Journal of Agronomy Research

Journal of Agronomy Research

Current Issue Volume No: 4 Issue No: 2

Research-article Article Open Access
  • Available online freely Peer Reviewed
  • Effect Of Hours Of Use And Age In Years In Estimating Repair And Maintenance Costs For Two Sizes Of Agricultural Tractors In Northern Sudan

    1 Faculty of Agricultural, University of Khartoum, Sudan 

    2 Departments of Agricultural Engineering, Colleges of Agricultural Studies, Sudan University of Science and Technology 

    Abstract

    Repair and maintenance cost is considered as one of important items for machinery management and selection. The present study was carried out in Dongola area for tractor repair and maintenance costs estimation. The data was collected from records of Elshimalya Company for Agricultural Inputs. Forty four tractors rep resenting two sizes of tractors, 75hp and 150hp used in the area were selected for this study. Based on the data collected, regression correlation analysis was carried out and mathematical models were derived to predict the accumulated repair and maintenance (R and M) costs as percent of purchase price in relation to accumulated hours of use and age (years) for each tractor size, and also for the two sizes collectively. Five model forms (linear, logarithmic, polynomial, power and exponential) were derived and the power function was found the best fit to explain the relation. The accumulated Rand M costs as percent of purchase price (Y) was increased as the accumulated hours of use (x) and age (g) of the tractor in years were increased. A high correlation was found between the accumulated R and M cost and both accumulated hours of use and tractor age in years (Average R2 = 0.93).

    It was concluded that the power function was the best fit for repair and maintenance cost estimations and the following relations may be used as an average for estimation of the accumulated R and M costs as percent of purchase price (Y) with accumulated hours of use (x) and age (g) of the tractor: Y=0.028x0.662 (mean) Y=12.294g1.276 (mean).

    Author Contributions
    Received Jun 18, 2021     Accepted Oct 13, 2021     Published Oct 16, 2021

    Copyright© 2021 Hassan Dahab Mohamed, et al.
    License
    Creative Commons License   This work is licensed under a Creative Commons Attribution 4.0 International License. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

    Competing interests

    The authors have declared that no competing interests exist.

    Funding Interests:

    Citation:

    Hassan Dahab Mohamed, N. O. Kheiry Abdalla, Ahmed Gafar Elfaki Montasir (2021) Effect Of Hours Of Use And Age In Years In Estimating Repair And Maintenance Costs For Two Sizes Of Agricultural Tractors In Northern Sudan Journal of Agronomy Research. - 4(2):1-11
    DOI 10.14302/issn.2639-3166.jar-21-3875

    Introduction

    Introduction

    Agricultural tractor is one of the most important energy and power sources in agricultural mechanization1. It requires high initial capital investment. The introduction of modern technology during the last century resulted in rapid growth of farm production. Tractors and farm machinery are important samples of this modern technology2. Tractor costs have great influence on farm business profit. Knowledge of tractor costs for farm operations has a prime importance in making management plans and decisions especially in comparing different tractor types and models thereby assisting in the selection of a more appropriate farm tractor. Costs of owning and operating farm machinery represent 35% to 50% of the costs of agricultural production when the land is excluded3. The repair and maintenance (R&M) cost is an important item in the costs of ownership and operation. R&M cost is a function of machine age and use4. In general, the costs other than those for R&M usually decrease with increasing usage, but the reverse is true with respect to R&M costs. The cost of R&M is usually about 10% of the total cost; as the machine age increases the cost increases until it becomes the largest cost item of owning and operating the farm machines5. Agricultural engineers have carried many studies regarding R&M of farm machines. Several studies were conducted in both developed and developing countries either to develop models to determine the cost during a certain period or to get absolute numbers to represent owning and operating certain equipment 6789. Using of American and European mathematical relations to estimate R and M costs in under developed and developing countries produced unrealistic and misleading results and therefore, these countries developed their own mathematical models101112. Poor and irregular maintenance reduce tractor reliability, increases fuel consumption, deceases engine power and life and increases exhaust emission13.

