M Elisabeth Pate-Cornell
Burton J. and DeeDee McMurtry Professor in the School of Engineering
Management Science and Engineering
Bio
Dr. Marie-Elisabeth Paté-Cornell is the Burt and Deedee McMurtry Professor in the School of Engineering, and a Professor and Founding Chair of the Department of Management Science and Engineering at Stanford University (2000-2011). Previously, she was the Professor and Chair of the Stanford Department of Industrial Engineering and Engineering Management and an Assistant Professor of Civil Engineering at MIT. Her specialty is engineering risk analysis with application to complex systems (seismic risk, space systems, medical procedures and devices, offshore oil platforms, cyber security, etc.). Her earlier research has focused on the optimization of warning systems and the explicit inclusion of human and organizational factors in the analysis of systems’ failure risks. Her more recent work is on the use of game theory in risk analysis with applications that have included counterterrorism and cyber security.
She is a member of the National Academy of Engineering where she chairs the section of Interdisciplinary Engineering and Special Fields, of the French Académie des Technologies, and of the NASA Advisory Council. She is co-chair of the committee of the National Academies (NASEM) on risk analysis methods for nuclear war and nuclear terrorism. She is a Fellow (and past president) of the Society for Risk Analysis and of the Institute for Operations Research and Management Science. She is the author of more than one hundred publications, with several best paper awards, and the co-editor of a book on Perspectives on Complex Global Problems (2016). She was a member of the Board of Advisors of the Naval Postgraduate School, which she chaired from 2004 to 2006, and of the Navy War College. Dr. Paté-Cornell was also a member of the President’s (Foreign) Intelligence Advisory Board (2001-2008), of the board of the Aerospace Corporation (2004-2013) of Draper Laboratory (2009-2016), and of InQtel (2006-2017). She was awarded the Frank Ramsey Medal of the Decision Analysis Society, the 2021 IEEE Ramo medal in Systems Engineering and Science, and the 2022 PICMET Award for Leadership in Technology Management. She is a Fellow (and past president) of the Society for Risk Analysis and of the Institute for Management Science and Operations Research, and a Distinguished Vising Scientist of the NASA Jet Propulsion Laboratory. She is the author of more than one hundred publications, for which she got several best paper awards, and the co-editor of a book on Perspectives on Complex Global Problems (2016). She holds a BS in Mathematics and Physics, Marseille (France), an Engineering degree (Applied Math/CS) from the Institut Polytechnique de Grenoble (France), an MS in Operations Research and a PhD in Engineering-Economic Systems, both from Stanford University.
She and her late husband, Dr. Allin Cornell had two children, Philip Cornell (born 1981) and Ariane Cornell (1984). She is married to Admiral James O. Ellis Jr. (US Navy, Ret.).
Administrative Appointments
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Elected Member, National Academy of Engineering (1995 - Present)
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Member, Board of Advisors of NPS Monterey (2012 - Present)
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Member, Intelligence Science and Technology Experts Group of the National Academies (2016 - Present)
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Member, NASA Advisory Council (2016 - Present)
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Member, Corporation of Draper Laboratory (2009 - 2016)
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Member, Stanford Advisory Board (2005 - 2010)
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Former Chair, Department of Management Science and Engineering (2000 - 2011)
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Vice-Chair, Senate (1998 - 1999)
Honors & Awards
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Recipient of the PICMET Award for Leadership in Technology Management, PICMET (2022)
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Recipient of the Ramo medal from IEEE in Systems Engineering and Science, IEEE (2021)
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Distinguished Visiting Scientist, Jet Propulsion Laboratory (2018)
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Best-paper award: “Asteroid Risk Assessment: A Probabilistic Approach.", Risk Analysis (paper with J. Reinhardt, X. Chen, W. Liu, P. Manchev) (2016)
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Best paper Award: “Probabilistic Warnings in National Security Crises: Pearl Harbor Revisited”, Decision Analysis, Vol. 13, No. pp. 1-25. by Blum D.M. and M.E. Paté-Cornell: (2016)
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Doctor of Business Administration, Honorary degree, University of Strathclyde, Glasgow, UK (2016)
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Ramsey Medal of the Decision Analysis Society, Institute for Operations Research and the Management Sciences (INFORMS). Decision Analysis Society (2010)
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Chevalier dans L’Ordre National du Merite, Ordre National du Mérite, France. (2008)
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Best-paper Award for the year, Military Operations Research Journal (2003)
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Member, French Académie des Technologies (2003)
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Chair, Decision Analysis Society of the Institute for Operations Research and the Management Sciences (2002-03)
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Award for Meritorious Civilian Service, U.S. Air Force (2002)
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Teaching Award for graduate teaching at the doctoral level, Stanford Department of Management Science and Engineering (June 2002)
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Distinguished Achievement Award, Society for Risk Analysis (2002)
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Fellow, Institute for Operations Research and the Management Sciences (INFORMS) (2002)
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Best paper of the year, IEEE Engineering Management Society (EMS) (2001)
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Conseiller, (Advisor), French Academy of Engineering (2001)
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Council member, National Academy of Engineering (2001)
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Visiting Professor, Ecole Normale Supérieure, Cachan, France (March 1996)
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President, Society for Risk Analysis (1995-1996)
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Fellow, Society for Risk Analysis (1995)
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Member, National Academy of Engineering (1995)
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Visiting Scholar, Electric Power Research Institute, Palo Alto, CA (January-March, 1995)
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Stanford Fellow, NASA-ASEE (1994)
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Decision Analysis Publication Award for the year, Decision Analysis Society of the Institute for Operations Research and the Management Sciences (1994)
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Finalist-Edelman Management Award, The Institute for Management Science (May 1993)
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Best Paper Award, American Nuclear Society (June 1990)
