Effect of Condition Monitoring on Risk Mitigation for Steam Turbines in the Forest Products Industry

2017 ◽  
Vol 3 (3) ◽  
Author(s):  
Bin Zhou ◽  
Kumar Bhimavarapu
Keyword(s):  
Condition Monitoring ◽  
Domain Knowledge ◽  
Risk Mitigation ◽  
Forest Products ◽  
Event Tree ◽  
Steam Turbines ◽  
Event Tree Analysis ◽  
Monitoring Techniques ◽  
Mechanical Breakdown ◽  
Semi Empirical

Industry has been implementing condition monitoring (CM) for turbines to minimize losses and to improve productivity. Deficient conditions can be identified before losses occur by monitoring the equipment parameters. For any loss scenario, the effectiveness of monitoring depends on the stage of the loss scenario when the deficient condition is detected. A scenario-based semi-empirical methodology was developed to assess various types of condition monitoring techniques, by considering their effect on the risk associated with mechanical breakdown of steam turbines in the forest products (FPs) industry. A list of typical turbine loss scenarios was first generated by reviewing loss data and leveraging expert domain knowledge. Subsequently, condition monitoring techniques that can mitigate the risk associated with each loss scenario were identified. For each loss scenario, an event tree analysis (ETA) was used to quantitatively assess the variations in the outcomes due to condition monitoring, and resultant changes in the risk associated with turbine mechanical breakdown. An application was developed following the methodology to evaluate the effect of condition monitoring on turbine risk mitigation.

Effect of Condition Monitoring on Risk Mitigation for Steam Turbines in the Forest Products Industry

2015 ◽  
Author(s):  
Bin Zhou ◽  
Kumar Bhimavarapu
Keyword(s):  
Condition Monitoring ◽  
Domain Knowledge ◽  
Risk Mitigation ◽  
Forest Products ◽  
Event Tree ◽  
Steam Turbines ◽  
Event Tree Analysis ◽  
Monitoring Techniques ◽  
Mechanical Breakdown ◽  
Semi Empirical

Industry has been implementing condition monitoring for turbines to minimize losses and to improve productivity. Deficient conditions can be identified before losses occur by monitoring the equipment parameters. For any loss scenario, the effectiveness of monitoring depends on the stage of the loss scenario when the deficient condition is detected. A scenario-based semi-empirical methodology was developed to assess various types of condition monitoring techniques, by considering their effect on the risk associated with mechanical breakdown of steam turbines in the forest products (FP) industry. A list of typical turbine loss scenarios was first generated by reviewing loss data and leveraging expert domain knowledge. Subsequently, condition monitoring techniques that can mitigate the risk associated with each loss scenario were identified. For each loss scenario, an event tree analysis was used to quantitatively assess the variations in the outcomes due to condition monitoring, and resultant changes in the risk associated with turbine mechanical breakdown. An application was developed following the methodology to evaluate the effect of condition monitoring on turbine risk mitigation.

Steam Turbine Loss Evaluation and Condition Monitoring: A Loss Data Based Study

2016 ◽  
Author(s):  
Bin Zhou
Keyword(s):  
Steam Turbine ◽  
Condition Monitoring ◽  
Domain Knowledge ◽  
Loss Reduction ◽  
Steam Turbines ◽  
Monitoring Methods ◽  
Loss Mitigation ◽  
Loss Data ◽  
Effective Condition ◽  
Different Levels

Steam turbine mechanical breakdowns dominate equipment losses in the Power-Gen and Forest Product industries. As steam turbines are likely custom-built, variations in design, operation and maintenance practices across different industries could result in different levels of significance of the loss drivers. The present study focuses on comparing the turbine loss drivers and effective condition monitoring for loss mitigation in both industries. Steam turbine loss events from the two industries during a recent 10-year period were first reviewed and classified into typical turbine loss scenarios. Contributions of each loss scenario to the total loss count and value were summarized and compared across the two industries. Subsequently, applicable turbine condition monitoring methods were identified for each loss scenario, and evaluated with expert domain knowledge and available loss data. These monitoring methods were finally prioritized according to their functional effectiveness in turbine loss reduction.

