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In today's highly competitive business environment, firms strive to maximize profitability by minimizing or eliminating disruptions and failures to maintain a competitive edge. This study focuses on evaluating risks in a hydraulic pump factory as a means to achieve sustainable growth. To accomplish this, a team of experts was formed to identify potential errors, utilizing a combination of risk priority number criteria weighted by Fuzzy Shannon's entropy and a fusion of multi-criteria decision-making and failure mode and effects analysis for evaluating and ranking failures. Moreover, the study emphasizes the importance of considering the interaction among risk assessment indicators, the inclusion of cost of failure, and modeling under fuzzy uncertainty circumstances, as they have a notable impact on the final ranking of failures to be processed for risk mitigation action planning. This research brings a new dimension to enhance the overall effectiveness of risk assessment by aggregation, as evidenced by a novel use of data classification in machine learning and correlation in statistics. The findings indicate that the aggregated ranking data series is best matched and most influenced by the weighted aggregated sum product assessment method, with the highest rate of recall and precision accomplished.
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BACKGROUND: Identification of blood group antigen frequencies in a population has various benefits in transfusion medicine. Most data in the literature include frequencies of these antigens in European and American countries. In this study for the first time we have reported frequencies of these antigens in the northeast of Iran. MATERIALS AND METHODS: Blood group antigens were characterized in the 522 blood donors in Mashhad, Iran. The following antigens including ABO, Rh (D, C, E, c, e), MNSs (M, N, S, s), Lutheran (Lu(a), Lu(b)), P (P, P(1)), Kell (K, k, Kp(a), Kp(b)), Lewis (Le(a), Le(b)), Duffy (Fy(a), Fy(b)) and Kidd (Jk(a), Jk(b)) were typed and phenotypes frequencies were expressed as a percentage. RESULTS: In the ABO blood group, the most common phenotype was O (33.9%) followed by A, B and AB. In the Rh blood group, the most common antigen was e (97.9%) and R(1)r (31.8%) being the most common phenotype. The most common phenotypes for MNSs, P, Lu and Kell blood group were M+N+, S-s+, P(1), Lu (a-b+), K-k+ and Kp (a-b+). A very rare phenotype of Lu (a-b-) was also observed in 2.7% of cases. We found rare phenotypes of Le (a+b+) and Fy (a-b-) in 7.9% and 3.4% of subjects, respectively. CONCLUSION: We determined some differences in phenotype frequencies of blood group compared with other studies. We found higher frequencies of B blood group and also more frequencies of some rare phenotypes, Lu (a-b-), Le (a+b+) and Fy (a-b-).
