Integrating Risk and Resilience Approaches to Catastrophe Management in Engineering Systems

Recent natural and man‐made catastrophes, such as the Fukushima nuclear power plant, flooding caused by Hurricane Katrina, the Deepwater Horizon oil spill, the Haiti earthquake, and the mortgage derivatives crisis, have renewed interest in the concept of resilience, especially as it relates to complex systems vulnerable to multiple or cascading failures. Although the meaning of resilience is contested in different contexts, in general resilience is understood to mean the capacity to adapt to changing conditions without catastrophic loss of form or function. In the context of engineering systems, this has sometimes been interpreted as the probability that system conditions might exceed an irrevocable tipping point. However, we argue that this approach improperly conflates resilience and risk perspectives by expressing resilience exclusively in risk terms. In contrast, we describe resilience as an emergent property of what an engineering system does, rather than a static property the system has. Therefore, resilience cannot be measured at the systems scale solely from examination of component parts. Instead, resilience is better understood as the outcome of a recursive process that includes: sensing, anticipation, learning, and adaptation. In this approach, resilience analysis can be understood as differentiable from, but complementary to, risk analysis, with important implications for the adaptive management of complex, coupled engineering systems. Management of the 2011 flooding in the Mississippi River Basin is discussed as an example of the successes and challenges of resilience‐based management of complex natural systems that have been extensively altered by engineered structures.     

Assessing Engineering Resilience for Systems with Multiple Performance Measures

Recently, efforts to model and assess a system's resilience to disruptions due to environmental and adversarial threats have increased substantially. Researchers have investigated resilience in many disciplines, including sociology, psychology, computer networks, and engineering systems, to name a few. When assessing engineering system resilience, the resilience assessment typically considers a single performance measure, a disruption, a loss of performance, the time required to recover, or a combination of these elements. We define and use a resilient engineered system definition that separates system resilience into platform and mission resilience. Most complex systems have multiple performance measures; this research proposes using multiple objective decision analysis to assess system resilience for systems with multiple performance measures using two distinct methods. The first method quantifies platform resilience and includes resilience and other “ilities” directly in the value hierarchy, while the second method quantifies mission resilience and uses the “ilities” in the calculation of the expected mission performance for every performance measure in the value hierarchy. We illustrate the mission resilience method using a transportation systems‐of‐systems network with varying levels of resilience due to the level of connectivity and autonomy of the vehicles and platform resilience by using a notional military example. Our analysis found that it is necessary to quantify performance in context with specific mission(s) and scenario(s) under specific threat(s) and then use modeling and simulation to help determine the resilience of a system for a given set of conditions. The example demonstrates how incorporating system mission resilience can improve performance for some performance measures while negatively affecting others.     

A Factor Analysis Approach Toward Reconciling Community Vulnerability and Resilience Indices for Natural Hazards

The concepts of vulnerability and resilience help explain why natural hazards of similar type and magnitude can have disparate impacts on varying communities. Numerous frameworks have been developed to measure these concepts, but a clear and consistent method of comparing them is lacking. Here, we develop a data-driven approach for reconciling a popular class of frameworks known as vulnerability and resilience indices. In particular, we conduct an exploratory factor analysis on a comprehensive set of variables from established indices measuring community vulnerability and resilience at the U.S. county level. The resulting factor model suggests that 50 of the 130 analyzed variables effectively load onto five dimensions: wealth, poverty, agencies per capita, elderly populations, and non–English-speaking populations. Additionally, the factor structure establishes an objective and intuitive schema for relating the constituent elements of vulnerability and resilience indices, in turn affording researchers a flexible yet robust baseline for validating and expanding upon current approaches.     

Decision‐Making Analytics Using Plural Resilience Parameters for Adaptive Management of Complex Systems

It is critical for complex systems to effectively recover, adapt, and reorganize after system disruptions. Common approaches for evaluating system resilience typically study single measures of performance at one time, such as with a single resilience curve. However, multiple measures of performance are needed for complex systems that involve many components, functions, and noncommensurate valuations of performance. Hence, this article presents a framework for: (1) modeling resilience for complex systems with competing measures of performance, and (2) modeling decision making for investing in these systems using multiple stakeholder perspectives and multicriteria decision analysis. This resilience framework, which is described and demonstrated in this article via a real‐world case study, will be of interest to managers of complex systems, such as supply chains and large‐scale infrastructure networks.     

