Agriculture (Oct 2020)

Agricultural Risk Management Using Fuzzy TOPSIS Analytical Hierarchy Process (AHP) and Failure Mode and Effects Analysis (FMEA)

  • Peyman Zandi,
  • Mohammad Rahmani,
  • Mojtaba Khanian,
  • Amir Mosavi

DOI
https://doi.org/10.3390/agriculture10110504
Journal volume & issue
Vol. 10, no. 11
p. 504

Abstract

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Failure mode and effects analysis (FMEA) is a popular technique in reliability analyses. In a typical FMEA, there are three risk factors for each failure modes: Severity (S), occurrence (O), and detectability (D). These will be included in calculating a risk priority number (RPN) multiplying the three aforementioned factors. The literature review reveals some noticeable efforts to overcome the shortcomings of the traditional FMEA. The objective of this paper is to extend the application of FMEA to risk management for agricultural projects. For this aim, the factor of severity in traditional FMEA is broken down into three sub-factors that include severity on cost, the severity on time, and severity on the quality of the project. Moreover, in this study, a fuzzy technique for order preference by similarity to ideal solution (TOPSIS) integrated with a fuzzy analytical hierarchy process (AHP) was used to address the limitations of the traditional FMEA. A sensitivity analysis was done by weighing the risk assessment factors. The results confirm the capability of this Hybrid-FMEA in addressing several drawbacks of the traditional FMEA application. The risk assessment factors changed the risk priority between the different projects by affecting the weights. The risk of water and energy supplies and climate fluctuations and pests were the most critical risk in agricultural projects. Risk control measures should be applied according to the severity of each risk. Some of this research’s contributions can be abstracted as identifying and classifying the risks of investment in agricultural projects and implementing the extended FMEA and multicriteria decision-making methods for analyzing the risks in the agriculture domain for the first time. As a management tool, the proposed model can be used in similar fields for risk management of various investment projects.

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