A dual perspective towards building resilience in manufacturing organizations

Modern manufacturing organizations exist in the most complex and competitive environment the world has ever known. This environment consists of demanding customers, enabling, but resource intensive Industry 4.0 technology, dynamic regulations, geopolitical perturbations, and innovative, ever-expanding global competition. Successful manufacturing organizations must excel in this environment while facing emergent disruptions generated as biproducts of complex man-made and natural systems. The research presented in this thesis provides a novel two-sided approach to the creation of resilience in the modern manufacturing organization. First, the systems engineering method is demonstrated as the qualitative framework for building literature-derived organizational resilience factors into organizational structures under a life cycle perspective. A quantitative analysis of industry expert survey data through graph theory and matrix approach is presented second to prioritize resilience factors for strategic practical implementation

Critical Infrastructures: Enhancing Preparedness & Resilience for the Security of Citizens and Services Supply Continuity: Proceedings of the 52nd ESReDA Seminar Hosted by the Lithuanian Energy Institute & Vytautas Magnus University

Critical Infrastructures Preparedness and Resilience is a major societal security issue in modern society. Critical Infrastructures (CIs) provide vital services to modern societies. Some CIs’ disruptions may endanger the security of the citizen, the safety of the strategic assets and even the governance continuity. The European Safety, Reliability and Data Association (ESReDA) as one of the most active EU networks in the field has initiated a project group on the “Critical Infrastructure/Modelling, Simulation and Analysis – Data”. The main focus of the project group is to report on the state of progress in MS&A of the CIs preparedness & resilience with a specific focus on the corresponding data availability and relevance. In order to report on the most recent developments in the field of the CIs preparedness & resilience MS&A and the availability of the relevant data, ESReDA held its 52nd Seminar on the following thematic: “Critical Infrastructures: Enhancing Preparedness & Resilience for the security of citizens and services supply continuity”. The 52nd ESReDA Seminar was a very successful event, which attracted about 50 participants from industry, authorities, operators, research centres, academia and consultancy companies.JRC.G.10-Knowledge for Nuclear Security and Safet

A Survey on Centrality Metrics and Their Implications in Network Resilience

Centrality metrics have been used in various networks, such as communication, social, biological, geographic, or contact networks. In particular, they have been used in order to study and analyze targeted attack behaviors and investigated their effect on network resilience. Although a rich volume of centrality metrics has been developed for decades, a limited set of centrality metrics have been commonly in use. This paper aims to introduce various existing centrality metrics and discuss their applicabilities and performance based on the results obtained from extensive simulation experiments to encourage their use in solving various computing and engineering problems in networks.Comment: Main paper: 36 pages, 2 figures. Appendix 23 pages,45 figure

A Systematic Review of Quantitative Resilience Measures for Water Infrastructure Systems

Over the past few decades, the concept of resilience has emerged as an important consideration in the planning and management of water infrastructure systems. Accordingly, various resilience measures have been developed for the quantitative evaluation and decision-making of systems. There are, however, numerous considerations and no clear choice of which measure, if any, provides the most appropriate representation of resilience for a given application. This study provides a critical review of quantitative approaches to measure the resilience of water infrastructure systems, with a focus on water resources and distribution systems. A compilation of 11 criteria evaluating 21 selected resilience measures addressing major features of resilience is developed using the Axiomatic Design process. Existing gaps of resilience measures are identified based on the review criteria. The results show that resilience measures have generally paid less attention to cascading damage to interrelated systems, rapid identification of failure, physical damage of system components, and time variation of resilience. Concluding the paper, improvements to resilience measures are recommended. The findings contribute to our understanding of gaps and provide information to help further improve resilience measures of water infrastructure systems

Safety and Reliability - Safe Societies in a Changing World

The contributions cover a wide range of methodologies and application areas for safety and reliability that contribute to safe societies in a changing world. These methodologies and applications include: - foundations of risk and reliability assessment and management - mathematical methods in reliability and safety - risk assessment - risk management - system reliability - uncertainty analysis - digitalization and big data - prognostics and system health management - occupational safety - accident and incident modeling - maintenance modeling and applications - simulation for safety and reliability analysis - dynamic risk and barrier management - organizational factors and safety culture - human factors and human reliability - resilience engineering - structural reliability - natural hazards - security - economic analysis in risk managemen

