pareto method
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2022 ◽  
pp. 215-229
Author(s):  
Antonia Mourtzikou ◽  
Marilena Stamouli ◽  
Georgia Kalliora ◽  
Ioanna Petraki ◽  
Christina Seitopoulou ◽  
...  

The use of quality indicators (QIs) and risk assessment are valuable tools for maintaining the quality of laboratory tests. Both are requirements of ISO 15189: 2012 and are usually based on standard statistical and empirical data. In this chapter, the authors focus on evaluating clinical laboratory quality indicators in the era of the COVID-19 pandemic. The goal is to pose and discuss, based on the authors' experience, the quality evaluation and risk assessment through the collection, study, and analysis of quality indicators covering the pre-analytical, analytical, and post-analytical phases of the laboratory testing process. QIs were evaluated using the Six Sigma method. Moreover, FMEA risk analysis was performed, and the degree of risk priority was assessed using the Pareto method. The results show that in the analytical phase, the laboratory's performance is satisfactory, while the pre-and post-analytical phases need further preventive/corrective actions.


Author(s):  
O.V. Tatarnikov ◽  
W.A. Phyo ◽  
Lin Aung Naing

This paper describes a method for optimizing the design of a spar-type composite aircraft wing structure based on multi-criterion approach. Two types of composite wing structures such as two-spar and three-spar ones were considered. The optimal design of a wing frame was determined by the Pareto method basing on three criteria: minimal weight, minimal wing deflection, maximal safety factor and minimal weight. Positions of wing frame parts, i.e. spars and ribs, were considered as optimization parameters. As a result, an optimal design of a composite spar-type wing was proposed. All the calculations necessary to select the optimal structural and design of the spar composite wing were performed using nonlinear static finite element analysis in the FEMAP with NX Nastran software package.


Author(s):  
Allan Costa Gomes ◽  
Raimundo Furtado Sampaio ◽  
Giovanni Cordeiro Barroso ◽  
Ruth Pastora Saraiva Leao
Keyword(s):  

2021 ◽  
Vol 4 ◽  
pp. 48-60
Author(s):  
Elchin Aliyev ◽  
◽  
Elmar Aliyev ◽  
Adilya Ali ◽  
◽  
...  

A comprehensive analysis of the applicantʼs solvency for obtaining a microcredit precedes the conclusion of a loan agreement with him. This allows to determine the risk factors associated with the possibility of non-repayment of a bank loan in due time, and, on the contrary, to assess the likelihood of timely repayment of the loan. Therefore, the assessment of the clientʼs creditworthiness is an integral part of the work of commercial banks and microfinance organizations to determine the possibility of issuing microloans to one or another applicant. The paper proposes a balanced approach to the multi-criteria assessment of the solvency of individuals, based, among other things, on a fuzzy analysis of their solvency indicators. The developed fuzzy inference system in combination with statistical methods for assessing solvency, can serve as an analytical core for a credit decision support system. Based on the example of ten hypothetical alternative borrowers, characterized by their current indicators, the corresponding assessments of their solvency were made, including scoring, Pareto method, Bord method and using a fuzzy inference system. Such a combined approach is distinguished by the ability to identify reliably a group of individuals with high credit discipline and the characteristics of those in relation to whom credit decisions are classified as high-risk.