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Visiting Scholar, International Institute for Applied Systems Analysis (IIASA), Laxenburg, Austria (July-August 1979)
Boards, Advisory Committees, Professional Organizations
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Member, National Academy of Engineering (1995 - Present)
Professional Education
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PhD, Stanford University (1978)
2024-25 Courses
- Engineering Risk Analysis
MS&E 250A (Win) - Project Course in Engineering Risk Analysis
MS&E 250B (Spr) - Senior Project
MS&E 108 (Win) -
Independent Studies (1)
- Directed Reading and Research
MS&E 408 (Aut, Win, Spr, Sum)
- Directed Reading and Research
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Prior Year Courses
2023-24 Courses
- Engineering Risk Analysis
MS&E 250A (Win) - Project Course in Engineering Risk Analysis
MS&E 250B (Spr)
2022-23 Courses
- Engineering Risk Analysis
MS&E 250A (Win) - Project Course in Engineering Risk Analysis
MS&E 250B (Spr) - Senior Project
MS&E 108 (Win)
2021-22 Courses
- Engineering Risk Analysis
MS&E 250A (Win) - Project Course in Engineering Risk Analysis
MS&E 250B (Spr)
- Engineering Risk Analysis
Stanford Advisees
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Doctoral Dissertation Advisor (AC)
Jarrod Shingleton -
Master's Program Advisor
Preston Forst, Pinger Lyu, Lily Raaka, Sue Shen, Bradley Strauss, Anchen Yang -
Doctoral (Program)
Khang Do, Victoria Li
All Publications
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UNCERTAINTIES, INTELLIGENCE, AND RISK MANAGEMENT: A FEW OBSERVATIONS AND RECOMMENDATIONS ON MEASURING AND MANAGING RISK
STANFORD JOURNAL OF INTERNATIONAL LAW
2015; 51 (1): 53-67
View details for Web of Science ID 000352465200003
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Improving Risk Management: From Lame Excuses to Principled Practice
RISK ANALYSIS
2014; 34 (7): 1228-1239
Abstract
The three classic pillars of risk analysis are risk assessment (how big is the risk and how sure can we be?), risk management (what shall we do about it?), and risk communication (what shall we say about it, to whom, when, and how?). We propose two complements as important parts of these three bases: risk attribution (who or what addressable conditions actually caused an accident or loss?) and learning from experience about risk reduction (what works, and how well?). Failures in complex systems usually evoke blame, often with insufficient attention to root causes of failure, including some aspects of the situation, design decisions, or social norms and culture. Focusing on blame, however, can inhibit effective learning, instead eliciting excuses to deflect attention and perceived culpability. Productive understanding of what went wrong, and how to do better, thus requires moving past recrimination and excuses. This article identifies common blame-shifting "lame excuses" for poor risk management. These generally contribute little to effective improvements and may leave real risks and preventable causes unaddressed. We propose principles from risk and decision sciences and organizational design to improve results. These start with organizational leadership. More specifically, they include: deliberate testing and learning-especially from near-misses and accident precursors; careful causal analysis of accidents; risk quantification; candid expression of uncertainties about costs and benefits of risk-reduction options; optimization of tradeoffs between gathering additional information and immediate action; promotion of safety culture; and mindful allocation of people, responsibilities, and resources to reduce risks. We propose that these principles provide sound foundations for improving successful risk management.
View details for DOI 10.1111/risa.12241
View details for Web of Science ID 000340570900007
View details for PubMedID 24989791
- Project Fox: near-earth objects impact risk 2013
- On risk analysis models for engineered systems using Bayesian methods 2013
- Counter-terrorism modeling: anticipating an attack 2013
- Recalibrating risks: reactions to Three-Mile Island, Chernobyl and Fukushima 2013
- On black swans and perfect storms 2013
- Decisions, risks, and games involving intelligent actors 2013
- An Engineering Risk Analysis perspective on “black swans” and “perfect storms: taking avoiding and managing the risks of rare events” 2013
- The illusion of classical validation for counter-terrorism models: verification and justification of variables and data 2013
- The tiger under the bed 2013
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On "Black Swans" and "Perfect Storms": Risk Analysis and Management When Statistics Are Not Enough
RISK ANALYSIS
2012; 32 (11): 1823-1833
Abstract
Two images, "black swans" and "perfect storms," have struck the public's imagination and are used--at times indiscriminately--to describe the unthinkable or the extremely unlikely. These metaphors have been used as excuses to wait for an accident to happen before taking risk management measures, both in industry and government. These two images represent two distinct types of uncertainties (epistemic and aleatory). Existing statistics are often insufficient to support risk management because the sample may be too small and the system may have changed. Rationality as defined by the von Neumann axioms leads to a combination of both types of uncertainties into a single probability measure--Bayesian probability--and accounts only for risk aversion. Yet, the decisionmaker may also want to be ambiguity averse. This article presents an engineering risk analysis perspective on the problem, using all available information in support of proactive risk management decisions and considering both types of uncertainty. These measures involve monitoring of signals, precursors, and near-misses, as well as reinforcement of the system and a thoughtful response strategy. It also involves careful examination of organizational factors such as the incentive system, which shape human performance and affect the risk of errors. In all cases, including rare events, risk quantification does not allow "prediction" of accidents and catastrophes. Instead, it is meant to support effective risk management rather than simply reacting to the latest events and headlines.
View details for DOI 10.1111/j.1539-6924.2011.01787.x
View details for Web of Science ID 000311300500002
View details for PubMedID 22385051
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Games, Risks, and Analytics: Several Illustrative Cases Involving National Security and Management Situations
DECISION ANALYSIS
2012; 9 (2): 186-203
View details for DOI 10.1287/deca.1120.0241
View details for Web of Science ID 000305308400012
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Shortcuts in Complex Engineering Systems: A Principal-Agent Approach to Risk Management
RISK ANALYSIS
2012; 32 (5): 836-854
Abstract
In this article, we examine the effects of shortcuts in the development of engineered systems through a principal-agent model. We find that occurrences of illicit shortcuts are closely related to the incentive structure and to the level of effort that the agent is willing to expend from the beginning of the project to remain on schedule. Using a probabilistic risk analysis to determine the risks of system failure from these shortcuts, we show how a principal can choose optimal settings (payments, penalties, and inspections) that can deter an agent from cutting corners and maximize the principal's value through increased agent effort. We analyze the problem for an agent with limited liability. We consider first the case where he is risk neutral; we then include the case where he is risk averse.