    In Sudan, agricultural tractors introduced in early nineteen-nineties and there are many tractor makes, models and sizes now distributed between irrigated and rain-fed agricultural farms. These tractors are owned by people from both the private and public sectors and even some are owned by individual farmers and they often work for more than 1200 hours per year14. Tractors have been used in Sudan, as a power source in agriculture for many years. The total number of tractors officially imported into the country between 1984 and 1994 increased from 23,590 units to 32,096 units (FAO, 1995)14. In Sudan, machinery repair, maintenance, and fuel and lubricants consumption is not given enough attention. About 40% of farm machinery was out of work very quickly due to lack of proper maintenance and un availability of genuine spare parts or using of spurious and non-genuine spare parts of low prices. There are some prediction models for tractors repair and maintenance costs in the Sudan were developed 151617. They decided that the correlation between repair and maintenance costs as a percent of tractor initial purchase price and the tractor accumulated hours of use would be best described by a power function equation. There were variations between these models in the predictions for the different tractors. They were varied in structural components due to differences in tractors specifications and conditions and locations of work, therefore, the present study was carried to develop computer models for repair and maintenance costs estimation in relation to hours of use and age for two sizes of diesel engine agricultural tractors in Dongla area.

    Materials And Methods

    Materials and Methods

    Results

    Results and Discussion Tractor Systems Failures and Repair and Maintenance Distribution

    It was observed the average repair and maintenance costs of different systems for the two tractor size generally increased with age, but the rate of increase varies for the two sizes. However, the mean R&M cost of the two tractor types showed relatively higher repair and maintenance costs occurred from year 2 and decreased in year 3 after that increased at years 4 and 5 (Table 2a and Figure 2). The engine and fuel systems accounted for more than 53% of the total accumulated R & M costs of the two tractor sizes when five years ownership was considered (Figure 1). The distribution of the accumulated R & M cost of different tractor systems was almost similar for the two types, but the hydraulic system R & M cost of type (150hp) was higher compared with the 75hp type.

    Distributions of accumulated repair and maintenance of agric tractor systems (a) 75hp tractor type (b) 150hp tractor type (c) mean of the two types Distribution of repair and maintenance costs of agricultural tractor systems (a) 75 hp tractor (b) 150hp tractor (c) mean of two types Repair and Maintenance costs distribution for different tractor systems (A)150 hp tractor
    Age Engine Transmission Hydraulic Fuel Other
    1 66353 83532 49778 114960 19120
    2 109415 139647 83185 834564 38220
    3 138072 165570 102735 111855 44140
    4 165140 218095 120365 81675 34845
    5 204415 250514 154290 75000 57175
    Mean 136679 171471.6 102070.6 243610.8 38700
    Repair and Maintenance costs distribution for different tractor systems (B)75 hp tractor
    1 39820 45465 34275 59706 17055
    2 5465 64270 45710 46320 14983
    3 78908 94745 53925 34270 18340
    4 81825 100677 53890 25098 25636
    5 75361 86410 48060 13755 17590
    Mean 56275.8 78313.4 47172 35829.8 18720.8
    Development of Repair and Maintenance Costs Prediction Models

    Regression analysis of the data was carried out to present the relation between the mean accumulated R&M cost as percent of purchase price and the mean accumulated hours of use of the two tractor types, on the models of linear, polynomial, logarithmic, power and exponential with correlation coefficient (Table 2). The value of correlation coefficient among the presented models was related to polynomial model with R2 = 0.86 and the highest value of correlation was for power model with R2 = 0.93 which is very close to the previous studies. In the most published studies in this field, power models were found easy in calculations and gave better cost predictions than the other models. Therefore, the small difference between the correlation coefficients of polynomial and power models and using of power model by other researchers, in the present study, power model was suggested as suitable form for repair and maintenance cost estimation. The power relations of accumulated R and M costs with accumulated hours of use and tractor age in years of study for the two tractor type and the average of the two types are given in Table 3 and Table 4, The average correlation coefficient was very high (R2 = 0.93) indicating that the tractor age and accumulated hours of use could adequately explain variations in R&M costs.

    Regression analysis of the relation between the mean accumulated R&M cost as percent of purchase price and mean accumulated hours of use
    Model Equation R square
    Linear Y= 0.0003x+22.181 0.732
    Logarithmic Y=23.598Ln (x)- 209.025 0.862
    Polynomial Y=-E-091.568x2+0.001x+7.04 0.859
    Exponential Y=20.017e7.467E-6x 0.617
    Power Y=0.028x0.662 0.927
    The power relation of accumulated R&M cost with accumulated hours of use of the two tractors
    Tractor type Power model R square F
    Tractor 75Hp Y= 0.011x0.763 0.994 501.813**
    Tractor 150Hp Y= 0.019x0.677 0.994 466.297**
    Mean Y=0.028x0.662 0.927 101.534**

    Figure 3, Figure 4, Figure 5 were predicted low accumulated R & M costs of the early stage tractor life, and then costs increased gradually with increasing age and accumulated hours of use in 75hp tractor type. The distribution of the accumulated repair and maintenance cost of different tractor system was increased gradually from fuel, transmission, engine hydraulic and other.

