Industrial Machine Systems Risk Assessment: A Critical Review of Concepts and Methods

Reducing the risk of work-related death and injury to machine operators and maintenance personnel poses a continuing occupational safety challenge. The risk of injury from machinery in U.S. workplaces is high. Between 1992 and 2001, there were, on average, 520 fatalities per year involving machines and, on average, 3.8 cases per 10,000 workers of nonfatal caught-in-running-machine injuries involving lost workdays. A U.S. task group recently developed a technical reference guideline, ANSI B11 TR3, "A Guide to Estimate, Evaluate, & Reduce Risks Associated with Machine Tools," that is intended to bring machine tool risk assessment practice in the United States up to or above the level now required by the international standard, ISO 14121. The ANSI guideline emphasizes identifying tasks and hazards not previously considered, particularly those associated with maintenance; and it further emphasizes teamwork among line workers, engineers, and safety professionals. The value of this critical review of concepts and methods resides in (1) its linking current risk theory to machine system risk assessment and (2) its exploration of how various risk estimation tools translate into risk-informed decisions on industrial machine system design and use. The review was undertaken to set the stage for a field evaluation study on machine risk assessment among users of the ANSI B11 TR3 method.     

Modeling Microbial Growth Within Food Safety Risk Assessments

Risk estimates for food-borne infection will usually depend heavily on numbers of microorganisms present on the food at the time of consumption. As these data are seldom available directly, attention has turned to predictive microbiology as a means of inferring exposure at consumption. Codex guidelines recommend that microbiological risk assessment should explicitly consider the dynamics of microbiological growth, survival, and death in foods. This article describes predictive models and resources for modeling microbial growth in foods, and their utility and limitations in food safety risk assessment. We also aim to identify tools, data, and knowledge sources, and to provide an understanding of the microbial ecology of foods so that users can recognize model limits, avoid modeling unrealistic scenarios, and thus be able to appreciate the levels of confidence they can have in the outputs of predictive microbiology models. The microbial ecology of foods is complex. Developing reliable risk assessments involving microbial growth in foods will require the skills of both microbial ecologists and mathematical modelers. Simplifying assumptions will need to be made, but because of the potential for apparently small errors in growth rate to translate into very large errors in the estimate of risk, the validity of those assumptions should be carefully assessed. Quantitative estimates of absolute microbial risk within narrow confidence intervals do not yet appear to be possible. Nevertheless, the expression of microbial ecology knowledge in "predictive microbiology" models does allow decision support using the tools of risk assessment.     

Issues in Ecological Risk Assessment: The CRAM Perspective

In 1989, a Committee on Risk Assessment Methodology (CRAM) was convened by the National Research Council (NRC) to identify and investigate important scientific issues in risk assessment. One of the first issues considered by the committee was the development of a conceptual framework for ecological risk assessment, defined as "the characterization of the adverse ecological effects of environmental exposures to hazards imposed by human activities." Adverse ecological effects include all biological and nonbiological environmental changes that society perceives as undesirable. The committee's opinion was that a general framework is needed to define the relationship of ecological risk assessment to environmental management and to facilitate the development of uniform technical guidelines. The framework for human health risk assessment proposed by the NRC in 1983 was adopted as a starting point for discussion. CRAM concluded that, although ecological risk assessment and human health risk assessment differ substantially in terms of scientific disciplines and technical problems, the underlying decision process is the same for both. Therefore, CRAM recommended that the 1983 risk assessment framework be modified to accommodate both human health and ecological risk assessment. CRAM defined an integrated health/ ecological risk assessment framework consisting of the four components: Hazard Identification, Exposure Assessment, Exposure-Response Assessment, and Risk Characterization. CRAM further provided recommendations on the scope of issues to be addressed in ecological risk assessment, critical research needs, and mechanisms for providing more detailed guidance on the scientific content of ecological risk assessments.     