View details for DOI 10.1111/j.1539-6924.2011.01736.x
View details for Web of Science ID 000303438200011
View details for PubMedID 22212012
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Counterinsurgency: A Utility-Based Analysis of Different Strategies
MILITARY OPERATIONS RESEARCH
2012; 17 (4): 5-23
View details for DOI 10.5711/1082598317405
View details for Web of Science ID 000314203700001
- Risk and Decision Analysis: Academic Experience and Current Research Epstein Institute invited seminar series, University of Southern California. Los Angeles, CA. 2012
- Some remarks on uncertainty, model complexity and the risks of no risk analysis 2012
- Tsunami design criteria for the Fukushima Dai-ichi nuclear power plant: an inquiry driven by curiosity 2012
- Risk Management in Game Situations: Principal-agent and adversarial examples 2012
- The risks of no risk analysis: The choice of a tsunami design criterion for the Fukushima-Daiichi nuclear power plant 2012
- Solar storms: Impact on cascading power grid failures A simple model and illustration 2012
- Effects of sever space weather on cascading power failure: an illustrative model and policy implications 2012
- Systems, risks and games analysis 2012
- Risk analysis in the systems engineering context a few examples and comments on Fukushima 2012
- A probabilistic framework for tactical warnings: inferring localized drug violence 2012
- Risk Management in Game Situations: Principal-agent, Adversarial and Cooperation Examples MIT, Engineering Systems Division Lecture Series, Cambridge MA. 2012
- Insolvencies in the American Property and Casualty Insurance Industry: a System's Approach Risk and Decision Analysis 2012; 3: 3-18
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Analysis of National Strategies to Counter a Country's Nuclear Weapons Program
DECISION ANALYSIS
2011; 8 (1): 30-45
View details for DOI 10.1287/deca.1110.0198
View details for Web of Science ID 000288412500004
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Probabilistic Analysis of a Country's Program to Acquire Nuclear Weapons
MILITARY OPERATIONS RESEARCH
2011; 16 (1): 5-20
View details for DOI 10.5711/108259831615
View details for Web of Science ID 000290929300001
- Probabilistic Simulation of Multi-stage Decisions for Operation of a Fractionated Satellite Mission 2011
- Report to the Department of Interior: Macondo Well-Deepwater Horizon Blowout: Lessons for Improving Offshore Drilling Safety (Committee member; co-author) National Academy of Engineering National Academy Press, Washington D.C.. 2011: 1
- Are engineering companies too risk-averse? 2011
- Improving the service industry: a Stanford perspective 2011
- Probabilistic Analysis of a Country’s Program to Acquire Nuclear Weapons Military Operations Research 2011; 16 (1): 5-16
- Space Weather: Impact on cascading power grid failures. A simple model and illustration 2011
- Risk Analysis: An Alternative to the “Stuff-happens” Philosophy (or words to that effect) 2011
- From Piper Alpha to Deepwater Horizon: some observations of risk management and regulation in the offshore oil industry 2011
- Games, Risks and National Security 2011
- Dynamics in Early Warning and Crisis Management with David Blum, Homeland Security and Advances in Risk Analysis 2011
- Safety Analysis of the Advanced Airspace Concept using Monte Carlo Simulation 2010
- Risk analysis when intelligent actors are involved (illustrated by the cases of the failure risks of the tiles of the space shuttle and patient risks in anesthesia), Invited Lecture Series in Systems Engineering, National University of Singapore (NUS). 2010
- Risks and games: three models and illustrations 2010
- Fires on Offshore platforms: a risk analysis perspective on Piper Alpha 2010
- Taking, avoiding and managing risks: An engineering perspective, including experts, games, and a few lessons learned 2010
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Stage-Gate Process for the Development of Medical Devices
JOURNAL OF MEDICAL DEVICES-TRANSACTIONS OF THE ASME
2009; 3 (2)
View details for DOI 10.1115/1.3148836
View details for Web of Science ID 000283763700004
- Greener grass and faster lanes On the roots of the brain drain from Europe to the US, Atomium Culture, European Parliament, Brussels, Belgium. 2009
- Probabilistic Risk Assessment The Wiley Encyclopedia of Operations Research and Management Science edited by Cochran, James, J. Wiley Pub. 2009: 1
- Risks and Games: Intelligent Actors and Fallible Systems 2009
- Failure Risks in the Insurance Industry: A Quantitative Systems Analysis The Risk Management and Insurance Review 2009; 12 (2): 199-212
- Risks and Games: Intelligent Actors and Fallible Systems 2009
- Risks and games: intelligent actors and fallible systems 2009
- The Iterative Nature of Medical Device Design 2009
- Accident Precursors The Wiley Encyclopedia of Operations Research and Management Science edited by Cochran, James, J. Wiley Pub. 2009: 1
- Expert opinions in risk analysis 2009
- Engineering Risk Analysis: Lessons Learned 2009
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Bayesian assessment of overtriage and undertriage at a level I trauma centre
PHILOSOPHICAL TRANSACTIONS OF THE ROYAL SOCIETY A-MATHEMATICAL PHYSICAL AND ENGINEERING SCIENCES
2008; 366 (1874): 2265-2277
Abstract
We analysed the trauma triage system at a specific level I trauma centre to assess rates of over- and undertriage and to support recommendations for system improvements. The triage process is designed to estimate the severity of patient injury and allocate resources accordingly, with potential errors of overestimation (overtriage) consuming excess resources and underestimation (undertriage) potentially leading to medical errors.We first modelled the overall trauma system using risk analysis methods to understand interdependencies among the actions of the participants. We interviewed six experienced trauma surgeons to obtain their expert opinion of the over- and undertriage rates occurring in the trauma centre. We then assessed actual over- and undertriage rates in a random sample of 86 trauma cases collected over a six-week period at the same centre. We employed Bayesian analysis to quantitatively combine the data with the prior probabilities derived from expert opinion in order to obtain posterior distributions. The results were estimates of overtriage and undertriage in 16.1 and 4.9% of patients, respectively. This Bayesian approach, which provides a quantitative assessment of the error rates using both case data and expert opinion, provides a rational means of obtaining a best estimate of the system's performance. The overall approach that we describe in this paper can be employed more widely to analyse complex health care delivery systems, with the objective of reduced errors, patient risk and excess costs.
View details for DOI 10.1098/rsta.2008.0036
View details for Web of Science ID 000256067000003
View details for PubMedID 18407901
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Early technology assessment of new medical devices
INTERNATIONAL JOURNAL OF TECHNOLOGY ASSESSMENT IN HEALTH CARE
2008; 24 (1): 36-44
Abstract
In the United States, medical devices represent an eighty-billion dollar a year market. The U.S. Food and Drug Administration rejects a significant number of applications of devices that reach the investigational stage. The prospects of improving patient condition, as well as firms' profits, are thus substantial, but fraught with uncertainties at the time when investments and design decisions are made. This study presents a quantitative model focused on the risk aspects of early technology assessment, designed to support the decisions of medical device firms in the investment and development stages.The model is based on the engineering risk analysis method involving systems analysis and probability. It assumes use of all evidence available (both direct and indirect) and integrates the information through a linear formula of aggregation of probability distributions. The model is illustrated by a schematic version of the case of the AtrialShaper, a device for the reduction of stroke risk that is currently in the preprototype stage.The results of the modeling provide a more complete description of the evidence base available to support early-stage decisions, thus allowing comparison of alternative designs and management alternatives.The model presented here provides early-stage decision-support to industry, but also benefits regulators and payers in their later assessment of new devices and associated procedures.
