Using EWGM Method to Optimise the FMEA as a Risk Assessment Methodology

YesFailure 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 paper 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, and facilitating an effective risk ranking by offering a unique value for each risk. The proposed methodology focuses not only on high severity values for risk ranking but also it 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 odor, and production.This research has been supported by Hashemite University, Jordan

Risk Evaluation in Failure Mode and Effects Analysis Using Fuzzy Measure and Fuzzy Integral

Failure mode and effects analysis (FMEA) is a popular and useful approach applied to examine potential failures in different products, designs, processes, and services. As a vital index, the risk priority number (RPN) can determine the risk priorities of failure modes by some risk factors such as occurrence (O), severity (S), and detection (D). However, in FMEA, the traditional risk priority number approach has some shortcomings, especially in setting the weight of risk factors. This paper presents an improved risk priority number approach based on a fuzzy measure and fuzzy integral. A fuzzy measure is used to reflect the importance of the individual indicators and the indicator set and a fuzzy integral is a nonlinear function defined on the basis of fuzzy measure. The weights of risk factors given by domain experts are seen as fuzzy densities to generate a λ -fuzzy measure which can reflect the weights’ difference and relevance about risk factors. Then, the Choquet integral is used to fuse every value of risk factors about failure modes so as to obtain the comprehensive evaluation result. The result can reflect the comprehensive risk level, so it has a definite physical significance. Finally, an illustrative example and a comparison with another approach are given to show the effectiveness of the proposed approach in the paper

System analysis of fatigue in pilots and co-pilots executing short-hall flight operations

Background: This study was conducted as part of Denel’s South African Regional Aircraft (SARA) development project. Regional aircraft have a maximum flight time of 60 minutes. Hence, the study focuses on matters pertaining to the short-haul flight context. Pilot fatigue has been recognised as a safety concern in the aviation industry. It impacts on pilot performance across the board, not least in the short-haul context. However, the specific factors that lead to pilot fatigue in short-haul operations have not been well researched. Research Aim: To identify and examine the factors which influence pilot/co-pilot fatigue in short-haul aviation contexts. Method: Fatigue is multifaceted, and has multiple definitions and descriptions. It is acknowledged as a complex phenomenon, the development of which is dynamically influenced by various factors. Thus, a systems approach based on the work system model by Smith and Carayon-Sainfort (1989) was adopted for this study. A systems analysis was conducted in two parts: 1) a literature analysis, and 2) expert interviews. Results: Both the literature analysis and the interviews indicated that pilot fatigue in short-haul flight operations represent composite system outcomes influenced by various factors. The factors identified were structured (systematised) into categories, namely organizational factors, task-related factors, environmental factors, factors linked to technology and tools, and non-work-related factors specific to the individual pilot. An example of a task-related factor would be the performance by pilots of multiple take-offs and landings; organizational factors include work time arrangements and duty scheduling (e.g. unpredictable schedule, early starts/late finishes, number of flight sectors in a shift, extended working hours, numerous consecutive work days, standby duties, flight, duty and rest limitations (regulations and guidelines); and short turnaround periods); environmental factors might include the small pressurised cockpit environment, movement restriction, very low humidity, low air pressure, vibrations, high noise levels, low light intensity light, and inclement weather); there are many examples of how tools and technology utilized by pilots might affect their fatigue levels; and finally, pilot-specific non-work-related factors would include things like the pilot’s age, health (lifestyle), family stress, work experience and sleep environment. All of these factors were identified during the literature analysis and have a significant bearing on how fatigue could present in short-haul pilots/co-pilots. Other important fatigue-related factors revealed during the expert interviews included, organizational culture, time management, health implications of fatigue, and management of fatigue. Conclusions: Pilot fatigue is a complex and multi-factorial physiological condition. There are many interacting components which contribute to pilot fatigue in short-haul operations. These should be viewed from an integrated perspective and holistic, systems-based approaches should be taken to manage these issues, particularly in the context of short-haul operations. This would optimize pilot performance and well-being and, most importantly, improve the safety of the work environment to enhance overall operation safety. Limitations: The study does not quantify the contributions made to pilot fatigue by the various factors explored. Therefore, care needs to be taken when designing and implementing interventions based on this research