Resilience of the Critical Communication Networks Against Spreading Failures: Case of the European National and Research Networks

A backbone network is the central part of the communication network, which provides connectivity within the various systems across large distances. Disruptions in a backbone network would cause severe consequences which could manifest in the service outage on a large scale. Depending on the size and the importance of the network, its failure could leave a substantial impact on the area it is associated with. The failures of the network services could lead to a significant disturbance of human activities. Therefore, making backbone communication networks more resilient directly affects the resilience of the area. Contemporary urban and regional development overwhelmingly converges with the communication infrastructure expansion and their obvious mutual interconnections become more reciprocal. Spreading failures are of particular interest. They usually originate in a single network segment and then spread to the rest of network often causing a global collapse. Two types of spreading failures are given focus, namely: epidemics and cascading failures. How to make backbone networks more resilient against spreading failures? How to tune the topology or additionally protect nodes or links in order to mitigate an effect of the potential failure? Those are the main questions addressed in this thesis. First, the epidemic phenomena are discussed. The subjects of epidemic modeling and identification of the most influential spreaders are addressed using a proposed Linear Time-Invariant (LTI) system approach. Throughout the years, LTI system theory has been used mostly to describe electrical circuits and networks. LTI is suitable to characterize the behavior of the system consisting of numerous interconnected components. The results presented in this thesis show that the same mathematical toolbox could be used for the complex network analysis. Then, cascading failures are discussed. Like any system which can be modeled using an interdependence graph with limited capacity of either nodes or edges, backbone networks are prone to cascades. Numerical simulations are used to model such failures. The resilience of European National Research and Education Networks (NREN) is assessed, weak points and critical areas of the network are identified and the suggestions for its modification are proposed

Mining complex trees for hidden fruit : a graph–based computational solution to detect latent criminal networks : a thesis presented in partial fulfilment of the requirements for the degree of Doctor of Philosophy in Information Technology at Massey University, Albany, New Zealand.

The detection of crime is a complex and difficult endeavour. Public and private organisations – focusing on law enforcement, intelligence, and compliance – commonly apply the rational isolated actor approach premised on observability and materiality. This is manifested largely as conducting entity-level risk management sourcing ‘leads’ from reactive covert human intelligence sources and/or proactive sources by applying simple rules-based models. Focusing on discrete observable and material actors simply ignores that criminal activity exists within a complex system deriving its fundamental structural fabric from the complex interactions between actors - with those most unobservable likely to be both criminally proficient and influential. The graph-based computational solution developed to detect latent criminal networks is a response to the inadequacy of the rational isolated actor approach that ignores the connectedness and complexity of criminality. The core computational solution, written in the R language, consists of novel entity resolution, link discovery, and knowledge discovery technology. Entity resolution enables the fusion of multiple datasets with high accuracy (mean F-measure of 0.986 versus competitors 0.872), generating a graph-based expressive view of the problem. Link discovery is comprised of link prediction and link inference, enabling the high-performance detection (accuracy of ~0.8 versus relevant published models ~0.45) of unobserved relationships such as identity fraud. Knowledge discovery uses the fused graph generated and applies the “GraphExtract” algorithm to create a set of subgraphs representing latent functional criminal groups, and a mesoscopic graph representing how this set of criminal groups are interconnected. Latent knowledge is generated from a range of metrics including the “Super-broker” metric and attitude prediction. The computational solution has been evaluated on a range of datasets that mimic an applied setting, demonstrating a scalable (tested on ~18 million node graphs) and performant (~33 hours runtime on a non-distributed platform) solution that successfully detects relevant latent functional criminal groups in around 90% of cases sampled and enables the contextual understanding of the broader criminal system through the mesoscopic graph and associated metadata. The augmented data assets generated provide a multi-perspective systems view of criminal activity that enable advanced informed decision making across the microscopic mesoscopic macroscopic spectrum

Operations Management

Global competition has caused fundamental changes in the competitive environment of the manufacturing and service industries. Firms should develop strategic objectives that, upon achievement, result in a competitive advantage in the market place. The forces of globalization on one hand and rapidly growing marketing opportunities overseas, especially in emerging economies on the other, have led to the expansion of operations on a global scale. The book aims to cover the main topics characterizing operations management including both strategic issues and practical applications. A global environmental business including both manufacturing and services is analyzed. The book contains original research and application chapters from different perspectives. It is enriched through the analyses of case studies