View details for DOI 10.1017/S0266462307080051
View details for Web of Science ID 000252748100005
View details for PubMedID 18218167
- Risk Analysis and Game Theory: Three Management and Policy Examples 2008
- Assessment of Overtriage and Undertriage at a Level I Trauma Centre Philosophical Transactions of the Royal Society: Mathematical, Physical and Engineering Sciences 2008: 2265-2277
- Assessing Risks of Terrorist Threats 2008
- Some Progress in the Analysis of Intelligence Information: Where We Are and Possible Improvements 2008
- Engineering Risk Analysis IEEE Technology Management Council of Silicon Valley, Sunnyvale CA. 2008
- Risk analysis when several decision makers are involved: policy and management examples FUR XIII, Barcelona, Spain. 2008
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Probabilistic Risk Analysis Versus Decision Analysis: Similarities, Differences and Illustrations
11th International Conference on the Foundations and Applications of Utility, Risk and Decision Theory
SPRINGER-VERLAG BERLIN. 2007: 223–242
View details for Web of Science ID 000269138700012
- Medical Device Development Models 2007
- Rationality and Imagination: The Engineering Risk Analysis Method and Some Applications Advances in Decision Analysis, Edward edited by Miles, E., Winterfeldt, v. Cambridge University Press. 2007: 1
- Engineering Risk Analysis: What we do, how we do it, and why do we do it? IPER 330, Stanford University 2007
- Probabilistic Risk Analysis vs. Decision Analysis: Similarities, Differences and Illustrations Uncertainty and Risk: Mental, Formal and Experimental Representations edited by Abdellaoui, M., Luce, R., D., Machina, M. Springer Pub.. 2007: 223–242
- Review of US Medical Device Regulation Journal of Medical Devices 2007; 1: 283-292
- Evidence-based decisions: who says no? provided that the evidence is right 2007
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Engineering risk analysis of a hospital oxygen supply system
MEDICAL DECISION MAKING
2006; 26 (2): 162-172
Abstract
Reports from the Food and Drug Administration (FDA) and the Joint Commission on Accreditation of Healthcare Organizations (JCAHO) have emphasized the potential for injury to patients caused by failures in oxygen supply systems. This article presents a model of patient risk related to the process of supplying oxygen at a single university hospital. One of the goals of the article is to illustrate how probabilistic risk analysis (PRA) can be used by hospitals to assess and mitigate risk and, therefore, to meet JCAHO requirements. PRA techniques are useful to 1) model the reliability of a complex system and 2) assess the cost-effectiveness of different risk mitigation measures. The authors focus on the risk estimation step, describing in detail their modeling of the oxygen supply system and analysis of the results. For the hospital that the authors study (20,000 admissions yearly), the total expected number of fatalities from oxygen system failure is 44 over a 30-year time horizon. The greatest contribution to the risk (94% of the expected number of fatalities) comes from problems that involve the supply network (e.g., damage to structure and poisoning) as opposed to incidents that occur inside patient rooms. Although the threat to patient safety is not dramatic, health care organizations should be concerned about potential failures of their oxygen system because improving this system could avoid low-probability, high-consequence failures at a low cost.
View details for DOI 10.1177/0272989X06286477
View details for Web of Science ID 000236557400008
View details for PubMedID 16525170
- Engineering Risk Analysis: Influence of Human and Organizational Factors 2006
- The Respective Roles of Risk and Decision Analyses in Decision Support Decision Analysis 2006; 3 (4): 220-232
- Global Financial Analysis (GFA): a Strategic Model of Bankruptcies in the Insurance Industry 2006
- Managing Shortcuts in Engineering Systems and Their Safety Effects: A Management Science Perspective 2006
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Probability of infancy problems for space launch vehicles
RELIABILITY ENGINEERING & SYSTEM SAFETY
2005; 87 (3): 303-314
View details for DOI 10.1016/j.ress.2004.06.001
View details for Web of Science ID 000226311400002
- Including Technical and Security Risks in the Management of Information Systems: A Programmatic Risk Management Model Systems Engineering 2005; 8 (1): 15-28
- A Bayesian Approach to Iraq's Nuclear Program Intelligence Analysis: A Hypothetical Illustration 2005
- Engineering Risk Analysis for Pro-Active Risk Management 2005
- Optimal Use of Budget Reserves to Minimize Technical and Management Failure Risks During Complex Project Development IEEE Transactions on Engineering Management 2005; 52 (3)
- Prospective Evaluation of Management Alternatives in Policy Making: Anesthesia Patient Risk Example 2005
- Probabilistic Modeling of Terrorist Threats 2005
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On the limitations of redundancies in the improvement of system reliability
RISK ANALYSIS
2004; 24 (6): 1423-1436
Abstract
Some program managers share a common belief that adding a redundant component to a system reduces the probability of failure by half. This is true only if the failures of the redundant components are independent events, which is rarely the case. For example, the redundant components may be subjected to the same external loads. There is, however, in general a decrease in the failure probability of the system. Nonetheless, the redundant element comes at a cost, even if it is less than that of developing the first one when both are based on the same design. Identical parts save the most in terms of design costs, but are subjected to common failure modes from possible design errors that limit the effectiveness of the redundancy. In the development of critical systems, managers thus need to decide if the costs of a parallel system are justified by the increase in the system's reliability. NASA, for example, has used redundant spacecraft to increase the chances of mission success, which worked well in the cases of the Viking and Voyager missions. These two successes, however, do not guarantee future ones. We present here a risk analysis framework accounting for dependencies to support the decision to launch at the same time a twin mission of identical spacecraft, given incremental costs and risk-reduction benefits of the second one. We illustrate this analytical approach with the case of the Mars Exploration Rovers launched by NASA in 2003, for which we had performed this assessment in 2001.
