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- MakaleYalnız künye2025Scopus SJRQ3Infection transmission risk analysis in Covid-19 intensive care nurses
Şahin, Melek; Şenel, Bilgin; Şenel, Mine; Ünlükal, Ceren
The coronavirus pandemic, which affects the whole world, continues to spread rapidly. The pandemic has reached a serious extent and the risks are getting deeper. The sector most affected by the pandemic has been the health sector and health personnel have become an indispensable element of this process. The people at highest risk of being infected are nurses who are in contact with or are responsible for the care of COVID-19 patients. This study was conducted to investigate the transmission risk of COVID-19 infection among nurses who care for patients in intensive care units.In this study, to prevent the transmission of infection from patient to nurse, possible failures in the process were determined by experts selected from nurses, and risk analyses were performed using Failure Mode and Effects Analysis and Entrophy-based Grey Relational Analysis methods. In this study, the three most probable and high-priority failure types were determined in the failures made in the procedures for the transmission of the infection from the patient to the nurse.There is a need to increase the quantity and quality of intensive care unit care personnel to manage new waves of COVID-19 or possible pandemic situations effectively.
- MakaleYalnız künye2021Scopus SJRQ1Systems failure analysis using Z-number theory-based combined compromise solution and full consistency method
Yousefi, Samuel; Valipour, Mahsa; Gul, Muhammet
Financial and time constraints force managers to put limited failure modes in priority to implement corrective and preventive actions. Thus, how prioritization can be done more constructively is of particular importance. This study aims to introduce an improved Failure Modes and Effects Analysis (FMEA) technique based on an extension of the Combined Compromise Solution (CoCoSo) method and the Full Consistency Method (FUCOM) to assess and prioritize failures in a production process. These developed methods called Z-CoCoSo and Z-FUCOM rely on the Z-number theory. They can consider uncertainty and reliability simultaneously in determining the weights of risk factors and the value of these factors in the studied problem. The proposed approach can cover some shortcomings of the conventional FMEA technique employed in identifying potential failures before their occurrence. Applying this approach enables experts to consider different weights for risk factors and uncertainty in the risk assessment process and provides them with a reliable ranking with high separability. Implementing the introduced approach for a real case study in the automotive parts industry has been compared with FMEA and other existent versions of the used methods demonstrating its reliable prioritization.
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