Imagine that some designers individually formulate rankings of different alternative design concepts for a new product and should identify the best one collectively. Or imagine that some reliability engineers, when qualitatively assessing the severity of potential failures of a production machine, should aggregate their subjective rankings into a single collective judgment that represents them as best as possible. These are two of the innumerable applications of the so-called ranking aggregation problem, which consists in aggregating multiple subjective rankings into a single collective judgment. Despite the importance of this problem in engineering, the current scientific literature is somewhat fragmented and unstructured. The practical applications are often managed borrowing methodological approaches from more traditional contexts—such as social choice/voting theory, economics, psychometrics, multiple criteria decision making/analysis—without necessarily being familiar with the scientific literature. This fragmentation and poor structuring, together with the limited level of methodological detail, probably depends on the fact that researchers and practitioners in engineering hardly have in-depth knowledge of decision-making techniques and tools. This limitation certainly makes it challenging to choose the most appropriate methodological approaches, depending on (1) the characteristics of the practical context, (2) the information available, and (3) the desired output data. This book tries to overcome the above limitation, addressing an audience of academics, practitioners, and technicians working in the engineering field, who do not necessarily have in-depth knowledge of decision-making problems. The aim is to deeply investigate the ranking decision problem and the related features (such as input/output data, simplification hypotheses, and practical implications) and to illustrate several methodological approaches in a structured way. The description, intended to provide a sufficiently broad overview of state of the art, is supported by pedagogical examples and real-life case studies. Although scientifically rigorous, the formalization of problems is not too heavy in terms of mathematical technicalities, not to undermine the legibility and fluency of the entire document. On the other hand, interesting cues and bibliographical references are available for the reader who wishes to deepen technical aspects. With this book, the authors aim to provide the reader with a selection of the most interesting, curious, and useful topics that they have developed in over twenty years of research on decision making within the engineering field. In addition to providing an organic overview of the most consolidated methodological approaches, the book illustrates innovative techniques, which could also be profitably used outside the boundaries of engineering. The rest of the book is organized into six chapters, which are briefly described below. Chapter 2 formally defines the ranking aggregation problem, focusing the attention on the characteristic input and output data. Chapter 3 explores the concept of ranking from the perspective of the so-called measurement theory and its derivations. Chapter 4 focuses on evaluating the association/concordance of expert rankings, referring to some established and innovative techniques from the scientific literature. Chapter 5 illustrates in detail a selection of (consolidated and innovative) ranking aggregation techniques, analyzing their strengths and weaknesses. The description is accompanied by several pedagogical examples. Chapter 6 describes some quantitative tools to check the degree of consistency between the collective judgment and the input data, in a practical and intuitive way. Chapter 7 concludes the book, presenting several real-world examples of the ranking aggregation problem within engineering, with special reference to the activities of design, development, and evaluation of the quality and reliability of products, services, and manufacturing processes.

Rankings and decisions in Engineering. Conceptual and practical insights / Franceschini, Fiorenzo; Maisano, Domenico; Mastrogiacomo, Luca. - STAMPA. - 319:(2022), pp. 1-248. [10.1007/978-3-030-89865-6]

Rankings and decisions in Engineering. Conceptual and practical insights

FRANCESCHINI Fiorenzo;MAISANO Domenico;MASTROGIACOMO Luca
2022

Abstract

Imagine that some designers individually formulate rankings of different alternative design concepts for a new product and should identify the best one collectively. Or imagine that some reliability engineers, when qualitatively assessing the severity of potential failures of a production machine, should aggregate their subjective rankings into a single collective judgment that represents them as best as possible. These are two of the innumerable applications of the so-called ranking aggregation problem, which consists in aggregating multiple subjective rankings into a single collective judgment. Despite the importance of this problem in engineering, the current scientific literature is somewhat fragmented and unstructured. The practical applications are often managed borrowing methodological approaches from more traditional contexts—such as social choice/voting theory, economics, psychometrics, multiple criteria decision making/analysis—without necessarily being familiar with the scientific literature. This fragmentation and poor structuring, together with the limited level of methodological detail, probably depends on the fact that researchers and practitioners in engineering hardly have in-depth knowledge of decision-making techniques and tools. This limitation certainly makes it challenging to choose the most appropriate methodological approaches, depending on (1) the characteristics of the practical context, (2) the information available, and (3) the desired output data. This book tries to overcome the above limitation, addressing an audience of academics, practitioners, and technicians working in the engineering field, who do not necessarily have in-depth knowledge of decision-making problems. The aim is to deeply investigate the ranking decision problem and the related features (such as input/output data, simplification hypotheses, and practical implications) and to illustrate several methodological approaches in a structured way. The description, intended to provide a sufficiently broad overview of state of the art, is supported by pedagogical examples and real-life case studies. Although scientifically rigorous, the formalization of problems is not too heavy in terms of mathematical technicalities, not to undermine the legibility and fluency of the entire document. On the other hand, interesting cues and bibliographical references are available for the reader who wishes to deepen technical aspects. With this book, the authors aim to provide the reader with a selection of the most interesting, curious, and useful topics that they have developed in over twenty years of research on decision making within the engineering field. In addition to providing an organic overview of the most consolidated methodological approaches, the book illustrates innovative techniques, which could also be profitably used outside the boundaries of engineering. The rest of the book is organized into six chapters, which are briefly described below. Chapter 2 formally defines the ranking aggregation problem, focusing the attention on the characteristic input and output data. Chapter 3 explores the concept of ranking from the perspective of the so-called measurement theory and its derivations. Chapter 4 focuses on evaluating the association/concordance of expert rankings, referring to some established and innovative techniques from the scientific literature. Chapter 5 illustrates in detail a selection of (consolidated and innovative) ranking aggregation techniques, analyzing their strengths and weaknesses. The description is accompanied by several pedagogical examples. Chapter 6 describes some quantitative tools to check the degree of consistency between the collective judgment and the input data, in a practical and intuitive way. Chapter 7 concludes the book, presenting several real-world examples of the ranking aggregation problem within engineering, with special reference to the activities of design, development, and evaluation of the quality and reliability of products, services, and manufacturing processes.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11583/2957269