Document Type : Original Article
Authors
1 Department of Agricultural Systems Engineering, Islamic Azad University, Tehran Science and Research Branch, Tehran, Iran
2 Department of Agricultural Economics, Science and Research Branch, Islamic Azad University, Tehran, Iran
3 Department of Mechanical Engineering, Shahr-e Qods Branch, Islamic Azad University, Shahr-e Qods, Iran
4 3. Department of Mechanical Engineering, Shahr-e Qods Branch, Islamic Azad University, Shahr-e Qods, Iran
Abstract
The obsolescence of grain harvesting combine fleets in Iran, in addition to increasing operation and maintenance costs, leads to higher harvesting losses, reduced operational capacity and efficiency, and diminished machinery reliability. This study was conducted to develop and evaluate a multi-criteria decision-making (MCDM) model for selecting the optimal replacement option for obsolete combines. Initially, influential indicators were identified through a literature review and screened using the Delphi method based on the opinions of 15 experts in mechanization and agricultural economics. Subsequently, the weights of these indicators were determined using the Fuzzy Analytical Hierarchy Process (FAHP), and four alternatives—new domestic combines, new foreign combines, used foreign combines, and major overhaul—were ranked using the TOPSIS technique. The results indicated that technical (0.326) and economic (0.261) dimensions held the highest significance, with the harvesting loss rate (global weight of 0.141) identified as the most critical indicator. The ranking of alternatives revealed that new foreign combines (similarity index of 0.673), new domestic combines (0.515), used foreign combines (0.405), and major overhaul (0.258) ranked first to fourth, respectively. Sensitivity analysis confirmed the stability of the ranking. Based on the findings, decision-making for fleet modernization should be grounded in technical performance, harvesting losses, life-cycle costs, and reliability, rather than merely machine age or initial purchase cost. The proposed model can serve as an efficient tool for fleet modernization policymaking and selecting optimal options for operators.
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