Function-Oriented Risk Model for Engineering System

2012 ◽  
Vol 433-440 ◽  
pp. 2899-2903
Author(s):  
Wei Jing Zhou ◽  
Huai Rong Shen
Keyword(s):  
Risk Factors ◽  
Risk Analysis ◽  
Risk Model ◽  
Modeling Method ◽  
Engineering System ◽  
Structural Description ◽  
System A ◽  
Logic Diagram ◽  
Servo Mechanism

Risk analysis is important to increase the reliability of engineering system. And an excellent model is the foundation. Traditional models are event-oriented so that it can’t describe the totality of the system. This paper introduces a function-oriented modeling approach-Goal Tree Success Tree and Master Logic Diagram. It provides a powerful functional/structural description and modeling method. It can represent the goals, the functions, the components and their interactions of the engineering system. So, it is a systemic modeling method for the risk analysis of engineering system. A case study of the servo mechanism of the launch vehicle shows that this approach can identify the key risk factors and the hidden risk factors. And it can trace the failure influence. It provides a systemic approach to risk analysis for researchers

Scenario based evaluation of a cost risk model through sensitivity analysis

2015 ◽  
Vol 22 (4) ◽  
pp. 403-423 ◽  
Author(s):  
Önder Ökmen ◽  
Ahmet Öztaş
Keyword(s):  
Risk Factors ◽  
Risk Analysis ◽  
Risk Model ◽  
Practical Method ◽  
Cost Evaluation ◽  
Sensitivity Analyses ◽  
Analysis Model ◽  
Content Type ◽  
Detailed Evaluation ◽  
Cost Risk

Purpose – Actual costs frequently deviate from the estimated costs in either favorable or adverse direction in construction projects. Conventional cost evaluation methods do not take the uncertainty and correlation effects into account. In this regard, a simulation-based cost risk analysis model, the Correlated Cost Risk Analysis Model, previously has been proposed to evaluate the uncertainty effect on construction costs in case of correlated costs and correlated risk-factors. The purpose of this paper is to introduce the detailed evaluation of the Cost Risk Analysis Model through scenario and sensitivity analyses. Design/methodology/approach – The evaluation process consists of three scenarios with three sensitivity analyses in each and 28 simulations in total. During applications, the model’s important parameter called the mean proportion coefficient is modified and the user-dependent variables like the risk-factor influence degrees are changed to observe the response of the model to these modifications and to examine the indirect, two-sided and qualitative correlation capturing algorithm of the model. Monte Carlo Simulation is also applied on the same data to compare the results. Findings – The findings have shown that the Correlated Cost Risk Analysis Model is capable of capturing the correlation between the costs and between the risk-factors, and operates in accordance with the theoretical expectancies. Originality/value – Correlated Cost Risk Analysis Model can be preferred as a reliable and practical method by the professionals of the construction sector thanks to its detailed evaluation introduced in this paper.

Risk Analysis in Renewable Energy System (RES) Investment for a Developing Country: A Case Study in Pakistan

2020 ◽  
Vol 19 (2) ◽  
pp. 204-223
Author(s):  
Izzet Alp Gul ◽  
Gülgün Kayakutlu ◽  
M. Özgür Kayalica
Keyword(s):  
Risk Factors ◽  
Renewable Energy ◽  
Life Cycle ◽  
Risk Analysis ◽  
Fossil Fuels ◽  
Energy Transition ◽  
Energy System ◽  
Assessment Model ◽  
Infrastructure Investments

Technological improvements allow changing a significant part of the electricity generation investments to renewable energies. Especially in emerging markets and energy import-dependent countries, shift to renewable energy generation became more important to break the links of dependency. Pakistan relies on imported fossil fuels; however, the country’s experience and ambition about the renewable energy transition gain prominence in recent years. Considering the long-term life cycle of energy infrastructure investments, possible risk factors and their dynamic nature must be analysed before the financial decisions are taken. This article aims to propose a system dynamics model for the risk analysis of investment life cycle. In this study, possible risk factors are detected and discussed in different categories. The casual loop diagram of possible risk factors and risk assessment model are designed, and the impacts are analysed. Case study of the proposed model in Pakistan highlighted the importance of commercial risks. The results achieved through this study will guide investors, sector participants and policymakers to develop stable strategies for promoting renewable energy in the country. JEL: Q42, P48, O13

scholarly journals Integration of Interpretive Structural Modeling with Fuzzy Bayesian Network for Risk Assessment of Tunnel Collapse