View details for Web of Science ID 000226235800003
View details for PubMedID 15660601
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Dynamic modeling of the tradeoff between productivity and safety in critical engineering systems
RELIABILITY ENGINEERING & SYSTEM SAFETY
2004; 86 (3): 269-284
View details for DOI 10.1016/j.ress.2004.02.003
View details for Web of Science ID 000224648300008
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Managing technology development for safety-critical systems
IEEE TRANSACTIONS ON ENGINEERING MANAGEMENT
2004; 51 (4): 451-461
View details for DOI 10.1109/TEM.2004.835086
View details for Web of Science ID 000224657600011
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Organizational warning systems: A probabilistic approach to optimal design
IEEE TRANSACTIONS ON ENGINEERING MANAGEMENT
2004; 51 (2): 183-196
View details for DOI 10.1109/TEM.2003.822460
View details for Web of Science ID 000221046900007
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Bayesian analysis of launch vehicle success rates
JOURNAL OF SPACECRAFT AND ROCKETS
2004; 41 (1): 93-102
View details for Web of Science ID 000189156900011
- Risks of Terrorist Attacks: Probabilistic Assessment and Use of Intelligence Information 2004
- Risk Analysis vs. Decision Analysis: Methods and Applications 2004
- On signals, response, and risk mitigation: a probabilistic approach to the detection and analysis of precursors In Accident Precursor Analysis and Management, Proceedings of the National Academy of Engineering Workshop on Precursors National Academy Press, Washington D.C.. 2004: 45–59
- Risk Analysis for Monitoring and Diagnosis of Problems in the Automotive Industry CONVERGENCE 2004 (auto. industry), Detroit, MI. 2004
- A Framework for Probabilistic Assessment of New Medical Technologies 2004
- The role of probabilistic risk analysis and decision analysis in the development process of large complex systems 2004
- Risk Costs for New Dams: Economic Analysis and Effects of Monitoring The Economics of Natural Hazards edited by Kunreuther, H., Rose, A. The International Library of Critical Writings in Economics, An Elgar Reference Collection, Northampton, MA.. 2004: 461–470
- Organizational Warnings and System Safety: A Probabilistic Analysis IEEE Transactions on Engineering Management 2004; 51 (2): 183-196
- Engineering Risk Analysis and Management Boeing Engineering Leadership Lecture Series, Boeing, Saint Louis, Missouri. 2004
- Engineering Systems and systems engineering in the MS&E department at Stanford University 2004
- Optimal Redundancy for Series Systems: a Value-maximizing Approach 2004
- A ProbabilisticAnalysis of the “Infancy Problem” of Space Launch Vehicles 2004
- Analyzing Losses from Hazard Exposures: a Conservative Probabilistic Estimate Using Supply Chain Risk Simulation 2004
- On Signals, Response, and Risk Mitigation: a Probabilistic Approach to Precursors’ Detection and Analysis Accident Precursor Analysis and Management,: Reducing Technological Risk Through Diligence, Proceedings of the NAE workshop on Precursors, Phimister National Academy Press. 2004: 45–59
- Risk Analysis for Monitoring and Diagnosis of Problems in the Automotive Industry 2004
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Risk chair for concurrent design engineering: Satellite swarm illustration
JOURNAL OF SPACECRAFT AND ROCKETS
2004; 41 (1): 51-59
View details for Web of Science ID 000189156900006
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Modeling the effects of dispersion of design teams on system failure risk
JOURNAL OF SPACECRAFT AND ROCKETS
2004; 41 (1): 60-68
View details for Web of Science ID 000189156900007
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Programmatic risk analysis for critical engineering systems under tight resource constraints
OPERATIONS RESEARCH
2003; 51 (3): 354-370
View details for Web of Science ID 000183367600002
- On the tiles of the space shuttle: a risk analysis in 1990 and the Columbia accident of 2003 2003
- Assessment and Ranking of Terrorist Threat: a Risk-Analytic Approach Marine Board of the NRC, Washington D.C. 2003
- Threat Assessment and Prioritization: a Risk Analysis Approach 2003
- A Probabilistic Approach to Precursors' Detection and Analysis in Risk Management 2003
- On the tiles of the Space Shuttle: estimating the risks and following up 2003
- Bayesian Analysis of Launch Vehicle Reliability 2003
- Terrorism Threat Assessment and Prioritization: A Risk Analysis 2003
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Component choice for managing risk in engineered systems with generalized risk/cost functions
RELIABILITY ENGINEERING & SYSTEM SAFETY
2002; 78 (3): 227-238
View details for Web of Science ID 000179993500002
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Risk and uncertainty analysis in government safety decisions
RISK ANALYSIS
2002; 22 (3): 633-646
Abstract
Probabilistic risk analysis (PRA) can be an effective tool to assess risks and uncertainties and to set priorities among safety policy options. Based on systems analysis and Bayesian probability, PRA has been applied to a wide range of cases, three of which are briefly presented here: the maintenance of the tiles of the space shuttle, the management of patient risk in anesthesia, and the choice of seismic provisions of building codes for the San Francisco Bay Area. In the quantification of a risk, a number of problems arise in the public sector where multiple stakeholders are involved. In this article, I describe different approaches to the treatments of uncertainties in risk analysis, their implications for risk ranking, and the role of risk analysis results in the context of a safety decision process. I also discuss the implications of adopting conservative hypotheses before proceeding to what is, in essence, a conditional uncertainty analysis, and I explore some implications of different levels of "conservatism" for the ranking of risk mitigation measures.
View details for Web of Science ID 000176547800023
View details for PubMedID 12088238
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Fusion of intelligence information: A Bayesian approach
RISK ANALYSIS
2002; 22 (3): 445-454
Abstract
The attack that occurred on September 11, 2001 was, in the end, the result of a failure to detect and prevent the terrorist operations that hit the United States. The U.S. government thus faces at this time the daunting tasks of first, drastically increasing its ability to obtain and interpret different types of signals of impending terrorist attacks with sufficient lead time and accuracy, and second, improving its ability to react effectively. One of the main challenges is the fusion of information, from different sources (U.S. or foreign), and of different types (electronic signals, human intelligence. etc.). Fusion thus involves two very distinct and separate issues: communications, i.e., ensuring that the different U.S. and foreign intelligence agencies communicate all relevant and accurate information in a timely fashion and, perhaps more difficult, merging the content of signals, some "sharp" and some "fuzzy," some dependent and some independent into useful information. The focus of this article is on the latter issue, and on the use of the results. In this article, I present a classic probabilistic Bayesian model sometimes used in engineering risk analysis, which can be helpful in the fusion of information because it allows computation of the posterior probability of an event given its prior probability (before the signal is observed) and the quality of the signal characterized by the probabilities of false positive and false negative. Experience suggests that the nature of these errors has been sometimes misunderstood; therefore, I discuss the validity of several possible definitions.
View details for Web of Science ID 000176547800009
View details for PubMedID 12088224
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Finding and fixing systems weaknesses: Probabilistic methods and applications of engineering risk analysis
RISK ANALYSIS
2002; 22 (2): 319-334
Abstract
Methods of engineering risk analysis are based on a functional analysis of systems and on the probabilities (generally Bayesian) of the events and random variables that affect their performances. These methods allow identification of a system's failure modes, computation of its probability of failure or performance deterioration per time unit or operation, and of the contribution of each component to the probabilities and consequences of failures. The model has been extended to include the human decisions and actions that affect components' performances, and the management factors that affect behaviors and can thus be root causes of system failures. By computing the risk with and without proposed measures, one can then set priorities among different risk management options under resource constraints. In this article, I present briefly the engineering risk analysis method, then several illustrations of risk computations that can be used to identify a system's weaknesses and the most cost-effective way to fix them. The first example concerns the heat shield of the space shuttle orbiter and shows the relative risk contribution of the tiles in different areas of the orbiter's surface. The second application is to patient risk in anesthesia and demonstrates how the engineering risk analysis method can be used in the medical domain to rank the benefits of risk mitigation measures, in that case, mostly organizational. The third application is a model of seismic risk analysis and mitigation, with application to the San Francisco Bay area for the assessment of the costs and benefits of different seismic provisions of building codes. In all three cases, some aspects of the results were not intuitively obvious. The probabilistic risk analysis (PRA) method allowed identifying system weaknesses and the most cost-effective way to fix them.
