranianJ.Agric.Sci. 33(4): 707-716. (in Farsi)
Almassi, M.Kiani, S. H. and Loveimi, N. 2008. Principles of Agricultural Mechanization. Jangal Press. (in Farsi)
Ashtiani, A. 2005. Determining the optimum mathematical model for prediction of tractors repair and maintenance costs in Sari Dasht-e-Naz Farm Company. Agric. Sci. Tabriz Uni. 15(4):102-112. (in Farsi)
Bowers, W. and Hunt, D. R. 1970. Application of mathematical formula to repair cost data. Trans. ASAE. 13, 806-809.
Fuls, J. 1999. The Correlation of repair and maintenance costs of agricultural machinery with operating hours management policy and operator skills for South Africa. http://www.arc.agric.za
Kim,Y. H. 1989. A forecasting methodology for maintenance cost of long-life equipment. PhD Thesis. University of Alabama.
Lyman, O. and Longnecker, M. 2001. An introduction to statistical methods and data analysis. R R. Donnelley & Sons, Inc./Willard. United States of America. 532-825.
Mitchell, Z. W. 1998. A Statistical Analysis of Construction Equipment Repair Costs Using Field Data & the Cumulative Cost Model. PhD Thesis. Faculty of the Virginia Polytechnic Institute and State University.
Morris, J. 1988. Estimation of Tractor Repair and Maintenance Costs. J. Agric. Eng. Res. 41, 191-200.
Nunnally, S. W. 1993. Construction means and methods. Prentice-Hall. Englewood Cliffs. NJ.
Oskounejad, M. M. 2003. Engineering economic evolution of industrial project. Amirkabir Industrial Univ. Press. (in Farsi)
Rotz, C. A. 1987. A Standard Model for Repair Costs of Agricultural Machinery. Appl. Eng Agric. (1): 3-9.