Workforce/Population,Economy, Infrastructure,Geography, Hierarchy,and Time (WEIGHT): Reflections on the Plural Dimensions of Disaster Resilience

The concept of resilience and its relevance to disaster risk management has increasingly gained attention in recent years. It is common for risk and resilience studies to model system recovery by analyzing a single or aggregated measure of performance, such as economic output or system functionality. However, the history of past disasters and recent risk literature suggest that a single-dimension view of relevant systems is not only insufficient, but can compromise the ability to manage risk for these systems. In this article, we explore how multiple dimensions influence the ability for complex systems to function and effectively recover after a disaster. In particular, we compile evidence from the many competing resilience perspectives to identify the most critical resilience dimensions across several academic disciplines, applications, and disaster events. The findings demonstrate the need for a conceptual framework that decomposes resilience into six primary dimensions: workforce/population, economy, infrastructure, geography, hierarchy, and time (WEIGHT). These dimensions are not typically addressed holistically in the literature; often they are either modeled independently or in piecemeal combinations. The current research is the first to provide a comprehensive discussion of each resilience dimension and discuss how these dimensions can be integrated into a cohesive framework, suggesting that no single dimension is sufficient for a holistic analysis of a disaster risk management. Through this article, we also aim to spark discussions among researchers and policymakers to develop a multicriteria decision framework for evaluating the efficacy of resilience strategies. Furthermore, the WEIGHT dimensions may also be used to motivate the generation of new approaches for data analytics of resilience-related knowledge bases.     

Resilience Analysis of a Remote Offshore Oil and Gas Facility for a Potential Hydrocarbon Release

Resilience is the capability of a system to adjust its functionality during a disturbance or perturbation. The present work attempts to quantify resilience as a function of reliability, vulnerability, and maintainability. The approach assesses proactive and reactive defense mechanisms along with operational factors to respond to unwanted disturbances and perturbation. This article employs a Bayesian network format to build a resilience model. The application of the model is tested on hydrocarbon‐release scenarios during an offloading operation in a remote and harsh environment. The model identifies requirements for robust recovery and adaptability during an unplanned scenario related to a hydrocarbon release. This study attempts to relate the resilience capacity of a system to the system's absorptive, adaptive, and restorative capacities. These factors influence predisaster and postdisaster strategies that can be mapped to enhance the resilience of the system.     

中国管理实践导向的管理科学与工程理论与方法

本文通过文献评述、专家调查和典型案例分析,试图解释中国管理实践导向的管理科学与工程学科学术研究的基本特点和发展趋势。结果表明,近年来基于中国数据、中国案例和中国经验的管理学术研究成果越来越多。这些研究考虑了中国国情、国家战略、制度和文化等因素,也反映出中国情景下管理科学与工程研究的复杂性和学科交叉性等特点。同时,针对“基于我国领跑工程的管理科学与工程研究”、“面向‘卡脖子’技术的管理科学与工程研究”两个领域的关键科学问题和未来发展进行了初步探讨。     

技术驱动的管理科学与工程研究

科技创新引领技术变革,加速变革的科技正在重塑世界政治、经济和社会发展的新格局、新形势。一系列新场景、新环境下的管理决策问题,如新一代移动通讯、人工智能、物联网、轨道交通与建筑工程、医疗工程、能源环境工程等,开启了管理科学与工程学科研究的新局面,并提出了全新的要求和挑战。本文通过系统梳理和总结相关文献和课题项目,阐述管理科学与工程领域的关键技术发展态势,并结合领域权威专家的问卷和访谈结果,立足新技术融合和新产业应用两个方面概括了技术驱动下管理科学与工程的主要研究方向。     

工程设计企业项目组织结构变革研究

根据工程设计企业的生产经营特点,通过实例分析,说明如何在工程设计企业中建立矩阵式组织结构,并就实施此种组织结构的优缺点进行分析,提出相应的改善措施和相关支撑体系。     

全球变局下的管理科学与工程研究

世界经济和科技格局变化是当前全球变局的重要驱动力,大国之间的竞争与合作将成为新时代大国关系的常态,同时全球视野下的人类发展也将面临前所未有的挑战。新形势下,以全球供应链的风险防范、国际贸易的摩擦、国际合作内容和形式的变化、海外重大工程建设以及突发公共卫生事件频发等为典型的全球治理问题对管理科学与工程研究提出了新的要求。本文在对文献及相关项目的研究现状进行总结的基础上,详细分析了我国在此方向的发展基础及优势,最后基于相关领域专家的问卷调查结果,阐述了该领域的主要研究方向。     

