2 Hazard, risk, risk analysis, risk management

1995 ◽  
pp. 4-6
Keyword(s):  
Risk Management ◽  
Risk Analysis ◽  
Hazard Risk

Design Thinking as a Tool for the Analysis of Project Risks

2019 ◽  
Vol 16 (6) ◽  
pp. 60-77
Author(s):  
E. V. Vasilieva ◽  
T. V. Gaibova
Keyword(s):  
Risk Management ◽  
Risk Analysis ◽  
Design Thinking ◽  
Management Tools ◽  
Project Risk ◽  
Team Members ◽  
Investment Projects ◽  
Risk Management Process ◽  
Project Objectives ◽  
Project Risk Analysis

This paper describes the method of project risk analysis based on design thinking and explores the possibility of its application for industrial investment projects. Traditional and suggested approaches to project risk management have been compared. Several risk analysis artifacts have been added to the standard list of artifacts. An iterative procedure for the formation of risk analysis artifacts has been developed, with the purpose of integrating the risk management process into strategic and prompt decision-making during project management. A list of tools at each stage of design thinking for risk management within the framework of real investment projects has been proposed. The suggested technology helps to determine project objectives and content and adapt them in regards to possible; as well as to implement measures aimed at reducing these risks, to increase productivity of the existing risk assessment and risk management tools, to organize effective cooperation between project team members, and to promote accumulation of knowledge about the project during its development and implementation.The authors declare no conflict of interest.

Methods and Tools for Natural Hazard Risk Analysis in Eastern Canada: Using Knowledge to Understand Vulnerability and Implement Mitigation Measures

2017 ◽  
Vol 18 (1) ◽  
Author(s):  
Miroslav Nastev ◽  
Marie-José Nollet ◽  
Ahmad Abo El Ezz ◽  
Alex Smirnoff ◽  
Sarah Kate Ploeger ◽  
...  
Keyword(s):  
Risk Analysis ◽  
Natural Hazard ◽  
Mitigation Measures ◽  
Eastern Canada ◽  
Hazard Risk

scholarly journals Research for Risk Management of Construction Projects in Taiwan

2021 ◽  
Vol 13 (4) ◽  
pp. 2034
Author(s):  
Chien-Liang Lin ◽  
Bey-Kun Chen
Keyword(s):  
Risk Management ◽  
Risk Analysis ◽  
Structural Equation ◽  
Construction Projects ◽  
Construction Project ◽  
Equation Modeling ◽  
Analysis Model ◽  
Sustainable Operation ◽  
Management Procedure ◽  
Risk Managers

Risks inevitably exist in all stages of a project. In a construction project, which is highly dynamic and complex, risk factors affect the expected achievement rates of the three main performance goals, namely schedule, cost, and quality. A comprehensive risk management procedure requires three crucial steps: risk confirmation, analysis, and treatment. Risk analysis is the core of risk management. Through structural equation modeling, this study developed a risk analysis model that takes a different perspective and considered the occurrence probability of risk events and the extent to which these events affect a project. The contractor dimension was discovered to exert the strongest influence on an overall project, followed by the subcontractor and design dimensions. This paper proposes a novel construction project risk analysis model, which considers the entire project. The proposed model can be used as a reference for risk managers to make decisions about project risks, so as to achieve the ultimate goal of saving resources and the sustainable operation of the construction project.

Analysis of risk concept for technical systems using digital twins

2020 ◽  
pp. 99-113
Author(s):  
Анатолий Михайлович Лепихин ◽  
Николай Андреевич Махутов ◽  
Юрий Иванович Шокин ◽  
Андрей Васильевич Юрченко
Keyword(s):  
Risk Management ◽  
Risk Analysis ◽  
Risk Model ◽  
Computer Modelling ◽  
Product Lifecycle Management ◽  
Operating Conditions ◽  
Digital Twins ◽  
Real Objects ◽  
Technical Systems ◽  
Active Research

Рассмотрены основные методологические аспекты анализа рисков технических систем с использованием цифровых двойников. Сформулирована концепция рисканализа и предложена базовая модель для ее реализации. Рассмотрены информационные аспекты анализа неопределенностей модели риска. Показано, что технологии цифровых двойников позволяют эффективно сочетать результаты компьютерного моделирования с данными мониторинга реальных объектов, обеспечивая более глубокий анализ объектов, с учетом множества вариантов конструкции, технологий и условий эксплуатации Development of technology and technical systems significantly increases in the volume of information. Traditional methods for designing, manufacturing and operating of technical systems do not allow processing such volumes of information. In this regard, the modern strategy for creating technical systems is based on the use of digital twins. Solving the problems of risk analysis and risk management for technical systems at all stages of the life cycle appears to be one of the promising areas for application of the digital twins technology. Despite of active research, using digital twins in risk analysis currently do not have appropriate methodological justifications and technical solutions in a number of key aspects. In particular, effective reductions of the order of risk models and quantifying uncertainty factors of various types have not been solved. The concept of the risk-informed decision making in product lifecycle management has not been implemented. In fact, there are very few publications on the risk analysis and risk management methodology using digital twins. The article discusses the main methodological aspects of risk analysis of technical systems using digital twins. The concept of risk analysis is formulated and a basic model for its implementation is proposed. The informational aspects of the analysis of uncertainties of the risk model are considered. It is shown that digital twin technologies allow effective combination of the results of computer modelling with the data monitoring of real objects, providing a deeper analysis of objects, taking into account a variety of design options, technologies and operating conditions.

