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Rankings and Decisions in Engineering: Conceptual and Practical Insights

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This book focuses on decision-making problems in engineering. It investigates the ranking aggregation problem and the related features, such as input/output data, simplification hypotheses, importance hierarchy of experts. In addition to a well-structured overview of several interesting, consolidated methodological approaches, it presents innovative approaches that can also be applied profitably in other fields. The fascinating selection of topics included is based on research that has been developed in the past twenty years. The descriptions are supported by figures, tables, flowcharts, diagrams, examples and practical case studies.

The book is an ideal resource for engineering academics, practitioners, technicians and students, who do not necessarily have an in-depth knowledge of decision-making. It is also a thought-provoking read for engineers and academics looking for innovative ways to improve engineering processes in a variety of fields, such as conceptual design, quality improvement, reliability engineering.

“Today, rankings are exercised in all spheres of life, products are ranked on Amazon and similar platforms; services such as restaurants and hotels on platforms such as TripAdvisor; and other services such as lectures or even medical treatment on different specialized platforms. We often make our daily decisions based on these rankings. The quality of our decisions depends on our ability to select appropriate methods to fit the context and needs. We need to be familiar with the theory and practice of these methods to make them useful. To this purpose, this book is an important addition to the bookshelves of academics and professionals, not only from engineering. The connection between theory and practice is weaved throughout the book, making it useful for practitioners also.”

Prof. Yoram Reich, Full Professor and Head of Systems Engineering research Initiative at Tel Aviv University (Israel), Editor-in-Chief of “Research in Engineering Design”

Author(s): Fiorenzo Franceschini, Domenico A. Maisano, Luca Mastrogiacomo
Series: International Series in Operations Research & Management Science, 319
Publisher: Springer
Year: 2022

Language: English
Pages: 258
City: Cham

Foreword
Preface
Contents
Abbreviations
Chapter 1: Introduction to Rankings and Decisions in Engineering
1.1 General Problem at a Glance
1.2 Historical Notes
1.2.1 Traditional Contexts
1.2.2 The Problem of Interest in Engineering
1.3 Response Modes for Data Collection
References
Chapter 2: Ranking Aggregation Problem
2.1 General Concepts
2.2 Input Data
2.2.1 Type of Rankings
2.2.2 Importance Hierarchy of Experts
2.3 Output Data
2.4 Specific Subproblems
References
Chapter 3: Rankings and Measurements
3.1 Introduction
3.2 Theory of Scales of Measurement
3.2.1 Nominal Scale
3.2.2 Ordinal Scale
3.2.3 Interval Scale
3.2.4 Ratio Scale
3.2.5 Comments on Stevens´ Scale Types
3.3 Representation Theory of Measurement
3.4 Rankings and Measurement Theory
3.4.1 Notion of Rank
3.4.2 Ordinal and Cardinal Rankings
3.4.3 Rankings as Special Measurements
References
Chapter 4: Ranking Association Measures
4.1 Introduction
4.2 Spearman´s Rank-Correlation Coefficient (ρ)
4.2.1 Definition
4.2.2 Practical Interpretation
4.2.3 Test of Significance
4.2.4 Example
4.3 Kendall´s Rank-Correlation Coefficient (τ)
4.3.1 Definition and Practical Interpretation
4.3.2 Test of Significance
4.3.3 Example
4.3.4 Concluding Remarks on ρ and τ
4.4 Kendall´s Coefficient of Concordance (W)
4.4.1 Example
4.4.2 Tied Objects
4.4.3 Test of Significance
4.5 Adapting W to Incomplete Rankings
4.5.1 Descriptive Parameters
4.5.2 Rationale of the Revised W
4.5.3 Examples
4.5.4 Final Considerations
Appendix
Further Data
References
Chapter 5: Ranking Aggregation Techniques
5.1 Taxonomy
5.1.1 Taxonomizing Aggregation Techniques
5.2 Case Study
5.3 Voting Theory´s Rule-Based Techniques
5.3.1 Best of the Best
5.3.2 Best Two
5.3.3 Instant-Runoff Voting
5.3.4 Borda Count
5.3.5 Further Application Examples
5.4 Techniques Involving a Hierarchy of Experts
5.4.1 ELECTRE-II Method
5.4.2 Yager´s Algorithm
5.4.3 Enhanced Yager´s Algorithm
5.5 Distribution-Based Techniques
5.5.1 Thurstone´s Law of Comparative Judgment
5.5.2 ZMII Technique
5.6 Comparing Different Aggregation Techniques
Appendix
Further Example
References
Chapter 6: Consistency of Ranking Aggregation Techniques
6.1 Notion of Consistency
6.2 p Indicators
6.2.1 Local Consistency: pj Indicators
6.2.2 Global Consistency: p, pA, and pB
6.2.3 Examples
6.2.4 Optimization Through p
6.3 Indicator
Appendix
Additional Figures
References
Chapter 7: Case Studies in Engineering
7.1 Introduction
7.2 P-FMEA for Distributed Manufacturing Processes
7.2.1 Methodology
7.2.2 Real-World Case Study (I)
7.2.3 Final Considerations
7.3 Prioritization of QFD Engineering Characteristics
7.3.1 Introduction to QFD
7.3.2 Real-World Case Study (II)
7.3.3 Final Considerations
7.4 Quality Classification with Rank-Ordered Experts
7.4.1 Background
7.4.2 Methodology and Real-World Case Study (III)
7.4.3 Final Remarks
7.5 Multi-attribute Analysis of Quality Perception
7.5.1 Real-World Case Study (IV)
7.5.2 Mapping Bivariate Ordinal Ratings into Rankings
7.5.3 Weighted Borda Count
References
Glossary
Index