ABSTRACT
In this study, the hazards occurring in a medium-sized gas filling facility were defined, and the risk scores of these hazards were determined by the expert team according to the Fine-Kinney risk analysis method. However, since the same risk significance score is obtained in different combinations of scale values in the classical Fine-Kinney risk analysis method and the characteristics/constraints of the company applied in the risk analysis are not taken into account, the hazards were evaluated using fuzzy Fine-Kinney risk analysis, and the most critical hazards were determined. Action plans are defined for critical hazards determined as a result of fuzzy Fine-Kinney risk analysis. Among the actions that require company resources, the action selection was performed with the TOPSIS method, taking into account their relationship with the hazards by integrating the weights, which was calculated with the AHP method, of affected groups. The effect of operating constraints is included in the last step of the study to calculate the final weights. Calculating the results by including the risk-affected groups and company constraints and ranking the actions reveals that the study is an original, objective, and applicable study.
Subject(s)
Fuzzy Logic , Risk AssessmentABSTRACT
Introduction: Amyotrophic lateral sclerosis (ALS) is a disease with high morbidity and mortality that adversely affects the activities of daily living. Disease progression in ALS is characterized by loss of function in bulbar, motor, and respiratory parameters. The revised amyotrophic lateral sclerosis functional rating scale (ALSFRS-R), which consists of 12 criteria, is used to determine disease effects on each of these functions. While each criterion is equally important when calculating the total ALSFRS-R score, the importance levels of the 12 criteria may vary in clinical practice. In this classical approach, the relationships among the parameters are not considered and the effects of bulbar, spinal, and respiratory dysfunctions on a patient's activities of daily living may be different. Methods: In this study, we aimed to evaluate ALS cases with the ALSFRS-R fuzzy method. Although each subheading in the ALSFRS-R had the same score, the disease score was determined by the fuzzy ALSFRS-R method, based on whether a subheading had priority in management of the disease. While creating the functional rating scale ALSFRS-R approach, fuzzy ALSFRS-R score values were obtained by creating fuzzy models for each main group and integrating the fuzzy model results of each main group into a separate model. Results: In total, 50 patients with definite ALS according to the El Escorial criteria (33 men [66%] and 17 women [34%]; mean age, 58.49±10.01 years) were included in the study. When ALSFRS-R results and fuzzy ALSFRS-R results were compared, the prioritization order of 45 patients increased using the fuzzy ALSFRS-R score, while the prioritization order of five patients remained the same in both evaluations. Conclusion: The approach obtained by using fuzzy membership functions and decision rules, formed in accordance with expert opinion, was applied to the data of 50 patients from a large-scale hospital. In total, 90% of the patients had increased prioritization when using the fuzzy ALSFRS-R scoring method. Our results showed that the fuzzy approach provided more accurate information regarding a patient's condition.
ABSTRACT
Cold chain, which affects human health and quality of life, is applied for temperature-sensitive and perishable products. Any problems occurring in the cold chain can cause deterioration in products, causing poisoning, death, or various diseases. There are many stages in the cold chain itself and the risk significance level of each stage is different. Therefore, the risks that occur depending on the weight of the stages in the cold chain should be defined and minimized and action plans are needed to be formed. Every action in the action plan cannot be implemented simultaneously since each action requires a different amount of budget and time resources of the companies are finite. Hence, the risks occurring in the cold chain should be minimized with the maximum use of limited company resources. In this study, an integrated mathematical model with analytical hierarchy method and failure mode and effect analysis is proposed that will maximize the weighted risk reduction amount by considering the budget and time constraints of the companies at the same time. The proposed approach has been applied in the 3PL service provider and the results are discussed. According to the results of the study where maximum benefit is aimed with the actions taken against the dangers, the maximum objective function value was obtained at the second and third levels of the workforce and budget values by evaluating the different situations with scenario analyses. In this solution, it is foreseen that by taking 5 actions, improvement will be made in 14 hazards.
