Optimization of Agricultural Machinery Utilization: A Case of Hetosa Farmers’ Cooperative Union, Oromia Region

Abstract

Farm mechanization refers to the integration of various tools, implements, and machinery into agricultural practices to improve production efficiency and effectiveness. A preliminary assessment of the Hetosa Farmers' Cooperative Union reveals several issues with the utilization of agricultural machinery, which hinder its members from delivering timely and effective mechanized services. The research was motivated by significant issues in the union's present machinery management system, including a lack of modern scheduling, outdated equipment, lack of data-based management, and underutilization of the existing machinery. A mixed-methods approach using qualitative and quantitative data collection instruments through interviews, questionnaires, and secondary data sources was employed in the study. Route optimization was done using MATLAB, GIS was used for terrain analysis, CROPWAT and MS Project for precipitation and crop period assessment and task scheduling, respectively. Census and purposive sampling techniques are used to assess the existing machinery, and tabu search algorithm and origin-destination cost matrices have been used in this study to reduce route distances and fuel consumption. The result indicated that the union could minimize the total fuel used by 11.28% throughout the region and up to 23.34% only in the Hetosa woreda. This greatly cuts the operational cost and enhances the working hours. An annual unproductive labor cost of 123,852 birr was identified due to inefficient refueling and machinery downtimes, with a combined financial loss of over 5.48 million birr in tillage and harvesting services. It was found that tractors and combine harvesters were outdated and could not support GPS technologies, thus leading to poor utilization and increasing maintenance costs. The study included Land use analysis of all Hetosa member woredas, which are Zuway Dugda, Dodota, Hetosa, Lude Hetosa, Munisa, Tiyo, and Sire. The study also established that full mechanization would be feasible in sloppy areas like Zuway Dugda and Dodota, while Munisa and Tiyo areas needed semi large scale and small-scale mechanization with targeted intervention supported by strategic scheduling. CROPWAT and MS Project utilized to analysis the growing periods and task scheduling respectively, enabled good machinery allocation and resource management. Based on these findings, the study recommends replacing aging machinery, establishing a fuel storage facility in order to reduce refueling time, promoting cluster farming to reduce fragmentation of farm areas, adopting digital machinery management, and improving coordination with governmental bodies to improve the supply chain. GIS-based landscape analysis is also recommended to enhance sustainable land use and machinery performance in varied landforms for the East Arsi Zone.