Review and Evaluation of the J100-10 Risk and Resilience Management Standard for Water and Wastewater Systems

Risk analysis standards are often employed to protect critical infrastructures, which are vital to a nation's security, economy, and safety of its citizens. We present an analysis framework for evaluating such standards and apply it to the J100-10 risk analysis standard for water and wastewater systems. In doing so, we identify gaps between practices recommended in the standard and the state of the art. While individual processes found within infrastructure risk analysis standards have been evaluated in the past, we present a foundational review and focus specifically on water systems. By highlighting both the conceptual shortcomings and practical limitations, we aim to prioritize the shortcomings needed to be addressed. Key findings from this study include (1) risk definitions fail to address notions of uncertainty, (2) the sole use of “worst reasonable case” assumptions can lead to mischaracterizations of risk, (3) analysis of risk and resilience at the threat-asset resolution ignores dependencies within the system, and (4) stakeholder values need to be assessed when balancing the tradeoffs between risk reduction and resilience enhancement.     

Agent‐Based Recovery Model for Seismic Resilience Evaluation of Electrified Communities

In this article, an agent‐based framework to quantify the seismic resilience of an electric power supply system (EPSS) and the community it serves is presented. Within the framework, the loss and restoration of the EPSS power generation and delivery capacity and of the power demand from the served community are used to assess the electric power deficit during the damage absorption and recovery processes. Damage to the components of the EPSS and of the community‐built environment is evaluated using the seismic fragility functions. The restoration of the community electric power demand is evaluated using the seismic recovery functions. However, the postearthquake EPSS recovery process is modeled using an agent‐based model with two agents, the EPSS Operator and the Community Administrator. The resilience of the EPSS–community system is quantified using direct, EPSS‐related, societal, and community‐related indicators. Parametric studies are carried out to quantify the influence of different seismic hazard scenarios, agent characteristics, and power dispatch strategies on the EPSS–community seismic resilience. The use of the agent‐based modeling framework enabled a rational formulation of the postearthquake recovery phase and highlighted the interaction between the EPSS and the community in the recovery process not quantified in resilience models developed to date. Furthermore, it shows that the resilience of different community sectors can be enhanced by different power dispatch strategies. The proposed agent‐based EPSS–community system resilience quantification framework can be used to develop better community and infrastructure system risk governance policies.     

Policy Learning for Flood Mitigation: A Longitudinal Assessment of the Community Rating System in Florida

Floods continue to inflict the most damage upon human communities among all natural hazards in the United States. Because localized flooding tends to be spatially repetitive over time, local decisionmakers often have an opportunity to learn from previous events and make proactive policy adjustments to reduce the adverse effects of a subsequent storm. Despite the importance of understanding the degree to which local jurisdictions learn from flood risks and under what circumstances, little if any empirical, longitudinal research has been conducted along these lines. This article addresses the research gap by examining the change in local flood mitigation policies in Florida from 1999 to 2005. We track 18 different mitigation activities organized into four series of activities under the Federal Emergency Management Agency's (FEMA) Community Rating System (CRS) for every local jurisdiction in Florida participating in the FEMA program on a yearly time step. We then identify the major factors contributing to policy changes based on CRS scores over the seven-year study period. Using multivariate statistical models to analyze both natural and social science data, we isolate the effects of several variables categorized into the following groups: hydrologic conditions, flood disaster history, socioeconomic and human capital controls. Results indicate that local jurisdictions do in fact learn from histories of flood risk and this process is expedited under specific conditions.     

管理科学与工程理论与方法突破若干重点前沿领域

管理科学与工程学科“十四五”战略规划课题组在国家自然科学基金委管理科学部的指导和资助下,通过调研和多轮专家评审归纳总结出“十四五”期间管理科学与工程学科层面的重点前沿领域。本文从运筹学和商务数据两个层面,汇报了亟需取得理论与方法突破的若干重点前沿领域。     

Market‐Implied Spread for Earthquake CAT Bonds: Financial Implications of Engineering Decisions

In the event of natural and man‐made disasters, owners of large‐scale infrastructure facilities (assets) need contingency plans to effectively restore the operations within the acceptable timescales. Traditionally, the insurance sector provides the coverage against potential losses. However, there are many problems associated with this traditional approach to risk transfer including counterparty risk and litigation. Recently, a number of innovative risk mitigation methods, termed alternative risk transfer (ART) methods, have been introduced to address these problems. One of the most important ART methods is catastrophe (CAT) bonds. The objective of this article is to develop an integrative model that links engineering design parameters with financial indicators including spread and bond rating. The developed framework is based on a four‐step structural loss model and transformed survival model to determine expected excess returns. We illustrate the framework for a seismically designed bridge using two unique CAT bond contracts. The results show a nonlinear relationship between engineering design parameters and market‐implied spread.     

