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

Peyman Zandi, Mohammad Rahmani, Mojtaba Khanian and Amir Mosavi
Additional contact information
Peyman Zandi: Industrial Management Department, Allameh Tabataba’i University, Tehran 1489684511, Iran
Mohammad Rahmani: Industrial Management, Bu-ali Sina University, Hamedan 6517838695, Iran
Mojtaba Khanian: Young Researchers and Elite Club, Hamedan Branch, Islamic Azad University, Hamedan 6518764811, Iran
Amir Mosavi: Faculty of Civil Engineering, Dresden University of Technology, 01069 Dresden, Germany

Agriculture, 2020, vol. 10, issue 11, 1-27

Abstract: 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.

Keywords: risk management; fuzzy; failure mode and effects analysis (FMEA); TOPSIS; VIKOR; analytical hierarchy process (AHP); multi-criteria decision making; big data; operations research; project management; sustainable development; uncertainty analysis (search for similar items in EconPapers)
JEL-codes: Q1 Q10 Q11 Q12 Q13 Q14 Q15 Q16 Q17 Q18 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (7)

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