企业IT项目风险评估与规避策略研究

结合企业竞争性战略思想构建了一个企业IT项目风险评估与规避模型,建立了企业IT项目风险评估的指标体系,在对湖北省128家企业信息化项目与风险现状调查研究的基础上对风险因素进行了分类、测度和评估,得出了战略与风险的内在关系,并根据风险评估结果分析了企业战略执行的效果。最后,对高风险的企业IT项目提出了一套风险规避策略并进行应用。结果表明,计划与控制风险对各种企业IT项目执行的竞争性战略均有显著影响,采取不同战略的企业,影响其IT项目开发的风险各不相同,选择风险规避的策略与时机也存在差异。     

Risk Analysis for Invasive Species: General Framework and Research Needs

A joint workshop was convened by the Society for Risk Analysis Ecological Risk Assessment Specialty Group and the Ecological Society of America Theoretical Ecology Section to provide independent scientific input into the formulation of methods and processes for risk assessment of invasive species. In breakout sessions on (1) the effects of invasive species on human health, (2) effects on plants and animals, (3) risk analysis issues and research needs related to entry and establishment of invasive species, and (4) risk analysis issues and research needs related to the spread and impacts of invasive species, workshop participants discussed an overall approach to risk assessment for invasive species. Workshop participants agreed on the need for empirical research on areas in which data are lacking, including potential invasive species, native species and habitats that may be impacted by invasive species, important biological processes and phenomena such as dispersal, and pathways of entry and spread for invasive species. Participants agreed that theoretical ecology can inform the process of risk assessment for invasive species by providing guidelines and conceptual models, and can contribute to improved decision making by providing a firm biological basis for risk assessments.     

Quantile Uncertainty and Value‐at‐Risk Model Risk

This article develops a methodology for quantifying model risk in quantile risk estimates. The application of quantile estimates to risk assessment has become common practice in many disciplines, including hydrology, climate change, statistical process control, insurance and actuarial science, and the uncertainty surrounding these estimates has long been recognized. Our work is particularly important in finance, where quantile estimates (called Value‐at‐Risk) have been the cornerstone of banking risk management since the mid 1980s. A recent amendment to the Basel II Accord recommends additional market risk capital to cover all sources of “model risk” in the estimation of these quantiles. We provide a novel and elegant framework whereby quantile estimates are adjusted for model risk, relative to a benchmark which represents the state of knowledge of the authority that is responsible for model risk. A simulation experiment in which the degree of model risk is controlled illustrates how to quantify Value‐at‐Risk model risk and compute the required regulatory capital add‐on for banks. An empirical example based on real data shows how the methodology can be put into practice, using only two time series (daily Value‐at‐Risk and daily profit and loss) from a large bank. We conclude with a discussion of potential applications to nonfinancial risks.     

基于差分进化自动聚类的信用风险评价模型研究

随着风险评价的日益复杂化, 多维度、多时序等不规则的样本数据增加了评估的难度。本文建立信用风险评价的差分进化自动聚类模型, 并将其应用到我国上市公司信用风险评价中。该模型不要求事先知道分类的数据, 相反, 通过群体智能去寻找最优的分区。通过数据仿真, 并与遗传算法、决策树、BP神经网络模型进行信用风险评价的实证对比研究, 结果表明, 该模型能够非常准确的找到数据对应的分区, 大大提高了信用评估的准确性, 降低了风险成本, 对信用风险的管理和控制具有很高的利用价值。     

The NAS Risk Paradigm as a Medium for Communication

Many journalists, public interest groups and other recipients of risk assessment information are familiar with the National Academy of Sciences risk assessment paradigm. From time to time, paradigm concepts appear in news features or community group discussions on environmental issues. With knowledge of the paradigm common to scientists, journalists, and other interested parties, the paradigm is a potentially important medium for communication between risk scientists, journalists, and the public. Specifically, the paradigm offers widely-accepted organizing principles for presenting risk information, a common language for addressing a variety of issues and concepts, and a flexible analytical system that accommodates the diversity of scientific information and policy perspectives that characterize the risk assessment process. In addition, the paradigm outlines important relationships and distinctions between risk assessment and risk management. Informed and creative use of these features of the paradigm can guide and simplify interviews between journalists or community groups and their expert sources, clarify presentation of risk information, and promote collaboration between risk scientists, journalists, and others to assure complete, objective and fair comment on risk issues of interest to the public.     

