A Novel Approach to Ship Operational Risk Analysis Based on D-S Evidence Theory

2021 ◽  
pp. 728-741
Author(s):  
Tao Liu ◽  
Yuanzi Zhou ◽  
Junzhong Bao ◽  
Xizhao Wang ◽  
Pengfei Zhang
Keyword(s):  
Risk Analysis ◽  
Evidence Theory ◽  
Operational Risk ◽  
Novel Approach

A New Tool for Prioritising the Risk of Failure Modes for Marine Machinery Systems

2014 ◽  
Author(s):  
Ikuobase Emovon ◽  
Rosemary A. Norman ◽  
Alan J. Murphy
Keyword(s):  
Risk Analysis ◽  
Failure Modes ◽  
Evidence Theory ◽  
Risk Priority Number ◽  
Averaging Technique ◽  
Risk Criteria ◽  
Novel Approach ◽  
Mode Effect ◽  
Simple Average

Failure Mode Effect and Analysis (FMEA) is one of the most powerful techniques for performing risk analysis for marine machinery systems, with risk being quantified through evaluating Risk Priority Numbers (RPNs) for all failure modes of the systems. The RPN is traditionally evaluated as the product of three risk criteria; occurrence (O), severity (S) and Detection (D). FMEA has several limitations such as the challenge of aggregating experts’ risk criteria rating that may be imprecise or incomplete. In this paper some of the limitations in the conventional FMEA technique are addressed using two approaches; AVeraging technique integrated with conventional Risk Priority Number (AVRPN) and AVeraging technique integrated with TOPSIS (AVTOPSIS). Both proposed techniques use a novel approach simple average in aggregating imprecise experts’ risk criteria ratings. A case study illustrates the suitability of both techniques for use in risk prioritisation jointly or independently as the results generated by both techniques are very similar. Furthermore, the AVRPN technique has been applied to an example from the literature and it has been demonstrated to be both computationally simple and capable of producing results which almost completely match those generated by modified Dempster-Shafer evidence theory techniques.

An operational risk analysis tool to analyze marine transportation in Arctic waters

2018 ◽  
Vol 169 ◽  
pp. 485-502 ◽  
Author(s):  
Bushra Khan ◽  
Faisal Khan ◽  
Brian Veitch ◽  
Ming Yang
Keyword(s):  
Risk Analysis ◽  
Operational Risk ◽  
Analysis Tool ◽  
Marine Transportation

An operational risk analysis of Iran Buyback contract and its policy implication

2017 ◽  
Vol 16 ◽  
pp. 43-53 ◽  
Author(s):  
Chengyuan Li ◽  
Mingjun Jiang ◽  
Haiming Ge ◽  
Zhen Li ◽  
Dongkun Luo
Keyword(s):  
Risk Analysis ◽  
Policy Implication ◽  
Operational Risk ◽  
Buyback Contract

scholarly journals Toward Business Integrity Modeling and Analysis Framework for Risk Measurement and Analysis

2020 ◽  
Vol 10 (9) ◽  
pp. 3145 ◽  
Author(s):  
Victor Chang ◽  
Raul Valverde ◽  
Muthu Ramachandran ◽  
Chung-Sheng Li
Keyword(s):  
Risk Analysis ◽  
Tax Evasion ◽  
Financial Services ◽  
Predictive Analytics ◽  
Operational Risk ◽  
Regulatory Compliance ◽  
Heston Model ◽  
Business Strategies ◽  
Modeling And Analysis ◽  
Risk Research

Financialization has contributed to economic growth but has caused scandals, misselling, rogue trading, tax evasion, and market speculation. To a certain extent, it has also created problems in social and economic instability. It is an important aspect of Enterprise Security, Privacy, and Risk (ESPR), particularly in risk research and analysis. In order to minimize the damaging impacts caused by the lack of regulatory compliance, governance, ethical responsibilities, and trust, we propose a Business Integrity Modeling and Analysis (BIMA) framework to unify business integrity with performance using big data predictive analytics and business intelligence. Comprehensive services include modeling risk and asset prices, and consequently, aligning them with business strategies, making our services, according to market trend analysis, both transparent and fair. The BIMA framework uses Monte Carlo simulation, the Black–Scholes–Merton model, and the Heston model for performing financial, operational, and liquidity risk analysis and present outputs in the form of analytics and visualization. Our results and analysis demonstrate supplier bankruptcy modeling, risk pricing, high-frequency pricing simulations, London Interbank Offered Rate (LIBOR) rate simulation, and speculation detection results to provide a variety of critical risk analysis. Our approaches to tackle problems caused by financial services and the operational risk clearly demonstrate that the BIMA framework, as the outputs of our data analytics research, can effectively combine integrity and risk analysis together with overall business performance and can contribute to operational risk research.

Operational Risk Analysis ToolOPERAtofor Oil and Gas Activities

2011 ◽  
Vol 2011 (1) ◽  
pp. abs259 ◽  
Author(s):  
Randi Kruuse-Meyer ◽  
Anders Bergsli ◽  
Anders Rudberg ◽  
Helene Østbøll
Keyword(s):  
Risk Analysis ◽  
Oil And Gas ◽  
Operational Risk

scholarly journals Operational risk analysis model used by the border police of the Republic of Serbia

2016 ◽  
Vol 58 (3) ◽  
pp. 25-45
Author(s):  
Sinisa Dostic ◽  
Darko Markovic
Keyword(s):  
Risk Analysis ◽  
Operational Risk ◽  
Analysis Model ◽  
The Republic
Sign in / Sign up

Export Citation Format

Share Document