Field-Based Reliability Assessment of Agricultural Machinery Using the Weibull Distribution: A Case Study in Northern State, Sudan
Abstract
Agricultural machinery reliability is critical for ensuring timely field operations, minimizing downtime, and improving machinery utilization. This study aimed to develop and evaluate an operational efficiency-based model to support maintenance planning and improve operational efficiency under Sudanese farming conditions. Five-year repair and maintenance records were obtained from the Northern State Agricultural Services Corporation, Sudan, for four machines: Belarus tractor, John Deere tractor, Camco tractor, and combine harvester. The collected data included operating hours, failure occurrences, and failures of major machine subsystems. A reliability model was developed using Microsoft Excel and Visual Basic for Applications (VBA), and the failure data were analyzed using the two-parameter Weibull distribution. Weibull parameters (shape β and scale α were estimated using probability plotting and linear regression, and reliability-life measures were determined for both machine and subsystem levels. At the machine level, the estimated shape parameter (β) ranged from 0.61 to 1.02, indicating different failure-rate patterns among the investigated machines. At the subsystem level, β values ranged from 1.18 to 2.25, indicating predominantly increasing failure rates consistent with wear, ageing, and component deterioration. The estimated reliability-life measures for the major subsystems ranged from 209 h for the combine harvester fuel system to 689 h for the Belarus brake system. The results demonstrate that Weibull-based reliability analysis can provide useful quantitative information for identifying failure patterns, prioritizing maintenance activities, planning spare parts, and supporting machinery replacement decisions. The developed model provides a practical approach for applying field failure data to reliability assessment and maintenance planning of agricultural machinery under Sudanese operating conditions.
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