Avaliação do risco em ativos físicos baseada numa metodologia Fuzzy-FMEA

Trabalho final de mestrado para obtenção do grau de mestre em Engenharia MecânicaNo contexto atual, a sustentabilidade das organizações surge como um aspeto essencial e transcendente aos demais departamentos de uma organização, desde a conceção de produto à responsabilidade social que a organização contribui com esse produto. No âmbito da área industrial da presente era tecnológica, é necessário delinear e construir estratégias de negócio que permitam não só garantir a competitividade do produto, quer em aspetos qualitativos, quer em aspetos monetários, como também eliminar deficiências no desempenho global de uma organização, destacando as deficiências de produção, manutenção e as resultantes das anteriores. A fim de colmatar tais deficiências no sector da Manutenção Industrial, foram desenvolvidas técnicas analíticas que apoiam a tomada de decisão no planeamento das ações de manutenção dos demais ativos físicos. A presente dissertação foca-se na metodologia FMEA e limitações respetivas, propondo uma solução que tenha a capacidade de as mitigar. Esta solução agrega a metodologia FMEA a uma sequência de metodologias de decisão baseada em multicritérios, em concreto o Analytical Hierarchy Process (AHP) e a Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). O enquadramento da lógica Fuzzy na metodologia proposta, permite que seja quantificada a incerteza humana no processo de tomada de decisão. Esta abordagem permite propor uma priorização mais expedita de 110 potenciais modos de falha de um caso de estudo, minimizando perdas na produção e aumentando o conforto e segurança dos colaboradores de uma organização, entre outros aspetos fundamentais ao sucesso da mesma.The sustainability of organizations is an important element to be considered in every department of an organization, from the product design to the organizations’ social responsibility on that product and how it contributes to society. As the present technological industrial sector grows, there’s an urgent need to draw and develop new business strategies which not only ensures product competitiveness, in matters of quality and economy, but also allows identifying the deficiencies in the overall performance of an industrial organization, particularly the deficiencies of the industrial process, of production and maintenance and those resulting from the previous. In order to solve those issues in the field of Industrial Maintenance, were created several analytical techniques which identify and rank the critical events of the equipment. The present dissertation focuses on the FMEA methodology and its limitations, proposing a methodology to mitigate them. This solution proposes one methodology which adds to the FMEA methodology a sequence of multicriteria decision making approaches (MCDM), specifically the Analytical Hierarchy Process (AHP) and the Technique for Order Preference for Similarity to the Ideal Solution (TOPSIS). The framing of Fuzzy Logic in this proposed methodology allows human uncertainty to be quantified in the decision-making process. This approach makes it possible to propose a prioritization of the 110 potential failure modes in a real a case study, minimizing losses in production and increasing the comfort and safety of the employees of the organization, among other aspects essential to its success.N/

ADVANCED RISK MANAGEMENT OF AN ARCTIC MARINE SEISMIC SURVEY OPERATION

This research is motivated by the lack of a robust risk management framework addressing the high risks in Arctic Marine Seismic Survey Operations (AMSSO), and the lack of transparent decision-making in Arctic shipping risk management globally. The literature review carried out herein reveals that the AMSSO and Arctic navigation involve significant risks caused by human elements and the unique features of this region. These known risk factors combine to constitute a ship-ice collision risk. This last represents the goal of the research investigation. With the complexity of the AMSSO system, three technical chapters are proposed to analyse and reduce the risks in the AMSSO. The first technical chapter deals with local risk analysis of the system. Herein, a Fuzzy Rule-based methodology is developed employing the probability distribution assessment in the form of belief degrees with Bayesian Network (BN) and Failure Mode and Effect Analysis (FMEA) for estimating the risk parameters of each hazard event using a computer-aided analysis. A case study of the application of the proposed risk model – Fuzzy Rule-based Bayesian Network (FRBN) –, in the Greenland, Iceland and Norwegian Seas (GNIS) AMSSO is carried out to identify the most critical hazard event in the prospect oil field. The second technical chapter deals with the global safety performance of the Ship-Ice Collision model dovetailing the Evidential Reasoning (ER) technique and Analytic Hierarchy Process (AHP) with the FRBN. A trial application of the global safety performance of the Ship-Ice Collision case in a prospect oil field is carried out to determine the safety level of AMSSO, measured against a developed benchmark risk. The outcome of the investigation reveals the Risk Influence Factor (RIF) of each hazard event in AMSSO. Since the risk level is far above the tolerable region of the developed benchmark risk, several Risk Control Options (RCOs) are investigated in the last technical chapter to reduce and control the critical risks. This technical chapter finalises the risk management framework developed in this research. In a trial application of reducing a critical risk in AMSSO, AHP-TOPSIS is utilised to find a balance between cost and benefit in selecting the most appropriate RCO at the heart of several RCOs and their associated criteria. The novelty of this research lies in the fact that it tackles the major concerns in risk analysis (concerns such as dynamic event risk analysis, hazard data uncertainties, and hazard event dependencies) of a complex system. More also, it adopts a hybrid methodology that offers a non-monotonic utility output to select the most appropriate RCO amongst several RCOs and conflicting criteria, to reduce the critical risks in AMSSO, in an economically viable strategy