View details for Web of Science ID 000175629400011
View details for PubMedID 12022679
- Assessment of the Effects of Biases on the Performance of a Portfolio of Missions International Journal of Aerospace Management 2002; 1 (4): 339-351
- Probabilistic Modeling of Terrorist Threats: a Systems Analysis Approach to Setting Priorities Among Countermeasures Military Operations Research 2002; 7 (4)
- Optimization of System and Compoennt Reinforcement with Discrete Risk/Cost Functions 2002
- Assessment of the Benefits of Anesthesia Patient Risk Reduction Measures: a Systems Analysis Approach Based on Probability Handbook of Operations Research/Management Science Applications in Health Care edited by Pierskalla, W., Sainfort, F., Brandeau, M. Kluwer Pub. 2002: 1
- Quantitative Risk Analysis: Why, when, and how? 2002
- Principles of Quantitative Risk Analysis 2002
- An Overarching Systems (Risk) Analysis Model for Threat Assessment. 2002
- Early Technology Assessment of New Medical Devices and Procedures: A Systems Analysis Approach Using Probabilistic Modeling 2002
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Probabilistic risk analysis for the NASA space shuttle: a brief history and current work
RELIABILITY ENGINEERING & SYSTEM SAFETY
2001; 74 (3): 345-352
View details for Web of Science ID 000172123000013
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Success factors and future challenges in the management of faster-better-cheaper projects: Lessons learned from NASA
IEEE TRANSACTIONS ON ENGINEERING MANAGEMENT
2001; 48 (1): 25-35
View details for Web of Science ID 000167742900002
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Risks of particle hits during space walks in low earth orbit
IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS
2001; 37 (1): 134-146
View details for Web of Science ID 000167551500010
- The danger of myopic conservatism in risk analysis: the problem of time allocation for the deep space network 2001
- Programmatic Risk Analysis to Search for Life on Mars 2001
- Managing Technology in the Information Age: Stanford’s New Department of Management Science and Engineering International Journal of Technology, Policy and Management, (IJTPM) 2001; 1 (2): 160-173
- Introducing a Risk Chair in Concurrent Design Engineering and Satellite Swarm Illustration 2001
- APRAM: An Advanced Programmatic Risk Analysis Method International Journal of Technology, Policy and Management (IJTPM) 2001; 1 (1): 47-65
- Management of Post-industrial Systems: Academic Challenges and the Stanford Experience International Journal of Technology, Policy and Management, (IJTPM) 2001; 1 (2): 151-159
- Risk and Uncertainty Analysis in Government Safety Decisions 2001
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Delays and safety in airline maintenance
RELIABILITY ENGINEERING & SYSTEM SAFETY
2000; 67 (3): 301-309
View details for Web of Science ID 000085501300010
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Safety and productivity trade-offs: managing nuclear reactor outages
INTERNATIONAL JOURNAL OF TECHNOLOGY MANAGEMENT
2000; 19 (3-5): 420-438
View details for Web of Science ID 000086492900014
- Can Faster-Better-Cheaper Work? Challenges and Recommendations for the Management of Future Space Missions 2000
- Global Risk Management Environmental Risk Planning and Management edited by Turner, B. 2000: 1
- Advanced Programmatic Risk Analysis for Programs of Dependent Projects Involving Critical Systems, and Unmanned Space Mission Illustration edited by Kondo, S., Furuta, K. 2000
- Greed and Ignorance: Motivations and Illustrations of the Quantification of Major Risks 2000
- Managing Technology in the Information Age: The New Department of Management Science and Engineering at Stanford University 2000
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Anticipating accidents that have not happened yet: A quantitative approach and airline maintenance application
Conference on Foresight and Precaution
A A BALKEMA PUBLISHERS. 2000: 289–295
View details for Web of Science ID 000088745600042
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Conditional uncertainty analysis and implications for decision making: The case of WIPP
RISK ANALYSIS
1999; 19 (5): 995-1002
Abstract
Uncertainty analyses and the reporting of their results can be misinterpreted when these analyses are conditional on a set of assumptions generally intended to bring some conservatism in the decisions. In this paper, two cases of conditional uncertainty analysis are examined. The first case includes studies that result, for instance, in a family of risk curves representing percentiles of the probability distribution of the future frequency of exceeding specified consequence levels conditional on a set of hypotheses. The second case involves analyses that result in an interval of outcomes estimated on the basis of conservative assumptions. Both types of results are difficult to use because they are sometimes misinterpreted as if they represented the output of a full uncertainty analysis. In the first case, the percentiles shown on each risk curve may be taken at face value when in reality (in marginal terms) they are lower if the chosen hypotheses are conservative. In the second case, the fact that some segments of the resulting interval are highly unlikely--or that some more benign segments outside the range of results are quite possible--does not appear. Also, these results are difficult to compare to those of analyses of other risks, possibly competing for the same risk management resources, and the decision criteria have to be adapted to the conservatism of the hypotheses. In this paper, the focus is on the first type (conditional risk curves) more than on the second and the discussion is illustrated by the case of the performance assessment of the Waste Isolation Pilot Plant in New Mexico. For policy-making purposes, however, the problems of interpretation, comparison, and use of the results are similar.
