Rankings and Decisions in Engineering: Conceptual and Practical Insights

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