Food quality and safety risk diagnosis in the food cold chain through failure mode and effect analysis

Wu, Jhao-Yi; Hsiao, Hsin‐I

doi:10.1016/j.foodcont.2020.107501

Cited by 95 publications

(52 citation statements)

References 33 publications

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“…Many articles have been published on food supply chain risk assessment and the application of FMEA in this area. Moreover, the method has been applied in controlling food production risk [21,22,59].…”

Section: Resultsmentioning

confidence: 99%

“…Zamani et al [58] designed a decision support system (DSS) based on fuzzy logic for evaluating and ranking the adaptation scenarios proposed on climate changes in the system of agriculture water resources in the southwest of Iran. FMEA approach also was used as a preventive tool in recognizing the risks of quality and safety of food in food cold chain for reducing the risks via effective control strategies [59].…”

Section: Risk Assessment Toolsmentioning

confidence: 99%

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

et al. 2020

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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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Section: Resultsmentioning

confidence: 99%

Section: Risk Assessment Toolsmentioning

confidence: 99%

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

et al. 2020

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“…These include complete or partial failure to control the cold supply chain temperature during the transition, avoidance of simple administrative failures, such as not following shipment directions, or an unexpected regulatory inhibitor [ 60 ]. At times, the temperature abuse happens at the product receiving stage as well as the product dispatch stage, which has serious implications [ 61 ]. The trend of outsourcing has facilitated so many things, however, such issues have become multifold.…”

Section: Inhibitors To Cold Supply Chain Operationsmentioning

confidence: 99%

“…enablers, barriers [ 4 , 27 ], practices [ 20 , 49 ], performance [ 45 , 60 ], risk management [ 9 , 54 ], competitiveness [ 15 ], cold chain network [ 39 ] etc. using different methodologies; (systematic) literature review [ 7 , 41 ], bayesian approach [ 7 ], petri net modeling [ 9 ], ISM and MICMAC [ 17 , 46 ], optimization approaches [ 23 ], system dynamic approach [ 36 ], and failure mode effect analysis [ 61 ]. Furthermore, the scope of these studies vary greatly; food cold supply chain [ 8 , 47 ], perishable food supply chain quality [ 10 ], vaccine cold chain [ 13 ], sea-food supply chain, halal food supply chain [ 24 ], fruits & vegetables supply chain [ 25 ], processed food supply chain [ 26 ], pineapple supply chain [ 42 ], strawberry supply chain [ 51 ], dairy supply chain [ 56 ].…”

Section: Inhibitors To Cold Supply Chain Operationsmentioning

confidence: 99%

Modelling the inhibitors of cold supply chain using fuzzy interpretive structural modeling and fuzzy MICMAC analysis

Sharma

Abbas²,

Siddiqui

2021

PLoS ONE

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The Cold Supply Chain (CSC) is an integral part of the supply chain of perishable products. The aim of this research is to examine the inhibitors that have a major impact on the performance of CSC operations in the United Arab Emirates (UAE). This study provides a synthesis and suggests a hierarchical model among CSC inhibitors and their respective relevance. The hierarchical synthesis of twelve (12) primary CSC inhibitors is achieved through a comprehensive literature review and consultation with academics and CSC professionals. This study used semi-structured interviews, a fuzzy interpretive structural modeling (FISM) and a Fuzzy-MICMAC (FMICMAC) analysis to explore and establish the relationship between and among identified inhibitors. FISM is used to examine the interaction between inhibitors, while FMICMAC analysis is used to examine the nature of inhibitors on the basis of their dependence and driving power. The results of the FISM and FMICMAC analysis show the inter-relationships and relative dominance of identified inhibitors. The results show that some inhibitors are of high strategic importance due to their high driving power and low dependence. These inhibitors seek more management attention in order to improve their effectiveness. The result of a hierarchical model helps to understand the influence of a particular inhibitor on others. ‘Higher capital and operating costs’ occupy the highest level in the FISM model. The ‘fragmented cold supply chains’, ‘lack of skilled labor’, ‘inadequate information system infrastructure’ and ‘lack of commitment by top level management’ had strong driving power but weak dependence, which characterizes them as independent inhibitors. Management should be extra careful when dealing with these inhibitors as they influence the effects of other variables at the top of the FISM hierarchy in the overall management of the cold supply chain. The study also suggests a number of recommendations for addressing these inhibitors in cold supply chains operating in the UAE. With due attention and care for these inhibitors, the operation of the cold supply chains is likely to be even more successful.

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“…In academia, various researchers have studied complex food safety issues, each with its own terminology and classification, for example, Wu and Hsiao [ 9 ] used a failure mode and effect analysis (FMEA) method to evaluate risk in food cold chains for chilled or frozen food companies in Taiwan; Lai et al [ 10 ] estimated on disease burden from foodborne illnesses in Taiwan from 2012 to 2015; Wu, Lin, and Chen [ 11 ] investigated food safety risks in China; Whitworth, Druckman, and Woodward [ 12 ] proposed the categorization of food scares; Jespersen, MacLaurin, and Vlerick [ 13 ] developed the food safety desirability response scale; Park, Kim, and Bahk [ 14 ] analyzed South Korean food safety incidents between 1998 and 2016; Nayak and Waterson [ 15 ] studied the food safety culture of a group of industry stakeholders in the UK; Wongprawmas and Canavari [ 16 ] provided food safety label categories that are indicators of Thailand consumers’ willingness to pay. Despite the increased academic interest in food safety issues in recent years, food safety incidents remain problematic and have not declined significantly over the past decade.…”

Section: Introductionmentioning

confidence: 99%

Food Safety Gaps between Consumers’ Expectations and Perceptions: Development and Verification of a Gap-Assessment Tool

Lin

Tsai

2020

IJERPH

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In recent decades, food safety has become a major concern due to frequent food safety incidents in many countries. This may lead to increased health risks associated with low quality food consumption, thereby reducing consumer trust in food safety. A better understanding of consumer perceptions of food safety can improve indicators that do not meet consumer expectations. We propose a food safety gap model with four gap-construct based on consumer expectations and perceptions. The model was empirically tested through a survey of 25 items, and then assessed for gaps through the importance–performance analysis (IPA). From a sample of 697 Taiwanese consumers, we found a huge gap between consumer expectations and perceptions related to food safety. More importantly, the results of the IPA indicate that most items must be immediately improved, which is vital in order to mitigate the risk of food safety.

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Food quality and safety risk diagnosis in the food cold chain through failure mode and effect analysis

Cited by 95 publications

References 33 publications

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

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

Modelling the inhibitors of cold supply chain using fuzzy interpretive structural modeling and fuzzy MICMAC analysis

Food Safety Gaps between Consumers’ Expectations and Perceptions: Development and Verification of a Gap-Assessment Tool

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