A fail-safe supply network is designed to mitigate the impact of variations and disruptions on people and corporations. This is achieved by (1) developing a network structure to mitigate the impact of disruptions that distort the network structure and (2) planning flow through the network to neutralize the effects of variations. In this monograph, we propose a framework, develop mathematical models and provide examples of fail-safe supply network design. We show that, contrary to current thinking as embodied in the supply network literature, disruption management decisions made at the strategic network design level are not independent from variation management decisions made at the operational level. Accordingly, we suggest that it is beneficial to manage disruptions and variations concurrently in supply networks. This is achieved by architecting fail-safe supply networks, which are characterized by the following elements: reliability, robustness, flexibility, structural controllability, and resilience. Organizations can use the framework presented in this monograph to manage variations and disruptions. Managers can select the best operational management strategies for their supply networks considering variations in supply and demand, and identify the best network restoration strategies including facility fortification, backup inventory, flexible production capacity, flexible inventory, and transportation route reconfiguration. The framework is generalizable to other complex engineered networks.

This illuminating text/reference presents a review of the key aspects of the modeling and simulation (M&S) life cycle, and examines the challenges of M&S in different application areas. The authoritative work offers valuable perspectives on the future of research in M&S, and its role in engineering complex systems. Topics and features: reviews the challenges of M&S for urban infrastructure, healthcare delivery, automated vehicle manufacturing, deep space missions, and acquisitions enterprise; outlines research issues relating to conceptual modeling, covering the development of explicit and unambiguous models, communication and decision-making, and architecture and services; considers key computational challenges in the execution of simulation models, in order to best exploit emerging computing platforms and technologies; examines efforts to understand and manage uncertainty inherent in M&S processes, and how these can be unified under a consistent theoretical and philosophical foundation; discusses the reuse of models and simulations to accelerate the simulation model development process. This thought-provoking volume offers important insights for all researchers involved in modeling and simulation across the full spectrum of disciplines and applications, defining a common research agenda to support the entire M&S research community.

This illuminating text/reference presents a review of the key aspects of the modeling and simulation (M&S) life cycle, and examines the challenges of M&S in different application areas. The authoritative work offers valuable perspectives on the future of research in M&S, and its role in engineering complex systems. Topics and features: reviews the challenges of M&S for urban infrastructure, healthcare delivery, automated vehicle manufacturing, deep space missions, and acquisitions enterprise; outlines research issues relating to conceptual modeling, covering the development of explicit and unambiguous models, communication and decision-making, and architecture and services; considers key computational challenges in the execution of simulation models, in order to best exploit emerging computing platforms and technologies; examines efforts to understand and manage uncertainty inherent in M&S processes, and how these can be unified under a consistent theoretical and philosophical foundation; discusses the reuse of models and simulations to accelerate the simulation model development process. This thought-provoking volume offers important insights for all researchers involved in modeling and simulation across the full spectrum of disciplines and applications, defining a common research agenda to support the entire M&S research community.

A fail-safe supply network is designed to mitigate the impact of variations and disruptions on people and corporations. This is achieved by (1) developing a network structure to mitigate the impact of disruptions that distort the network structure and (2) planning flow through the network to neutralize the effects of variations. In this monograph, we propose a framework, develop mathematical models and provide examples of fail-safe supply network design. We show that, contrary to current thinking as embodied in the supply network literature, disruption management decisions made at the strategic network design level are not independent from variation management decisions made at the operational level. Accordingly, we suggest that it is beneficial to manage disruptions and variations concurrently in supply networks. This is achieved by architecting fail-safe supply networks, which are characterized by the following elements: reliability, robustness, flexibility, structural controllability, and resilience. Organizations can use the framework presented in this monograph to manage variations and disruptions. Managers can select the best operational management strategies for their supply networks considering variations in supply and demand, and identify the best network restoration strategies including facility fortification, backup inventory, flexible production capacity, flexible inventory, and transportation route reconfiguration. The framework is generalizable to other complex engineered networks.