    Accumulated repair and maintenance costs as percent of purchase price as affected by hours of use and age (year) for the75Hp tractor Accumulated repair and maintenance costs as percent of purchase price as affected by hours of use and age (year) for the150 Hp tractor. Comparison of the present study prediction models with other models in world Comparison of the present study prediction models with other models in Sudan
    Comparison of the Present Study Prediction Models with Other Models in the World

    The model of the average accumulated repair and maintenance costs predicted in this study was compared to the other similar models from USA, UK, and Ireland as shown in Table 5. It was clear that the present derived model accounted for relatively lower values of accumulated repair and maintenance costs compared to the world mentioned models. These variations may be attributed to the differences in spare parts prices between Sudan and the industrial countries, or may be due to variations in soil type, climate, preventive maintenance programmer applied and operation conditions. This lower value of repair and maintenance costs may be also due to the procurement and usage of spurious and non-genuine spare parts, variations in tractors technical specifications and lower labor charges for repairing and maintaining tractors in Sudan compared to the industrial world countries.

    The power relation of accumulated R&M cost with accumulated age (years) of the two tractors  
    Tractor type Power model R square F
    Tractor 75Hp Y= 14.14x1.14 0.994 465.008**
    Tractor 150Hp Y= 10.689x1.412 0.944 50.601**
    Mean Y=12.294x1.276 0.952 158.781**
    Comparison of the Present Predictions Model with Other Models Developed in Sudan

    When the predicted model in this study is compared to the other models from Sudan as shown in Table 6 it was observed that this model accounted for lower (1999) for all levels of accumulated hours of use, but after 2010 accumulated hours of use the rate of increase in accumulated repair and maintenance costs was gradual in this study while was very sharp16 model. This may be attributed to differences in spare parts, oils and lubricants prices within the country also may be due to variations in repair rates, frequent breakdowns, labor charges for repairing and maintaining tractors and operators and mechanics skills. Table 7

    Comparison between the present study estimates of repair and maintenance costs as percentage of initial purchase price with other estimates from world
    Source Model Repair and maintenance costs as % of
    initial purchase price
    1000 2000 3000 4000 5000
    Ward et al. (1981) y = (4.82x1.9).10-6 2.4 9 19.5 33.6 51.4
    Morris (1988) UK y = (9.96x1.48).10-5 2.7 7.7 13.9 21.3 29.7
    Khoub (2008) Iran y = (0.002x1.162) 6.1 13.3 22 30.7 39.7
    This study Y=0.028x0.662 2.71 4.29 5.61 6.78 7.87
    A comparison between this study estimates of repair and maintenance costs as percentage of initial purchase price with other estimates from Sudan
    Source Model Repair and maintenance costs as % of initial purchase price
    1000 2000 3000 4000 5000
    Ahmed etal., (1999) y = (2.53x2.4).10-7 4 21.2 56 111.7 190.8
    Dahab&Osama (2002) y = (4.0x1.25).10-4 2.3 5.4 8.9 12.7 16.8
    Awad Omer (2007) y = (2.0x1.59).10-5 1.2 3.5 6.8 10.7 15.2
    Farid Eltom, (2012) y = (1.7x1.29).10-4 1.3 3 5.2 7.5 9
    This study Y=0.028x0.662 2.71 4.29 5.61 6.78 7.87

    When the model of this study was compared to Dahab and Osama (2002)15 model for repair and maintenance costs, it was clear that the estimates of the present model accounted for lower values than15 up to 2011 accumulated hours of use, after which this model accounted for higher values. This may be attributed to variations in tractors specifications, ages and makes.

    The comparison between this model17 prediction showed that the present model accounted for higher values of repair and maintenance costs 17 for all levels. This may be due to conditions of work, operators and mechanics skills, maintenance regime followed and labor charges for repairing and maintaining of tractors. The difference may also be attributed to differences in tractors technical specifications and cost computations methodology, however when the model of this study was compared18, it was clear that the estimates of the present model accounted for larger values until 2025 accumulated hours of use, after which this model accounted for lower value. This may be attributed to variations in tractors specifications, condition of work and skills of mechanics and operators.

    Conclusion

    Conclusions

    The following conclusion may be drawn from the present study

    1. The relationship between accumulated repair and maintenance costs as percentage of the initial purchase price of the tractor and accumulated hours of use and age in years for the two tractors in Dongla area could better be described by the power function equation.

    2. The accumulated repair and maintenance costs increase with tractor age and hours of use.

    3. The predicted models for repair and maintenance costs of tractors in Sudan were lower than those of other countries; therefore, each area or country develops its own models of R&M costs to its operational and field conditions.

    Affiliations:
    Affiliations: