Abstract:
Machinery management is a complex process that deals with optimization of mechanized operations for agricultural production in a dynamic and in uncertain weather conditions. The complexity arise from high investment and operating costs, presence of diversified and intensified cropping pattern and timeliness factor.
At the start of each season the agricultural manager is confronted with the questions of : (1) what is the optimum machinery seasonal scheduling plan to follow under the prevailing constraint of limited resources (strategic plan). (2) How to operate and implement the seasonal plan in order to physically achieve the maximum profit with resilient machinery. Thus , this study was directed to develop a sound analytical user- friendly computer model to aid decision – makers to prepare their machinery strategic plan.
To achieve these objectives the developed algorithm consists of submodels that combine in overall unified expert model. It starts by initialized set of input data to construct machinery scheduling program and bar–chart. A submodel was developed to estimate all elements of machinery costs.
For the purpose of evaluating the program financial and technical factors were determined. Then, linear programming and Pert techniques were employed to improve the utilization of material, money and man resources. Consequently, the scheduling program was revised, updated and revaluated after determing the cost elements.
For the purpose of model verification, validation and application input data was collected from primary and secondary sources using various sampling technique from Rahad irrigation Scheme and Wad Salman Agricultural Project ( Sinar Estate ) for the last five years .
The model was verified by comparing its outputs with Rahad existing machinery scheduling program for two, three and four course rotation. The model succeeded in reducing the peak number of required tractors in July by 30, 29 and 16 % for two, three and four course rotation respectively. Comparison of the model output with performance of Rahad four course rotation by an overall index that capture peak number of tractors, cost of operations, execution time and machine utilization indicated a significant difference between the simulated results and the current status in Rahad Scheme.
Comparing actual with prediction was tested by comparing the output with existing scheduling program of Rahad Scheme with respect to satisfaction of the purpose of model building to minimize wastage of resources and a better utilization of resources during program implementation.
Application of the optimization models resulted in reducing the demand for total number of tractors and costs of operations to execute the program. During implementation phase financial (NPV, B/C and IRR), material and money (Labor, Power utilization and distribution and their maximum number at critical period) were evaluated. Analysis of the financial indicators showed a positive status for the running Rahad scheduling program. Technical indicators reflected the increase in labor demand by the increase in crop intensity while power utilization per area and maximum number of tractors were inversely related to crop intensity. The power distribution efficiency was improved slightly by optimization technique for the various crop rotations.
Examination of resource utilization during implementation by Pert technique in order to coordinate program execution, time planning and taking corrective action indicated that : disc harrowing is the most critical activity. Using the Pert technique resulted in saving of time for all crop rotation and help to assess risk in time management by calculating different levels of probability of execution . Utilization of the optimization model resulted in time saving of 9, 11 and 13% at 100% level of probability of program implementation for two, three and four course rotation respectively.
The model was utilized for the purpose of designing a new machinery unit for Wad Salman Agricultural Project. The model succeeded in generating the basic element to develop this new unit. These elements include machinery scheduling program, their costs and the technical and financial indicators of performance.
The model sensitivity to changes at 10% and 20% step of each single input (cultivated area and total cost of operations ) and their interactions on the outputs of maximum number of machines, total fuel costs, machine utilization factor and IRR for the Rahad four- course rotation using analysis of variance.
For the case of single input changes of the cultivated area reveals that there was significant (P.0.05) increase in maximum number of machines, total fuel costs and IRR with increase in cultivated area while there was no significant effect on machine utilization. The total costs, maximum number of machines and total costs of fuel were found to be significantly increased with costs increase. In contrast, there was no significant increase in both IRR and machine utilization.
For the case of multiple inputs effect of the area was found to be more dominant for the results indicate significant effects with maximum number of machines, total fuel costs and IRR and no significant effect for machine utilization.
The policy making recommendations generated from the model building and its application for the cases studied includes the benefits of application of the experts system as pre requisite for improving performance of scheduling and managing Rahad machinery set up, ability to compare alternative crop rotations with respect to machinery utilization. The model also offer aviable tool for decision – maker to control resources during implementation of machinery schedule and to build a new machinery service unit.
For future research the text indicated four areas that need to be studied in depth and to be added as submodels to the program.