Advanced Risk Analysis in Engineering Enterprise Systems

1. Auflage 2023
ISBN: 978-1-032-47755-8
Verlag: CRC Press

Buch, Englisch, 464 Seiten, Format (B × H): 156 mm x 234 mm, Gewicht: 453 g

Reihe: Statistics: A Series of Textbooks and Monographs

Since the emerging discipline of engineering enterprise systems extends traditional systems engineering to develop webs of systems and systems-of-systems, the engineering management and management science communities need new approaches for analyzing and managing risk in engineering enterprise systems. Advanced Risk Analysis in Engineering Enterprise Systems presents innovative methods to address these needs.

With a focus on engineering management, the book explains how to represent, model, and measure risk in large-scale, complex systems that are engineered to function in enterprise-wide environments. Along with an analytical framework and computational model, the authors introduce new protocols: the risk co-relationship (RCR) index and the functional dependency network analysis (FDNA) approach. These protocols capture dependency risks and risk co-relationships that may exist in an enterprise.

Moving on to extreme and rare event risks, the text discusses how uncertainties in system behavior are intensified in highly networked, globally connected environments. It also describes how the risk of extreme latencies in delivering time-critical data, applications, or services can have catastrophic consequences and explains how to avoid these events.

With more and more communication, transportation, and financial systems connected across domains and interfaced with an infinite number of users, information repositories, applications, and services, there has never been a greater need for analyzing risk in engineering enterprise systems. This book gives you advanced methods for tackling risk problems at the enterprise level.

Autoren/Hrsg.

Pinto, Cesar Ariel

Garvey, Paul R.

Fachgebiete

• Technische Wissenschaften Maschinenbau | Werkstoffkunde Produktionstechnik Industrielle Qualitätskontrolle
• Mathematik | Informatik Mathematik Stochastik
• Wirtschaftswissenschaften Betriebswirtschaft Management Qualitätsmanagement, Qualitätssicherung (QS), Total Quality Management (TQM)
• Technische Wissenschaften Technik Allgemein Industrial Engineering

Inhaltsverzeichnis

Engineering Risk Management. Perspectives on Theories of Systems and Risk. Foundations of Risk and Decision Theory. A Risk Analysis Framework in Engineering Enterprise Systems. An Index to Measure Risk Co-Relationships. Functional Dependency Network Analysis. A Decision-Theoretic Algorithm for Ranking Risk Criticality. A Model for Measuring Risk in Engineering Enterprise Systems. Random Processes and Queuing Theory. Extreme Event Theory. Prioritization Systems in Highly Networked Environments. Risks of Extreme Events in Complex Queuing Systems. Appendix. References. Index.

Über Autor(innen)

C. Ariel Pinto is an Associate Professor in the Department of Engineering Management and Systems Engineering at Old Dominion University, where he co-founded the Emergent Risk Initiative. He earned a Ph.D. in systems engineering from the University of Virginia. Dr. Pinto’s research interests encompass the areas of risk management in engineered systems, including project risk management, risk valuation, risk communication, analysis of extreme-and-rare events, and decision making under uncertainty.

Paul R. Garvey is Chief Scientist and a Director for the Center for Acquisition and Systems Analysis, a division of The MITRE Corporation. He earned an A.B. and M.Sc. in pure and applied mathematics from Boston College and Northeastern University, respectively, and a Ph.D. in engineering management from Old Dominion University, where he was awarded the doctoral dissertation medal from the faculty of the College of Engineering. He is the author of the CRC Press books Analytical Methods for Risk Management and Probability Methods for Cost Uncertainty Analysis. Dr. Garvey’s research interests include the theory and application of risk-decision analytic methods to operations research problems in the system sciences domains.