Risk assessment of crane operation hazards using modified FMEA approach with Z-number and set pair analysis

In view of two key deficiencies of failure mode and effects analysis (FMEA) in crane operation hazard risk assessment-information loss and hazard grade lack, a crane operation hazard risk assessment model based on the Z-number and set pair analysis (Z-SPA) is proposed. In this research, the Z-number is used to address the information uncertainty. To reduce the risk losing evaluation information in the conversion of the Z-number into a crisp number, it is translated into an interval number. In this assessment model, the grades of crane operation hazards are determined using grade discrimination rules and a score function of a connection number based on set pair analysis. Two case studies are presented to exemplify the effectiveness of the approach. The first case validates the proposed method, and the second case illustrates the application of the modified FMEA to crane operation hazard risk analysis. Furthermore, the assessment results are analyzed and compared with previous studies to highlight the superiority of the proposed model.

Empowerment of individuals in Iranian health systems: a qualitative study using the Z-cognitive map approach

The empowerment of people is considered as one of the most effective approaches in national healthcare systems. Identifying the effective criteria for this empowerment approach can be useful for planning enhancements. Therefore, studying and researching different aspects of people empowerment, and identifying the various relationships among related factors are of great importance. In this study - after identifying and extracting the effective factors in empowering individuals/insured persons, and interviewing health insurance and healthcare experts through content analysis - a causal model examining variables and their impact intensity through cognitive mapping is designed and drawn up. In modeling the concept of empowerment, to cover the ambiguity of expert comments, a combination of the Z-number approach with cognitive mapping has been used. Results demonstrate how various factors relate to insured empowerment. According to the results of empowerment strategies, the insurance participation strategy with the highest central index was determined as the most effective strategy, and the appropriate component for individuals gained the highest score in the centrality index. The results of this article help a lot to policy making in medical insurance.

Re-evaluation of the healthcare service quality criteria for the Covid-19 pandemic: Z-number fuzzy cognitive map

Hospitals as healthcare centers have faced many challenges with the Covid-19 spread, which results in a decline in the quality of health care. Because the number of patients referred to hospitals increases dramatically during the pandemic, providing high-quality services and satisfying them is more important than ever to maintain community health and create loyal customers in the future. However, health care quality standards are generally designed for normal circumstances. The SERVPERF standard, which measures customer perceptions of service quality, has also been adjusted for hospital service quality measurement. In this study, the SERVPERF standard criteria for health services are evaluated in the Covid-19 pandemic. For this purpose, by considering the causal relationships between the criteria and using Z-Number theory and Fuzzy Cognitive Maps (FCMs), the importance of these criteria in the prevalence of infectious diseases was analyzed. According to the results, hospital reliability, hospital hygiene, and completeness of the hospital with ratios 0.9559, 0.9305, and 0.9268 are respectively the most influential criteria in improving the quality of health services in the spread of infectious diseases circumstances such as the Covid-19 pandemic. A review of the literature shows that in previous studies, comprehensive research has not been done on prioritizing the criteria for measuring the quality of health services in the context of the spread of infectious diseases.

An integrated quality and resilience engineering framework in healthcare with Z-number data envelopment analysis

Supplier selection for medical equipment is a major challenge for hospitals in healthcare supply chains. The primary reason for measuring medical equipment supplier efficiency is to achieve the highest level of overall performance and productivity in healthcare supply chains. This study presents an integrated quality and resilience engineering (QRE) framework for evaluating medical equipment suppliers' performance using structural equation modeling and Z-number data envelopment analysis (Z-DEA). Noise analysis is used to select the best α-cut for the Z-DEA model, and fuzzy data are used to handle uncertainties. We show that flexibility, conformance to standards, redundancy, cost, quality certifications, and delivery time significantly affect the medical equipment suppliers' performance. In addition, we demonstrate that the proposed integrated QRE framework is more efficient and informative than stand-alone quality engineering or resiliency engineering. We present a case study in a cardiovascular hospital to illustrate the applicability of the proposed framework for medical equipment supplier evaluation and selection. To the best of our knowledge, this is the first study to integrate QRE and Z-DEA for supplier performance evaluation in healthcare.

Assessment of methods for determination of glycan composition of erythropoietin

Erythropoietin (EPO) is a monomeric, highly glycosylated, protein hormone (molecular size around 30-35 kD), produced mainly in adult kidneys, which acts principally on red blood cell progenitors and precursors to promote red cell production. Therapeutic EPO products are widely used biotherapeutics. They are mainly produced by recombinant DNA technology in mammalian cells and their biological activity is closely linked to the degree of N-glycan sialylation. Determination of the sialic acids' content and complexity by glycan mapping therefore appears critical to ensure the quality and efficacy of the EPO therapeutic products. The European Directorate for the Quality of Medicines & HealthCare organised a study (BSP144) under the aegis of the Biological Standardisation Programme to assess N-glycan mapping tests with the aim of incorporating a standard method into the European Pharmacopoeia monograph 'Erythropoietin concentrated solution' (1316). The use of a 'reagent panel' consisting of six EPO preparations with a range of iso-electric properties facilitated comparison between laboratories and methodologies. Based on the study results, a robust and repeatable HPAEC-PAD chromatographic method was identified and work to introduce it in the monograph as an example method has been initiated.

Sensor Data Fusion with Z-Numbers and Its Application in Fault Diagnosis

Sensor data fusion technology is widely employed in fault diagnosis. The information in a sensor data fusion system is characterized by not only fuzziness, but also partial reliability. Uncertain information of sensors, including randomness, fuzziness, etc., has been extensively studied recently. However, the reliability of a sensor is often overlooked or cannot be analyzed adequately. A Z-number, Z = (A, B), can represent the fuzziness and the reliability of information simultaneously, where the first component A represents a fuzzy restriction on the values of uncertain variables and the second component B is a measure of the reliability of A. In order to model and process the uncertainties in a sensor data fusion system reasonably, in this paper, a novel method combining the Z-number and Dempster–Shafer (D-S) evidence theory is proposed, where the Z-number is used to model the fuzziness and reliability of the sensor data and the D-S evidence theory is used to fuse the uncertain information of Z-numbers. The main advantages of the proposed method are that it provides a more robust measure of reliability to the sensor data, and the complementary information of multi-sensors reduces the uncertainty of the fault recognition, thus enhancing the reliability of fault detection.