Author(s):  
Kostiantyn Predun ◽  
Yurii Franchuk ◽  
Olha Obodianskaya

Natural gas in accordance with the provisions of the Energy Strategy of Ukraine for the period up to 2035, despite the significant development of "green" energy remains the main energy source in the country. Due to the accession to the single European area of regulation of natural gas trade in the country, all calculations for fuel consumption should be performed in units of energy. Thus, the defining issues are the quality of natural gas. One of the features of the gas supply system is a  significant degree of uncertainty in the change of a large number of disturbing factors and constantly changing parameters of its operation. Among others, a mathematical model based on the theory of fuzzy logic was chosen to assess quality. Based on the results of consideration of factors characterizing the physical and chemical properties of natural gas extracted from the field, the quality of its preparation for transportation and technical conditions of operation of the gas distribution system of the settlement, a fuzzy set was obtained to determine fuel quality. One of the methods of analysis in complex and multiconnected systems is the Pareto method, which consists in classifying problems into a few, but essential, and numerous, but insignificant. Modeling the management of natural gas quality using the membership functions of linguistic variables, which are the factors influencing it by the Pareto method, allows to vary the most significant factors that take into account the most influential of them. The resulting Pareto bar chart clearly illustrates the number of factors influencing the quality of natural gas. The diagram shows that the most influential factors on the quality of natural gas and on reducing the operational reliability of gas transmission and gas distribution systems are, respectively, higher heat of combustion under standard conditions and fuel moisture content. In this regard, in the organizational and technological support of natural gas consumption at a high level, they should be considered in the first place. 


2021 ◽  
Author(s):  
V. I. Tihvinskiy ◽  
L. V. Kazantseva ◽  
V. A. Morozov

2021 ◽  
Vol 307 ◽  
pp. 06004
Author(s):  
Artem Artyukhov ◽  
Sergii Lyeonov ◽  
Tetyana Vasylieva ◽  
Jan Polcyn

The article is devoted to selecting the methods of finding the cause-effect relationships in simulating the system “quality education” and to determining the factors influencing the quality of education in the socioeconomic development of both the university and education stakeholders. The rationale for selecting the tools for studying cause-and-effect relationships in modelling the system is formulated. It is shown that for the system “quality of education” it is possible to use analysis tools that were previously inherent only in technical systems. An integrated approach to assessment using the Pareto method, Ishikawa method, cycle and Deming principles is proposed. Each stage of studying cause-and-effect relationships is considered; the relationship between the stages and the tools used is shown. The consistent application of these tools for the “quality of education” system has not yet been implemented, which determines the novelty of this work. As a result of implementing such a complex algorithm, the system approaches the external quality assessment in its optimal state with a clearly expressed optimization criterion and methods of achieving it.


Author(s):  
Carlos Andres Delgado Saavedra ◽  
Angel García-Baños ◽  
Victor Andrés Bucheli-Guerrero

Rankings compare the performance of organizations. In many cases, rankings provide a good assessment of successful or-ganizations. However, rankings often generate controversy and debate since they support the making decisions. A ranking is a weighted linear combination of indicators, and the weights assigned to each of the indicators can lead to different rank orders. In most cases, rankings are used as a tool to support making decisions, such as resource allocation; therefore, these decisions can be affected by the assignment of such weights. In this article, we analyze the behavior of a ranking and the weights; simulations are used to calculate the change in the order of the equally weighted ranking and of the randomly weighted ranking. In this regard, we present a discussion and ranking design alternatives.


2020 ◽  
Vol 9 (2) ◽  
pp. 18-33
Author(s):  
Zoi S. Athanasiadou ◽  
Antonia Mourtzikou ◽  
Marilena Stamouli ◽  
Petros Karkalousos

The use of quality indicators and risk evaluation are valuable tools for maintaining the quality of laboratory tests. There are both requirements of ISO 15189: 2012 and are usually based on common statistical and empirical data. The purpose of the present study was the quality quantification and risk evaluation through the collection, study, and analysis of quality indicators covering the pre-analytical, analytical, and post-analytical phases of the laboratory testing process. Statistical data was collected for the period from 1/12/2017 to 28/2/2018, using the LIS of Biochemical Laboratory. QIs were evaluated using the Six Sigma method and the Pareto statistical tool. FMEA risk analysis was performed, while the degree of risk priority with the Pareto method. The results show that in the analytical phase the QIs give us satisfactory values, while those in the pre- and post- analytical phases need further preventive/corrective actions in order to overcome the problems raised by the QIs. Thus, the fully automatization and computerization of the laboratory is needed.


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