2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Leping He ◽  
Tao Tang ◽  
Qijun Hu ◽  
Qijie Cai ◽  
Zhijun Li ◽  
...  
Keyword(s):  
Risk Factors ◽  
Risk Analysis ◽  
Bayesian Network ◽  
Risk Model ◽  
Multicriteria Decision Making ◽  
Structural Modeling ◽  
Interpretive Structural Modeling ◽  
Construction Risk ◽  
Tunnel Collapse ◽  
The Relationship

Frequent collapse accidents in tunnels are associated with many construction risk factors, and the interrelationship among these risk factors is complex and ambiguous. This study’s aim is to clarify the relationship among risk factors to reduce the tunnel collapse risk. A multicriteria decision-making method is proposed by combining interpretive structural modeling (ISM) and fuzzy Bayesian network (FBN). ISM is used to determine the hierarchical relationships among risk factors. FBN quantitatively analyzes the strength of the interaction among risk factors and conducts risk analysis. The ISM-FBN method contains three steps: (1) drawing the ISM-directed graph; (2) obtaining the probability of the FBN nodes; and (3) using GeNle to implement risk analysis. The proposed method is also used to assess the collapse risk and detect the critical factors in the Canglongxia Tunnel, China. This method’s tunnel collapse risk model can provide managers with clear risk information and better realize project management.

Proximity and density of neighboring farms and water supply, as risk factors for bacteriosis: A case study of spatial risk analysis in tilapia and rainbow trout farms of Oaxaca, Mexico

Aquaculture ◽  
2020 ◽  
Vol 520 ◽  
pp. 734955
Author(s):  
Luis Guerrero-Cabrera ◽  
Beatriz Carely Luna Olivera ◽  
José Geiser Villavicencio-Pulido ◽  
Romel Jesus Ortiz Luna
Keyword(s):  
Risk Factors ◽  
Rainbow Trout ◽  
Risk Analysis ◽  
Water Supply ◽  
Spatial Risk ◽  
Spatial Risk Analysis ◽  
Trout Farms

scholarly journals Using EWGM method to optimise the FMEA as a risk assessment methodology

2019 ◽  
Vol 27 (2) ◽  
pp. 144-154 ◽  
Author(s):  
Sahar AL Mashaqbeh ◽  
Jose Eduardo Munive-Hernandez ◽  
Mohammed Khurshid Khan
Keyword(s):  
Risk Factors ◽  
Risk Assessment ◽  
Risk Analysis ◽  
Systematic Approach ◽  
Failure Modes ◽  
Assessment Tool ◽  
Geometric Mean ◽  
Assessment Process ◽  
Risk Ranking

Failure modes and effect analysis (FMEA) is a proactive, highly structured and systematic approach for failure analysis. It has been also applied as a risk assessment tool, by ranking potential risks based on the estimation of risk priority numbers (RPNs). This article develops an improved FMEA methodology for strategic risk analysis. The proposed approach combines the analytic hierarchy process (AHP) technique with the exponential and weighted geometric mean method (EWGM) to support risk analysis. AHP is applied to estimate the weights of three risk factors: Severity (S), Occurrence (O) and Detection (D), which integrate the RPN for each risk. The EWGM method is applied for ranking RPNs. Combining AHP with EWGM allows avoiding repetition of FMEA results. The results of the developed methodology reveal that duplication of RPNs has been decreased, facilitating an effective risk ranking by offering a unique value for each risk. The proposed methodology not only focuses on high severity values for risk ranking but it also considers other risk factors (O and D), resulting in an enhanced risk assessment process. Furthermore, the weights of the three risk factors are considered. In this way, the developed methodology offers unique value for each risk in a simple way which makes the risk assessment results more accurate. This methodology provides a practical and systematic approach to support decision makers in assessing and ranking risks that could affect long-term strategy implementation. The methodology was validated through the case study of a power plant in the Middle East, assessing 84 risks within 9 risk categories. The case study revealed that top management should pay more attention to key risks associated with electricity price, gas emissions, lost-time injuries, bad odour and production.