A Discussion of Findings and Their Possible Implications from a Workshop on Bioterrorism Threat Assessment and Risk Management

In November 2001, the Monterey Institute of International Studies convened a workshop on bioterrorism threat assessment and risk management. Risk assessment practitioners from various disciplines, but without specialized knowledge of terrorism, were brought together with security and intelligence threat analysts to stimulate an exchange that could be useful to both communities. This article, prepared by a subset of the participants, comments on the workshop's findings and their implications and makes three recommendations, two short term (use of threat assessment methodologies and vulnerability analysis) and one long term (application of quantitative risk assessment and modeling), regarding the practical application of risk assessment methods to bioterrorism issues.     

Assessment of Catastrophic Risk Using Bayesian Network Constructed from Domain Knowledge and Spatial Data

Prediction of natural disasters and their consequences is difficult due to the uncertainties and complexity of multiple related factors. This article explores the use of domain knowledge and spatial data to construct a Bayesian network (BN) that facilitates the integration of multiple factors and quantification of uncertainties within a consistent system for assessment of catastrophic risk. A BN is chosen due to its advantages such as merging multiple source data and domain knowledge in a consistent system, learning from the data set, inference with missing data, and support of decision making. A key advantage of our methodology is the combination of domain knowledge and learning from the data to construct a robust network. To improve the assessment, we employ spatial data analysis and data mining to extend the training data set, select risk factors, and fine‐tune the network. Another major advantage of our methodology is the integration of an optimal discretizer, informative feature selector, learners, search strategies for local topologies, and Bayesian model averaging. These techniques all contribute to a robust prediction of risk probability of natural disasters. In the flood disaster's study, our methodology achieved a better probability of detection of high risk, a better precision, and a better ROC area compared with other methods, using both cross‐validation and prediction of catastrophic risk based on historic data. Our results suggest that BN is a good alternative for risk assessment and as a decision tool in the management of catastrophic risk.     

Variability and Uncertainty Meet Risk Management and Risk Communication

In the past decade, the use of probabilistic risk analysis techniques to quantitatively address variability and uncertainty in risks increased in popularity as recommended by the 1994 National Research Council that wrote Science and Judgment in Risk Assessment. Under the 1996 Food Quality Protection Act, for example, the U.S. EPA supported the development of tools that produce distributions of risk demonstrating the variability and/or uncertainty in the results. This paradigm shift away from the use of point estimates creates new challenges for risk managers, who now struggle with decisions about how to use distributions in decision making. The challenges for risk communication, however, have only been minimally explored. This presentation uses the case studies of variability in the risks of dying on the ground from a crashing airplane and from the deployment of motor vehicle airbags to demonstrate how better characterization of variability and uncertainty in the risk assessment lead to better risk communication. Analogies to food safety and environmental risks are also discussed. This presentation demonstrates that probabilistic risk assessment has an impact on both risk management and risk communication, and highlights remaining research issues associated with using improved sensitivity and uncertainty analyses in risk assessment.     

Foundational Issues in Risk Assessment and Risk Management

This is a perspective article on foundational issues in risk assessment and management. The aim is to discuss the needs, obstacles, and challenges for the establishment of a renewed, strong scientific foundation for risk assessment and risk management suited for the current and future technological challenges. The focus is on (i) reviewing and discussing the present situation and (ii) identifying how to best proceed in the future, to develop the risk discipline in the directions needed. The article provides some reflections on the interpretation and understanding of the concept of “foundations of risk assessment and risk management” and the challenges therein. One main recommendation is that different arenas and moments for discussion are needed to specifically address foundational issues in a way that embraces the many disciplinary communities involved (from social scientists to engineers, from behavioral scientists to statisticians, from health physicists to lawyers, etc.). One such opportunity is sought in the constitution of a novel specialty group of the Society of Risk Analysis.     