A Comprehensive and Practical Framework for Reliable Scheduling in Project Management

2014 ◽  
Vol 903 ◽  
pp. 378-383 ◽  
Author(s):  
Shiva Mansoorzadeh ◽  
Sha’ri Mohd Yusof ◽  
Shahriar Mansoorzadeh ◽  
Hossein Zeynal
Keyword(s):  
Risk Management ◽  
Project Management ◽  
Risk Mitigation ◽  
Electrical Power ◽  
Mitigation Strategies ◽  
Management Technique ◽  
Event Tree ◽  
Project Schedule ◽  
Event Tree Analysis ◽  
Project Objectives

Schedule reliability is essential to successfully achieve EPC (engineering, procurement and constriction) project objectives. Several studies in the past were based on traditional risk management technique which has its own limitations that lack one to obtain a reliable project schedule. To overcome these limitations a comprehensive framework is developed based on the integration of risk management and Critical Chain Project Management (CCPM) that can give a much reliable project scheduling. In the proposed framework, risk analysis is first determined through fuzzy FMEA technique to provide identification of critical risk events (CRE). The effect of CRE on project schedule is then defined and total project time which considers risk factors is calculated. To support risk mitigation, fault tree and event tree analysis are combined which allows the root causes of the risk event be defined and also mitigation strategies determined to control each identified CRE. Eventually, CCPM is distributed which enable implementation of the project based on initial plan and to obtain reasonable Feeding Buffer time on risky tasks. This paper presents the proposed framework using a real case study on construction phases of EPC projects in an electrical power industry.

Risk mitigation in unstabilized approach with fuzzy Bayesian bow-tie analysis

2020 ◽  
Vol 92 (10) ◽  
pp. 1513-1521
Author(s):  
Caner Acarbay ◽  
Emre Kiyak
Keyword(s):  
Risk Assessment ◽  
Performance Indicator ◽  
Risk Mitigation ◽  
Assessment System ◽  
Assessment Process ◽  
Event Tree ◽  
Event Tree Analysis ◽  
Tree Analysis ◽  
Content Type ◽  
Bow Tie

Purpose Stable approach concept has great importance for the safe operation of an airline during the approach and landing phases. The purpose of this study is to analyse the unstabilized approaches with bow-tie method and determine the threats that may cause risk in an unstable approach. Design/methodology/approach In this study, risk assessment of the unstabilized approaches is carried out by using fuzzy bow-tie method and Bayesian networks. Bow-tie method is the combination of event tree analysis and fault tree analysis. Bayesian network is used in the analysis to see interrelationship of basic and intermediate events as well as to update posterior probabilities. Finally, analysis results are verified by the safety performance indicator values. Findings In this study, the probabilistic values of the numerical model presented by the risk assessment system for risks were calculated using the fuzzy bow-tie method. Thus, the risk assessment system has been transformed into a structure that can be expressed in a probabilistic manner, and the relationship of the risks within the system has been examined and the effect of a possible change on the risk value has been found to be prevalent. Originality/value The bow-tie model is widely applied to assess the risks in aviation. Obtaining prior probabilities is not always possible in the risk assessment process. In this paper, innovative fuzzy bow-tie method is used to assess the risks to overcome the lack of prior probability problem in aviation operations.

scholarly journals RISK MANAGEMENT ON THE WARSHIP TASK OPERATIONS

JOURNAL ASRO ◽  
2018 ◽  
Vol 9 (1) ◽  
pp. 23
Author(s):  
Diksono Diksono ◽  
I Made Jiwa ◽  
Suparno Suparno
Keyword(s):  
Risk Mitigation ◽  
Fault Tree ◽  
Fault Tree Analysis ◽  
Main Tool ◽  
Main Task ◽  
Event Tree ◽  
Event Tree Analysis ◽  
Tree Analysis ◽  
Formal Safety Assessment ◽  
The Impact