SUBCONTRACTING MANAGEMENT IN AN EPC PROJECT: A CASE STUDY OF DELAY RISKS

2015 ◽  
Vol 2 (1) ◽  
Author(s):  
Puti Farida Tamin ◽  
Dian Perwitasari ◽  
Rizal Tamin
Keyword(s):  
Risk Factors ◽  
Power Generation ◽  
Risk Factor ◽  
Risk Analysis ◽  
Alternative Energy ◽  
Project Completion ◽  
Infrastructure Project ◽  
Qualitative Risk Analysis ◽  
Critical Project

Subcontracting was adopted in a major EPC power generating infrastructure project in South-Sumatera, Indonesia. The completion of this project, which was executed in the framework of the government’s alternative energy power generation acceleration endeavor, was delayed. This paper analyzes subcontracting management as the main cause of the delay. A data collecting survey, which included interviews with project respondents, was conducted in the objective to obtain their perception on delay risk caused by subcontracting management. A risk factor list was created based on this survey. A qualitative risk analysis was used to assess the risk extent. 18 risk factors with high and significant levels are presented. The list of risk factors in each of the EPC project’s phases was then used in analyzing the project’s completion delay. It is shown that the main contractor’s lack of experience in the work’s subcontracting management has caused miscommunications in engineering phase, tender process miscalculations, lack of procured materials and equipment quality, imperfect construction preparation, imperfect commissioning, and reworks. Construction was identified as the most critical project phase due to a relatively high number of subcontractors involved in the work and the complexity of the EPC project. The interaction of the whole factors finally caused project completion delay.

Based on the ISM Model of REITs Endowment Property Financing Risk Analysis

2014 ◽  
Vol 1030-1032 ◽  
pp. 2523-2526
Author(s):  
Hai Min Wei ◽  
Lian Yue
Keyword(s):  
Risk Factors ◽  
Risk Management ◽  
Risk Analysis ◽  
Risk Model ◽  
Financing Risk ◽  
Financing Pattern ◽  
New Form ◽  
The Relationship

Endowment property is prevalent a new form of social endowment in China in recent years, But financing has become one of the bottleneck for its smooth development. In this paper, the author combing the various risk factors of REITs financing pattern, using ISM model to analysis the factors involved in grading evaluation, rendering risk model diagram to explain the structure, resulting the relationship between the various risk factors, clear the direction of risk management

scholarly journals Developing a Risk Model for Assessment and Control of the Spread of COVID-19

Risks ◽  
2021 ◽  
Vol 9 (2) ◽  
pp. 38
Author(s):  
Usama H. Issa ◽  
Ashraf Balabel ◽  
Mohammed Abdelhakeem ◽  
Medhat M. A. Osman
Keyword(s):  
Risk Factors ◽  
Risk Analysis ◽  
Risk Model ◽  
Risk Groups ◽  
Personal Hygiene ◽  
Exact Nature ◽  
Analysis Model ◽  
Factors Affecting ◽  
Probability Of Occurrence ◽  
The Impact

Coronavirus disease 2019 (COVID-19) continues to spread rapidly all over the world challenging nearly all governments. The exact nature of COVID-19’s spread and risk factors for such a rapid spread are still imprecise as available data depend on confirmed cases only. This may result in an asymmetrically distributed burden among countries. There is an urgent need for developing a new technique or model to identify and analyze risk factors affecting such a spread. Fuzzy logic appears to be suitable for dealing with multi-risk groups with undefined data. The main purpose of this research was to develop a risk analysis model for COVID-19’s spread evaluation. Other objectives included identifying such risk factors aiming to find out reasons for such a fast spread. Nine risk groups were identified and 46 risk factors were categorized under these groups. The methodology in this study depended on identifying each risk factor by its probability of occurrence and its impact on viruses spreading. Many logical rules were used to support the proposed risk analysis model and represented the relation between probabilities and impacts as well as to connect other risk factors. The model was verified and applied in Saudi Arabia with further probable use in similar conditions. Based on the model results, it was found that (daily activities) and (home isolation) are considered groups with highest risk. On the other hand, many risk factors were categorized with high severity such as (poor social distance), (crowdedness) and (poor personal hygiene practices). It was demonstrated that the impact of COVID-19’s spread was found with a positive correlation with the risk factors’ impact, while there was no association between probability of occurrence and impact of the risk factors on COVID-19’s spread. Saudi Arabia’s quick actions have greatly reduced the impact of the risks affecting COVID-19’s spread. Finally, the new model can be applied easily in most countries to help decision makers in evaluating and controlling COVID-19’s spread.

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