View details for Web of Science ID 000083825000013
View details for PubMedID 10765442
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Risk assessment based on financial data: Market response to airline accidents
RISK ANALYSIS
1999; 19 (3): 473-486
View details for Web of Science ID 000082303800014
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Designing risk-management strategies for critical engineering systems
IEEE TRANSACTIONS ON ENGINEERING MANAGEMENT
1999; 46 (1): 87-100
View details for Web of Science ID 000078191800008
- Global Trends in the Management of Post-industrial Systems: Academic Challenges and the Stanford Experience 1999
- Medical Application of Engineering Risk Analysis and Anesthesia Patient Risk Illustration American Journal of Therapeutics 1999; 6 (5): 245-255
- Airline Maintenance vs Flight Delays: Probabilistic Methods and Risk Management for Accidents That Have Not Happened Yet 1999
- Challenges and Recommendations for the Management of Faster-Better-Cheaper Space Missions 1999
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Dynamic risk management systems: Hybrid architecture and offshore platform illustration
RISK ANALYSIS
1998; 18 (4): 485-496
View details for Web of Science ID 000076284000015
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Challenges in the management of faster-better-cheaper space missions
IEEE Aerospace Conference
I E E E. 1998: 507–514
View details for Web of Science ID 000074665200046
- Diagnostic anténatal: doutes À visage différent: l’alliance thérapeutique autour de l’enfant meurtri Michel Serres and André Chancholle Eds.Hermann Pub., Paris, France. 1998: 1
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Risk comparison: Uncertainties and ranking
4th International Conference on Probabilistic Safety Assessment and Management
SPRINGER-VERLAG LONDON LTD. 1998: 1991–1996
View details for Web of Science ID 000084758100301
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Analytical tools for the management of faster-better-cheaper space missions
IEEE Aerospace Conference
I E E E. 1998: 515–530
View details for Web of Science ID 000074665200047
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Priorities in risk management: Human and organizational factors as external events and a maritime illustration
4th International Conference on Probabilistic Safety Assessment and Management
SPRINGER-VERLAG LONDON LTD. 1998: 2675–2680
View details for Web of Science ID 000084758100404
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Anesthesia patient risk: A quantitative approach to organizational factors and risk management options
RISK ANALYSIS
1997; 17 (4): 511-523
Abstract
The risk of death or brain damage to anesthesia patients is relatively low, particularly for healthy patients in modern hospitals. When an accident does occur, its cause is usually an error made by the anesthesiologist, either in triggering the accident sequence, or failing to take timely corrective measures. This paper presents a pilot study which explores the feasibility of extending probabilistic risk analysis (PRA) of anesthesia accidents to assess the effects of human and management components on the patient risk. We develop first a classic PRA model for the patient risk per operation. We then link the probabilities of the different accident types to their root causes using a probabilistic analysis of the performance shaping factors. These factors are described here as the "state of the anesthesiologist" characterized both in terms of alertness and competence. We then analyze the effects of different management factors that affect the state of the anesthesiologist and we compute the risk reduction benefits of several risk management policies. Our data sources include the published version of the Australian Incident Monitoring Study as well as expert opinions. We conclude that patient risk could be reduced substantially by closer supervision of residents, the use of anesthesia simulators both in training and for periodic recertification, and regular medical examinations for all anesthesiologists.
View details for Web of Science ID A1997XZ03600014
View details for PubMedID 9323876
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Probabilistic analysis of the effect of resource constraints on system safety: Towing failures during the construction of concrete platforms
7th International Offshore and Polar Engineering Conference (ISOPE-97)
INTERNATIONAL SOCIETY OFFSHORE& POLAR ENGINEERS. 1997: 268–274
View details for Web of Science ID A1997BJ14E00040
- Normative Engineering Risk Management Systems Reliability Engineering and System Safety 1997; 57 (2): 159-169
- Hybrid Dynamic Risk Management Systems: Concepts and Illustration Advances in Expert Systems for Management: Evaluation and Value in Knowledge-based Systems edited by Grabowski, M., Wallace, W., A. JAI Press, Greenwich, CT. 1997; 2nd: 213–227
- The Interdisciplinary Nature of Risk Analysis edited by Waller, R., A., Covello, V., T. 1997
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Patient risk in anesthesia: Probabilistic risk analysis and management improvements
ANNALS OF OPERATIONS RESEARCH
1996; 67: 211-233
View details for Web of Science ID A1996VN75000011
- Affordable Cleanup? Opportunity for Cost Reduction in the Decontamination and Decommissioning of the Nation's Enrichment Facilities (co-author of various sections) Committee on the Decontamination and Decommissioning of Uranium Enrichments Plants: National Academy Press, Washington, D.C.. 1996: 1
- Human and Management Factors in Probabilistic Risk Analysis: the SAM Approach and Observations from Recent Applications Reliability Engineering and System Safety 1996; 53: 115-126
- Global Risk Management Journal of Risk and Uncertainty 1996; 12: 239-255
- Advanced Risk Management System (ARMS): Cost Reduction through Better Safety Management 1996
- Uncertainties in Risk Analysis: Six Levels of Treatment Reliability Engineering and System Safety 1996; 54: 95-111
- The SAM Framework: A Systems Analysis Approach to Modeling the Effects of Management on Human Behavior in Risk Analysis Risk Analysis 1996; 16 (4): 501-515
- Uncertainties in Global Climate Change Estimates Climatic Change 1996; 33: 145-149
- The Treatment of Uncertainties in Risk Analysis: Management Relevance and Comparison Issues 1996
- Patient Risk in Anesthesia and Benefits of Management Improvements 1996
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MANAGING FIRE RISK ONBOARD OFFSHORE PLATFORMS - LESSONS FROM PIPER-ALPHA AND PROBABILISTIC ASSESSMENT OF RISK REDUCTION MEASURES
FIRE TECHNOLOGY
1995; 31 (2): 99-119
View details for Web of Science ID A1995QX54100002
- Probabilistic Interpretation of Command and Control Signals: Bayesian Updating of the Probability of Nuclear Attack Reliability Engineering and System Safety 1995; 47 (1): 27-36
- Structure and Illustration of a Probabilistic Risk Analysis Model for Space Shuttle EVAs 1995
- Dynamic Risk Management Systems: Concepts and Illustration 1995
- Numerical Safety Goals for Engineering Risk Management 1994
- Risk Analysis: Hazards and Zonation Improving the Safety of Marine Pipelines National Academy Press, Washington D.C.. 1994: 1
- A Challenge to the Compound Lottery Axiom: A Two-stage Normative Structure and Comparison to Other Theories Theory and Decision 1994; 37 (3): 267-309
- Risk Management for the Tiles of the Space Shuttle Interfaces 1994; 24: 64-86
