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Regression Models for Repair and Maintenance Cost of Tractors Used in BARI Farms

M. A. Hossain
Machinery Repair and Maintenance Division, Bangladesh Agricultural Research Institute, Gazipur, Bangladesh.

M. S. Hassan
Machinery Repair and Maintenance Division, Bangladesh Agricultural Research Institute, Gazipur, Bangladesh.

M. D. Hossain
Dept. of Farm Power and Machinery, Bangladesh Agricultural University, Mymensingh, Bangladesh.

Abstract/ Executive Summary:

Multiple and linear regression models were developed to estimate the repair and main cost of MF-240, MF-375, FORD-3910 and KUBOTA-4500DT Tractors used in Ban Agricultural Research Institute during the period of 1991-97. Tractor age has a high positive correlation with repair and maintenance cost whereas the annual use has a very low correlation with repair and maintenance cost. Both multiple and linear regression models were found adequate to describe the repair and maintenance cost of all tractors. Multiple regression were better than linear regression models for MF-240 and KUBOTA-4500DT Tractors whereas linear regression models were better than linear regression models for MF-375 and FORD-3910 Tractors. These models may be used to estimate the repair and maintenance cost of tractors by government and private farms.

Keywords: Regression Models, Repair and Maintenance, Cost, Tractors

Location: Regional Agricultural Research Stations (RARS), Jamalpur, hurdi (Pabna), Jessore and Rahmatpur (Barisal)

Start Date: 00-00-1991

End Date: 00-00-1997

Program Area: Farm Mechanization

Non-commodity: Cost of production

Objectives:

To develop regression models for the repair and maintenance cost tractors used in BARI farms.

Methodology:

A survey was conducted to collect the data for repair and maintenance cost of different models of tractors at BARI, Gazipur and its four Regional Agricultural Research Stations (RARS) located at Jamalpur, hurdi (Pabna), Jessore and Rahmatpur (Barisal). Data of seven years were collected for the period of 1991-97. The selected tor models in this study were MF-240, MF-375, FORD-3910 and KUBOTA-4500DT. Three tractors of the same age were taken under study but for KUBOTA-4500DT, two tractors were selected (due to unavailability) at different locations of BARI farms. The annual operating time was collected from logbook of the individual tractor. The annual repair and maintenance cost of each tor was collected from the BARI repair maintenance history book. The repair maintenance cost was considered for the market price of the year 1997. The statistical analysis were done by using Microsoft Excel 97 package. The modules were evaluated in terms of statistical errors. The value of RMSE (Root Mean Square Error) represents the fitting ability of a model in relation to the number of data points. Smaller the RMSE value, better the fitting ability of a model. MRD (Mean Relative Deviation) is used to describe the goodness of fit of a model. For a good model, all error terms should be minimum.

Source of Information: Journal of the Institution of Engineers; Agricultural Engineering Division, Vol. 26/AE, No. 1, Dec. 1999

Article Link (Online Journal):

Funding Source:

Total Budget (Tk.) :

Achievement/Findings:

In multiple and linear regression models, tractor age has a high positive correlation with repair and maintenance cost whereas the annual use has a very low correlation with repair and maintenance cost. Both multiple and linear regression models are adequate to describe the repair and maintenance cost of all the tractors. Multiple regression models were better than linear regression models for MF-240 and KBOTA-4500DT Tractors whereas linear regression models were better than linear regression models for MF-375 and FORD-3910 Tractors. These models may be used to estimate the repair and maintenance cost of tractors used by government and private farms.

Knowledge Management: Journal