# The Development of a Cold-Chain-Packaging Risk Management Model Based on Fuzzy Bayesian Network
## 4 Case Study  
The global expansion of immunization programs, humanitarian supply chains and the pandemic disruptions of COVID-19 have increased the demand for vaccines in the past few years. A vaccine cold chain starts from when the research and development of the vaccines begin and then goes through manufacturing, transportation to national and regional storage facilities, and next moves to health centers or to outreach, all in refrigerated environments during transportation and storage. The WHO (2024) now has humanitarian vaccines for more than 20 life-threatening diseases, including diphthe, tetanus, pertussis, influenza, measles, etc., which can prevent about 3.5 to 5 million deaths every year [54]. Therefore, this case study aims to develop a risk management model for vaccine cold chain packaging. Risk factors leading to product safety risk and occupation safety risk are illustrated in Figures 2 and 3. To ease the calculation process, the risk assessment focuses on vaccine shipping container risk and handling risks, illustrated in Figure 4. Shipping containers contain monitoring devices and materials and devices for regulating the internal environment in the container. The risk factors for vaccine cold chain shipping solutions are listed in Table 1, and include product safety risk, occupational safety risk, container risk, handling  
Figure 1: Flow diagram of the BN-based risk management model. risk, monitoring and packaging risk. Possible causes of these risks are included as well as the possible consequences. The product safety risks are risks that can cause potential health and safety hazards due to vaccine quality deterioration. Contaminations, a loss of vaccine potency, over-thawing and mechanical damage can lead to product safety issues. This can lead to hazards, like vaccines not being effective, or can even cause harm to health. Occupational safety risks are risks that can cause harm to cold chain workers' health and safety due to the extraordinarily cold working environment or improper training, and this can lead to injuries or cold-related diseases, or to slipping on cold surfaces. Container risks are risks that can damage the shipping containers, and this can lead to temperature disruptions, quality decay and safety hazards. Potential causes of container risk include poor packaging or monitoring of the cold chain. Handling risks are risks that can lead to product or occupational safety issues due to incorrect handling, which can lead to safety hazards, damage to products, injuries and waste. Factors that can lead to handling risk include insufficient personnel training, vague instructions, lack of sanitation, etc. The monitoring risk refers to risks that cause monitoring disruptions and have the potential to cause over-thawing, lack of traceability, temperature disruptions, etc. Insufficient or poor monitoring devices and poor traceability  
Figure 3: Factors that can potentially lead to occupational-safety-related risk. Figure 2: Factors leading to vaccine safety risks. can cause monitoring-related risks. The packaging risk refers to risks that can cause damage to the packages, resulting in packaging not being able to provide sufficient temperature control or harming the environment. Potential causes of packaging-related risk consist of the use of improper materials, improper capacity, unsafe packages and packaging having a lack of sustainability. Domain experts have been asked to describe the prior and conditional probabilities of the nodes. In this case study, a seven-point Likert point scale was used, as recommended by the International Maritime Organization (IMO), as shown in Table 2. Triangular fuzzy membership sets are used for the fuzzification step. All membership functions in this case study use narrow ranges of intervals for calculation so the spread of the posterior probabilities is not too wide.