On the Risk Management and Risk Governance of Petroleum Operations in the Barents Sea Area

In this article, we discuss issues of risk management and risk governance with respect to petroleum operations in the Barents Sea area. We will focus on the decision problems related to whether or not to open the Barents Sea for petroleum activities in special vulnerable areas. We will explore to what extent the International Risk Governance Council risk governance framework provides valuable insights for and assistance to the decisionmaker and other stakeholders (including the industry and NGOs). The study covers issues related to risk assessment and appraisal, risk acceptance and tolerability, the use of the precautionary principle, risk perception, stakeholder involvement, risk communication, and risk management. The overall aim of the article is to point to areas where the risk governance could have been and can be improved for these and similar decision problems.     

Elusive Critical Elements of Transformative Risk Assessment Practice and Interpretation: Is Alternatives Analysis the Next Step?

This article argues that “game‐changing” approaches to risk analysis must focus on “democratizing” risk analysis in the same way that information technologies have democratized access to, and production of, knowledge. This argument is motivated by the author's reading of Goble and Bier's analysis, “Risk Assessment Can Be a Game‐Changing Information Technology—But Too Often It Isn't” (Risk Analysis, 2013; 33: 1942–1951), in which living risk assessments are shown to be “game changing” in probabilistic risk analysis. In this author's opinion, Goble and Bier's article focuses on living risk assessment's potential for transforming risk analysis from the perspective of risk professionals—yet, the game‐changing nature of information technologies has typically achieved a much broader reach. Specifically, information technologies change who has access to, and who can produce, information. From this perspective, the author argues that risk assessment is not a game‐changing technology in the same way as the printing press or the Internet because transformative information technologies reduce the cost of production of, and access to, privileged knowledge bases. The author argues that risk analysis does not reduce these costs. The author applies Goble and Bier's metaphor to the chemical risk analysis context, and in doing so proposes key features that transformative risk analysis technology should possess. The author also discusses the challenges and opportunities facing risk analysis in this context. These key features include: clarity in information structure and problem representation, economical information dissemination, increased transparency to nonspecialists, democratized manufacture and transmission of knowledge, and democratic ownership, control, and interpretation of knowledge. The chemical safety decision‐making context illustrates the impact of changing the way information is produced and accessed in the risk context. Ultimately, the author concludes that although new chemical safety regulations do transform access to risk information, they do not transform the costs of producing this information—rather, they change the bearer of these costs. The need for further risk assessment transformation continues to motivate new practical and theoretical developments in risk analysis and management.     

基于改进教学式方法的可解释信用风险评价模型构建

信用风险评价是金融机构风险防控的重要环节之一。近年来，基于机器学习的信用风险评价模型以其准确的预测效果受到越来越多的关注，但机器学习模型具有可解释性不强的弊端，导致投资者无法完全信任其预测结果。针对上述问题，本文提出了一种改进的教学式方法，利用机器学习模型指导生成一个兼顾准确性与可解释性的信用风险评价决策树模型，以辅助投资者决策。为提高决策树对机器学习模型中正确功能的学习能力，提出了基于Weight Synthetic Minority Over-sampling Technique（Weight-SMOTE）的伪数据集生成方法，以提高伪数据集中可信度高的功能所标记的伪样本比例；为实现所生成的决策树在准确性、可解释性以及其与机器学习模型一致性间的有效权衡，在决策树生成过程中提出了一种新的决策树剪枝方法；同时针对保真度评价指标的局限性，提出了真保真度评价指标，来有效的衡量决策树与机器学习模型正确功能的近似程度。最后使用3个真实信用风险评价数据集对改进的教学式方法进行验证，实验结果表明所提出方法能够生成准确且可解释的信用风险评价模型，以满足投资者的决策偏好与实际需求。     

Consideration of Background Exposures in the Management of Hazardous Waste Sites: A New Approach to Risk Assessment

The current approach to health risk assessment of toxic waste sites in the U.S. may lead to considerable expenditure of resources without any meaningful reduction in population exposure. Risk assessment methods used generally ignore background exposures and consider only incremental risk estimates for maximally exposed individuals. Such risk estimates do not address true public health risks to which background exposures also contribute. The purpose of this paper is to recommend a new approach to risk assessment and risk management concerning toxic waste sites. Under this new approach, which we have called public health risk assessment, chemical substances would be classified into a level of concern based on the potential health risks associated with typical national and regional background exposures. Site assessment would then be based on the level of concern for the particular pollutants involved and the potential contribution of site contaminants to typical background human exposures. While various problems can be foreseen with this approach, the key advantage is that resources would be allocated to reduce the most important sources of human exposure, and site remediation decisions could be simplified by focussing on exposure assessment rather than questionable risk extrapolations.     