管理科学与工程学科基金项目资助和SCI论文发表情况分析

系统地统计了2003～2008年国家自然科学基金委员会管理科学部管理科学与工程学科面上项目和青年项目受资助的总体情况,分析了各个子学科类别的资助状况和发表SCI论文情况,同时分析比较了国家"十一五"与"十五"期间的资助项目情况和发表SCI论文数量情况,找出其中存在的问题并对其原因进行了分析.最后,依据国家自然科学基金"十一五"发展战略,提出今后国家自然科学基金资助策略和建议.     

The implementation of digital technologies for operations management: a case study for manufacturing apps

Abstract

Manufacturing applications address business to business (B2B) with highly customised applications developed for specific requirements, offering highly specialised solution-oriented and service-based software components, systems, and digital tools that aim at a fast and accurate decision-making support system. The purpose of this paper is to describe the implementation of digital technologies for operations management using manufacturing or engineering apps (eApps), for product design and manufacturing processes. In particular, starting from the specific needs of two companies from mature European industries as automotive and food, this work depicts how this kind of solutions can support companies and improve their operations. In particular, related benefits and challenges faced for the full implementation of the developed tools are highlighted. Moreover a business model to exploit the manufacturing apps is also proposed. The business model proposed for the exploitation of the eApps supports the commercialisation of all the revenue streams offered by this rapidly growing sector taking into account the specific needs of the concerned stakeholders through a diversified value proposition.     

管理科学与工程学科“十四五”发展战略研究:学科界定与保障政策

我国管理科学与工程学科的发展是国家全局性科学技术发展战略的重要组成部分,能够在相关重大发展领域提供关键助力,因而需要在宏观层面上探索具有问题导向属性,并且能够充分反映时代特性和国家实际需求的管理科学与工程学科发展战略。鉴于此,以厘清该学科界定与研究意义为基础,结合相关调研结果,探索了我国管理科学与工程学科“十四五”发展战略的保障政策,以期为我国“十四五”规划多个关键战略方向的重大需求提供管理支撑和量化参考,同时助力国家自然科学基金委员会全面深化科学基金改革。     

Decision support tool for lean product and process development

Lean and concurrent engineering (CE) are widely acknowledged business process improvement strategies. These strategies can improve processes, reduce costs, and cut waste enabling organisations to remain competitive. Lean manufacturing offers an enterprise-wide methodology that improves reliability and flexibility while reducing lead-times and inventory carrying costs. Companies in manufacturing and service sectors are focusing on integrating lean manufacturing methodology with other applications, so that, all their systems and processes are aligned. This article proposes a CE framework based on application of information technology and object-oriented methodology for lean manufacturing. This approach expected to give manufacturing companies an extra edge in today's competitive market. A case study is presented in this article to demonstrate the effectiveness of CE framework in a machine tool manufacturing company. CE practice was adopted for new products, to align the systems and processes of the company. Product development lead-time was found to decrease by more than 50% compared to similar development projects carried out by the company. The need for rework was found to be negligible and the development cost was reduced considerably.     

综合集成研讨厅的研制

为处理经济系统这类的复杂巨系统及与其有关的决策问题, 国内学者以“系统论”的观 点, 于1990 年提出从定性到定量的综合集成法. 1992 年又进一步把该方法加以拓广, 形成综 合集成研讨厅. 在上述工作的基础上, 就工程化的研讨厅的设计与实施中的体系结构、关键问 题、工作方式与研讨流程等进行详细讨论; 并结合当前Internet 技术群的发展, 一方面把参加 研讨厅的成员的条件适当放宽与调整, 听取与收集广大群众的意见; 另一方面把研讨厅扩展为 分布式的, 将综合集成研讨厅建立在因特网的基础上, 讨论了基于Internet 技术群构建研讨厅 的技术路线与思路. 上述工作使得综合集成研讨厅有可能成为决策科学化、民主化的综合集成 决策支持系统.