- PRA As A Management Tool: Improving the Safety of the Tiles of the Space Shuttle Orbiter 1994
- The Advanced Risk Management System - ARMS 1994
- PRA As A Management Tool in the Design Phase 1994
- Quantitative Safety Goals for Risk Management of Industrial Facilities Structural Safety 1994; 13 (3): 145-157
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PROBABILISTIC RISK ANALYSIS AND RISK-BASED PRIORITY SCALE FOR THE TILES OF THE SPACE-SHUTTLE
RELIABILITY ENGINEERING & SYSTEM SAFETY
1993; 40 (3): 221-238
View details for Web of Science ID A1993KV56000003
- Learning from the Piper Alpha Accident: A Post-Mortem Analysis of Technical and Organizational Factors Risk Analysis 1993; 13 (2): 215-232
- Risk Analysis and Risk Management for Offshore Platforms: Lessons from the Piper Alpha Accident Journal of Offshore Mechanics and Arctic Engineering 1993; 115: 179-190
- Subjective De-biasing of Data Sets: A Bayesian Approach 1993
- Risk Management for Existing Facilities: A Global Approach to Numerical Safety Goals Applied Mechanics Reviews 1993; 46 (5): 242-245
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PRA AS A MANAGEMENT TOOL - ORGANIZATIONAL-FACTORS AND RISK-BASED PRIORITIES FOR THE MAINTENANCE OF THE TILES OF THE SPACE-SHUTTLE ORBITER
RELIABILITY ENGINEERING & SYSTEM SAFETY
1993; 40 (3): 239-257
View details for Web of Science ID A1993KV56000004
- A Two-step Procedure for the Bayesian Updating of the Probability of Nuclear Attack on the United States 1992
- Management Errors and System Reliability: A Probabilistic Approach and Application to Offshore Platforms Risk Analysis 1992; 12 (1): 1-18
- The Advanced Risk Management System Project: A Resource-Constrained Normative Decision System 1992
- Seismic Hazard Uncertainties in Rational Building Code Decisions 1992
- Rationality and Risk Uncertainties in Building Code Provisions 1991
- Aversion to Epistemic Uncertainties in Rational Decision Making: Effects on Engineering Risk Management 1991
- Hybrid Systems for Failure Diagnosis, Operations Research and Artificial Intelligence: The Integration of Problem Solving Strategies edited by Brown, D., E. Kluwer Academic Pub. 1990: 1
- Dynamic Optimization of Cash Flow Management Decisions: A Stochastic Model IEEE Transactions on Engineering Management 1990; 37 (3): 203-212
- Organizational Aspects of Engineering System Safety: The Case of Offshore Platforms Science 1990; 250: 1210-1217
- Organizational Control of System Reliability: A Probabilistic Approach and Application to Offshore Platforms Control-Theory and Advanced Technology 1989; 5 (4): 549-568
- Reliability Management of Offshore Platforms: A Quantitative Approach to Organizational Factors 1989
- Organizational Extensions of PRA Models and NASA Application 1989
- Organizational Roots of System Failure: The Case of Offshore Platforms 1989
- Engineering Reliability: The Organizational Link 1988
- Costs and Benefits of Seismic Rehabilitation 1988
- Organizational Factors in Reliability Models 1988
- Risk-Based Monitoring of Industrial Systems 1988
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PROBABILISTIC RISK ANALYSIS AND SAFETY REGULATION IN THE CHEMICAL-INDUSTRY
JOURNAL OF HAZARDOUS MATERIALS
1987; 15 (1-2): 97-122
View details for Web of Science ID A1987H951500005
- Risk Regulation for Nuclear Power Plants: Probability and Analytical Uncertainties 1987
- Warnings of Malfunctions: The Decision to Inspect and Maintain Production Processes on Schedule or on Demand Management Science 1987; 33 (10): 1277-1290
- Risk in Defense Policy Decisions 1987
- Risk Uncertainties in Safety Decisions: Dealing with Soft Numbers edited by Lind, N., C. 1987
- Risk Analysis and Relevance of Uncertainties in Nuclear Safety Decisions, Public Regulation: New Perspectives on Institutions and Policies edited by Bailey, E., E. The MIT Press. 1987: 227–253
- Warning Systems in Risk Management Risk Analysis 1986; 6 (2): 223-234
- Probability and Uncertainty in Nuclear Safety Decisions Nuclear Engineering and Design 1986; 93 (2 & 3): 319-327
- Risk Uncertainties in Public Sector Safety Decisions: Assessment Methods and Management Implications 1986
- Risk Cost for New Dams: Economic Analysis and Effects of Monitoring Water Resources Research 1986; 22 (1): 5-14
- Fire Monitoring by Cameras in Oil Refineries: A Risk-Cost-Benefit Analysis 1985
- Reduction of Fire Risks in Oil Refineries: Economic Analysis of Camera Monitoring Risk Analysis 1985; 5 (4): 277-288
- Warning Systems and Defense Policy: A Reliability Model for the Command and Control of the U.S. Nuclear Forces Risk Analysis 1985; 5 (2): 121-138
- Warning Systems and Risk Reduction edited by Whipple, C., Covello, V. 1985
- Costs and Benefits of Seismic Upgrading of Some Buildings in the Boston Area Earthquake Spectra 1985; 1 (4): 721-740
- Warning Systems: Application to the Reduction of Risk Costs for New Dams 1984
- Warning Systems: Response Models and Optimization 1984
- Fault Trees vs. Event Trees in Reliability Analysis Risk Analysis 1984; 4 (3): 177-186
- Earthquake Prediction: The Costs of Crying Wolf 1984
- Aggregation of Opinions and Preferences in Decision Problems Low Probability-High Consequence Risk Analysis: Issues, Methods and Case Studies, (Proceedings of the 1982 Annual Meeting of the Society for Risk Analysis held in Arlington, VA Plenum Press, New York. 1984: 493–503
- Warning Systems and Risk Reduction 1983
- Acceptable Decision Processes and Acceptable Risks in Public Sector Regulations IEEE Transaction on Systems, Man, and Cybernetics 1983; SMC-13 (3): 113-124
- Seismic Regulation for Some Existing Buildings in the Boston Area: Economic and Safety Analysis 1983
- Discounting in Risk Analysis: Capital vs. Human Safety in Risk, Structural Engineering and Human Error edited by Grigoriu, M. University of Waterloo. 1983: 1
- Relevance of Risk Uncertainties in Regulated Decisions 1983
- Probabilistic Assessment of Warning Systems 1983
- Analysis of Warning Systems: Application to Earthquake Prediction Earthquake Prediction Research 1982; 1 (2): 197-205
- The Decision to Predict Earthquakes and its Economic Implications 1981
- Consistency of Standards Across the Different Economic Sectors 1981
- Risk of Dam Failure in Benefit-Cost Analysis Water Resources Research 1980; 16 (3): 449-456
- Public Policy Issues: Earthquake Engineering Bulletin of the Seismological Society of America 1980; 70 (5): 1955-1968
- Evaluation of the Economic Consequences of Natural Catastrophes 1980
- Dam Failure in Benefit/Cost Analysis 1980
- Assessment and Mitigation of Earthquake Effects on Economic Production 1980
- Acceptance of a Social Cost for Human Safety 1979
- Public Policy Issues: Earthquake Prediction Bulletin of the Seismological Society of America 1979; 69 (5): 1533-1547
- Public Policy in Earthquake Effects Mitigation 1977
- Review of the Prince William Sound Risk Assessment Study Committee on Risk Assessment and Management for Marine Systems (national Research Council, Marine Board). Chair of the committee, co-author of several sections. National Academy Press, Washington D.C.. : 1
- Probabilistic Analysis of the Effect of Resource Constraints on System Safety: Towing Failures During the Construction of Concrete Platforms
- Games and Risk Analysis: Three examples of single and alternate moves Game theoretic Risk Analysis of Security Threats edited by Bier, V., Azaiez, M., N. Springer Pub, New York.. : 147–175
- Warning Systems for Engineering Projects