Risk Assessment Can Be a Game‐Changing Information Technology—But Too Often It Isn't

The printing press was a game‐changing information technology. Risk assessment could be also. At present, risk assessments are commonly used as one‐time decision aids: they provide justification for a particular decision, and afterwards usually sit on a shelf. However, when viewed as information technologies, their potential uses are much broader. Risk assessments: (1) are repositories of structured information and a medium for communication; (2) embody evaluative structures for setting priorities; (3) can preserve information over time and permit asynchronous communication, thus encouraging learning and adaptation; and (4) explicitly address uncertain futures. Moreover, because of their “what‐if” capabilities, risk assessments can serve as a platform for constructive discussion among parties that hold different values. The evolution of risk assessment in the nuclear industry shows how such attributes have been used to lower core‐melt risks substantially through improved templates for maintenance and more effective coordination with regulators (although risk assessment has been less commonly used in improving emergency‐response capabilities). The end result of this evolution in the nuclear industry has been the development of “living” risk assessments that are updated more or less in real time to answer even routine operational questions. Similar but untapped opportunities abound for the use of living risk assessments to reduce risks in small operational decisions as well as large policy decisions in other areas of hazard management. They can also help improve understanding of and communication about risks, and future risk assessment and management. Realization of these opportunities will require significant changes in incentives and active promotion by the risk analytic community.     

A Bayesian Approach to Integrated Ecological and Human Health Risk Assessment for the South River,Virginia Mercury‐Contaminated Site

We conducted a regional‐scale integrated ecological and human health risk assessment by applying the relative risk model with Bayesian networks (BN‐RRM) to a case study of the South River, Virginia mercury‐contaminated site. Risk to four ecological services of the South River (human health, water quality, recreation, and the recreational fishery) was evaluated using a multiple stressor–multiple endpoint approach. These four ecological services were selected as endpoints based on stakeholder feedback and prioritized management goals for the river. The BN‐RRM approach allowed for the calculation of relative risk to 14 biotic, human health, recreation, and water quality endpoints from chemical and ecological stressors in five risk regions of the South River. Results indicated that water quality and the recreational fishery were the ecological services at highest risk in the South River. Human health risk for users of the South River was low relative to the risk to other endpoints. Risk to recreation in the South River was moderate with little spatial variability among the five risk regions. Sensitivity and uncertainty analysis identified stressors and other parameters that influence risk for each endpoint in each risk region. This research demonstrates a probabilistic approach to integrated ecological and human health risk assessment that considers the effects of chemical and ecological stressors across the landscape.     

Probabilistic Models for Risk Assessment

Recent concern with the potential for stray carbon fibers to damage electronic equipment and cause economic losses has led to the development of advanced risk-assessment methods. Risk assessment often requires the synthesis of risk profiles which represent the probability distribution of total annual losses due to a certain set of events or activities. A number of alternative probabilistic models are presented which the authors have used to develop such profiles. Examples are given of applications of these methods to assessment of risk due to conductive fibers released from aircraft or automobile fires. These assessments usually involve a two-stage approach: estimation of losses for several subclassifications of the overall process, and synthesis of the results into an aggregate risk profile. The methodology presented is capable of treating a wide variety of situations involving sequences of random physical events.     

Dimensions of Risk Perception for Financial and Health Risks

This study of 29 MBA students compares two models of risk perception for both financial and health risk stimuli. The first, inspired by Luce and Weber's Conjoint Expected Risk (CER) model, uses five dimensions: probability of gain, loss and status quo, and expected benefit and harm. The second, inspired by the Sovic et al. psychometric model, employs seven dimensions: voluntariness, dread, control, knowledge, catastrophic potential, novelty, and equity. The CER-type model provided a better fit for most subjects and stimuli. Adding the psychological risk dimensions from the Slovic et al. model explained only modestly more variance. Relationships between the dimensions of the two models are described and the construction of a hybrid model explored.