ABSTRACT The main task of the Indonesia Navy is to enforce the law and maintain security in the territorial sea of national jurisdiction, so that the Indonesian Navy is required to have the main tool of weapons systems (Alutsista) are always ready to carry out the task. The frequent occurrence of accidents experienced by the Indonesian Warship (KRI). This reduces the ability of Warship in performing the task. The purpose of this research is to investigate the causes and effects of accidents, and seek risk mitigation that is considered appropriate. Formal Safety Assessment (FSA) is a structured and systematic methodology used for maritime safety analysis. The fault tree analysis is used to investigate the cause of marine accidents and the event tree analysis is used to determine the impact of an accident. The results of this study are FSA can be effectively applied in accident investigations, although the calculation of cost benefit analysis for warships can be ignored because the Warship task cannot be compared to the value of money.  Keywords: Task Operation, Warship, FSA, fault tree analysis, event tree analysis

Challenges and Developments in Navigational Risk Assessment With Large Uncertainty

2014 ◽  
Author(s):  
Xinping Yan ◽  
Jinfen Zhang ◽  
Di Zhang ◽  
Carlos Guedes Soares
Keyword(s):  
Risk Assessment ◽  
Safety Assessment ◽  
Oil Spills ◽  
Rule Base ◽  
Event Tree ◽  
Event Tree Analysis ◽  
General Application ◽  
The Past ◽  
Formal Safety Assessment ◽  
Belief Rule Base

Concerns have been raised to navigational safety worldwide because of the increasing throughput and the passing ships during the past decades while maritime accidents such as collisions, groundings, overturns, oil-spills and fires have occurred, causing serious consequences. Formal Safety Assessment (FSA) has been acknowledged to be a framework widely used in maritime risk assessment. Under this framework, this paper discusses certain existing challenges when an effective safety assessment is carried out under a variety of uncertainties. Some theories and methodologies are proposed to overcome the present challenges, e.g., Fault/Event Tree Analysis (FTA/ETA), Evidential Reasoning (ER), Bayesian Belief Network (BBN) and Belief Rule Base (BRB). Subsequently, three typical case studies that have been carried out in the Yangtze River are introduced to illustrate the general application of those approaches. These examples aim to demonstrate how advanced methodologies can facilitate navigational risk assessment under high uncertainties.

Probabilistic Tephra Hazard Assessment of Campi Flegrei, Italy

2021 ◽  
Author(s):  
Beatriz Martínez Montesinos ◽  
Manuel Titos ◽  
Laura Sandri ◽  
Sara Barsotti ◽  
Giovanni Macedonio ◽  
...  
Keyword(s):  
Hazard Assessment ◽  
Wide Spectrum ◽  
Numerical Code ◽  
Campi Flegrei ◽  
Computational Domain ◽  
Event Tree ◽  
Hazard Maps ◽  
Event Tree Analysis ◽  
Short And Long Term

<p>Campi Flegrei is an active volcano located in one of the most densely inhabited areas in Europe and under high-traffic air routes. There, the Vesuvius Observatory’s surveillance system, which continuously monitors volcanic seismicity, soil deformations and gas emissions, highlights some variations in the state of the volcanic activity. It is well known that fragmented magma injected into the atmosphere during an explosive volcanic eruption poses a threat to human lives and air-traffic. For this reason, powerful tools and computational resources to generate extensive and high-resolution hazard maps taking into account a wide spectrum of events, including those of low probability but high impact, are important to provide decision makers with quality information to develop short- and long- term emergency plans. To this end, in the framework of the Center of Excellence for Exascale in Solid Earth (ChEESE), we show the potential of HPC in Probabilistic Volcanic Hazard Assessment. On the one hand, using the ChEESE's flagship Fall3D numerical code and taking advance of the PRACE-awarded resources at CEA/TGCC-HPC facility in France, we perform thousands of simulations of tephra deposition and airborne ash concentration at different flight levels exploring the natural variability and uncertainty on the eruptive conditions on a 3D-grid covering a 2 km-resolution 2000 km x 2000 km computational domain. On the other hand, we create short- and long-term workflows, by updating current Bayesian-Event-Tree-Analysis-based prototype tools, to make them capable of analyze the large amount of information generated by the Fall3D simulations that finally gives rise to the hazard maps for Campi Flegrei.</p>

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