scholarly journals Hydrological Layered Dialysis Research on Supply Chain Financial Risk Prediction under Big Data Scenario

2018 ◽  
Vol 2018 ◽  
pp. 1-9
Author(s):  
Jia Liu ◽  
Shiyong Li ◽  
Xiaoxia Zhu
Keyword(s):  
Risk Management ◽  
Big Data ◽  
Supply Chain ◽  
Risk Analysis ◽  
Risk Prediction ◽  
Financial Institutions ◽  
Surface Runoff ◽  
Financial Risk ◽  
Supply Chain Finance ◽  
Runoff Model

In recent years, internet development provides new channels and opportunities for small- and middle-sized enterprises’ (SMEs) financing. Supply chain finance is a hot topic in theoretical and practical circles. Financial institutions transform materialized capital flows into online data under big data scenario, which provides networked, precise, and computerized financial services for SMEs in the supply chain. By drawing on the risk management theory in economics and the distributed hydrological model in hydrology, this paper presents a supply chain financial risk prediction method under big data. First, we build a “hydrological database” used for the risk analysis of supply chain financing under big data. Second, we construct the risk identification models of “water circle model,” “surface runoff model,” and “underground runoff model” and carry on the risk prediction from the overall level (water circle). Finally, we launch the supply chain financial risk analysis from breadth level (surface runoff) and depth level (underground runoff); moreover, we integrate the analysis results and make financial decisions. The results can enrich the research on risk management of supply chain finance and provide feasible and effective risk prediction methods and suggestions for financial institutions.

scholarly journals The impact of a and b value uncertainty on loss estimation in the reinsurance industry

2000 ◽  
Vol 43 (1) ◽  
Author(s):  
D. Liechti ◽  
E. Ruettener ◽  
S. Eugster ◽  
R. Streit
Keyword(s):  
Risk Management ◽  
Risk Analysis ◽  
Loss Estimation ◽  
Earthquake Risk ◽  
Seismic Risk Analysis ◽  
Earthquake Catalogues ◽  
Local Soil ◽  
Average Annual Loss ◽  
The Impact ◽  
Loss Level

In the reinsurance industry different probabilistic models are currently used for seismic risk analysis. A credible loss estimation of the insured values depends on seismic hazard analysis and on the vulnerability functions of the given structures. Besides attenuation and local soil amplification, the earthquake occurrence model (often represented by the Gutenberg and Richter relation) is a key element in the analysis. However, earthquake catalogues are usually incomplete, the time of observation is too short and the data themselves contain errors. Therefore, a and b values can only be estimated with uncertainties. The knowledge of their variation provides a valuable input for earthquake risk analysis, because they allow the probability distribution of expected losses (expressed by Average Annual Loss (AAL)) to be modelled. The variations of a and b have a direct effect on the estimated exceeding probability and consequently on the calculated loss level. This effect is best illustrated by exceeding probability versus loss level and AAL versus magnitude graphs. The sensitivity of average annual losses due to different a to b ratios and magnitudes is obvious. The estimation of the variation of a and b and the quantification of the sensitivity of calculated losses are fundamental for optimal earthquake risk management. Ignoring these uncertainties means that risk management decisions neglect possible variations of the earthquake loss estimations.

scholarly journals Workplace risk management for SARS-CoV-2: a three-step early in-tervention strategy for effective containment of infection chains with special regards to virus variants with increased infectivity

2021 ◽  
Author(s):  
Andreas Paassen ◽  
Laura Anderle ◽  
Karsten John ◽  
Sebastian Wilbrand
Keyword(s):  
Risk Management ◽  
Risk Analysis ◽  
Scientific Knowledge ◽  
Epidemiological Model ◽  
Model Calculations ◽  
Targeted Testing ◽  
Alternative Measures

Background: Priority during the SARS-CoV2 pandemic is that employees need to be protected from infection risks and business activities need to be ensured. New virus variants with increased infec-tion risks require an evolved risk strategy. Material and methods: Several standard measures such as testing, isolation and quarantine are combined to a novel risk strategy. Epidemiological model calculations and scientific knowledge about the course of SARS-CoV2 infectivity are used to optimize this strategy. The procedure is implemented in an easy-to-use calculator based on Excel. Layout in practice and results: Alternative combinations of measures and practical aspects are discussed. Example calculations are used to demonstrate the effect of the discussed measures. Conclusion: That quarantine calculator derived from these principles enables even non-specialists to perform a differentiated risk analysis and to introduce optimized measures. Targeted testing routines and alternative measures ensure staff availability.

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