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Full Description
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.
Contents
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.
