Risk Assessment of a Wind Turbine: A New FMECA-Based Tool With RPN Threshold Estimation

A wind turbine is a complex system used to convert the kinetic energy of the wind into electrical energy. During the turbine design phase, a risk assessment is mandatory to reduce the machine downtime and the Operation & Maintenance cost and to ensure service continuity. This paper proposes a procedure based on Failure Modes, Effects, and Criticality Analysis to take into account every possible criticality that could lead to a turbine shutdown. Currently, a standard procedure to be applied for evaluation of the risk priority number threshold is still not available. Trying to fill this need, this paper proposes a new approach for the Risk Priority Number (RPN) prioritization based on a statistical analysis and compares the proposed method with the only three quantitative prioritization techniques found in literature. The proposed procedure was applied to the electrical and electronic components included in a Spanish 2 MW on-shore wind turbine

A review of applications of fuzzy sets to safety and reliability engineering

Safety and reliability are rigorously assessed during the design of dependable systems. Probabilistic risk assessment (PRA) processes are comprehensive, structured and logical methods widely used for this purpose. PRA approaches include, but not limited to Fault Tree Analysis (FTA), Failure Mode and Effects Analysis (FMEA), and Event Tree Analysis (ETA). In conventional PRA, failure data about components is required for the purposes of quantitative analysis. In practice, it is not always possible to fully obtain this data due to unavailability of primary observations and consequent scarcity of statistical data about the failure of components. To handle such situations, fuzzy set theory has been successfully used in novel PRA approaches for safety and reliability evaluation under conditions of uncertainty. This paper presents a review of fuzzy set theory based methodologies applied to safety and reliability engineering, which include fuzzy FTA, fuzzy FMEA, fuzzy ETA, fuzzy Bayesian networks, fuzzy Markov chains, and fuzzy Petri nets. Firstly, we describe relevant fundamentals of fuzzy set theory and then we review applications of fuzzy set theory to system safety and reliability analysis. The review shows the context in which each technique may be more appropriate and highlights the overall potential usefulness of fuzzy set theory in addressing uncertainty in safety and reliability engineering

A MODIFIED FMEA APPROACH BASED INTEGRATED DECISION FRAMEWORK FOR OVERCOMING THE PROBLEMS OF SUDDEN FAILURE AND ACCIDENTAL HAZARDS IN TURBINE AND ALTERNATOR UNIT

The proposed work presents a novel integrated decision framework, based on Intuitionistic Fuzzy (IF)- Failure Mode & Effect Analysis (IF-FMEA), and IF-Technique for Order of Preference by Similarity to Ideal Solution (IF-TOPSIS) approaches for analysing the failure risk issues of Turbine and Alternator Unit (TAU) in a chemical treatment-based sugar process industry. The proposed novel IF-FMEA approach-based modelling overcomes the various demerits of traditional FMEA approaches which are faced during the identification of critical failure causes based on Risk Priority Number (RPN) outputs. On the basis of detailed qualitative information related to plant operation, FMEA sheet was developed and linguistic ratings were collected against three risk factors such as probability of Occurrence (O), Severity (S), and Detection (D). IF- Hybrid Weighted Euclidean Distance (IFHWED) score has been computed to rank all listed failure causes under three risk factors. The ranking results based on IF-FMEA approach has been compared with the well existed IF-TOPSIS approach for evaluating the accuracy of proposed modelling results. Sensitivity analysis has been also done for checking the robustness of the framework. The analysis results were provided to maintenance executives of the TAU unit to frame optimum maintenance plan for overcoming the problems of sudden breakdown. The analysis results are also applicable to TAU systems which are installed in other chemical process industries globally.

Improving patient safety through human-factor-based risk management

AbstractNational and international efforts under the initiative ‘patient safety’ aim for more safety and transparency within healthcare systems for both patients and professionals. Within the healthcare sector, workflows become more and more complex, while time and money become scarce. As the consequence, the risk awareness, fault management and quality aspects in general become more important. One of the most established risk assessment methods is Failure Mode and Effect Analysis (FMEA) – a reliability analysis and risk assessment tool widely used in various industries. The traditional FMEA is using a Risk Priority Number (RPN) ranking system to evaluate and identify the risk level of failures, and to prioritize actions. However, there are shortcomings in obtaining a quality estimate of the failure ratings with FMEA, especially when human factors play a role, as it is in healthcare. Thus, a new risk assessment method named HFdFMEA (Human Factor dependent FMEA) based on dependency of used parameters and observation of human factors, is proposed to address these drawbacks. The results of this paper show that the HFdFMEA does not only increase risk level of failures based on the inclusion of human-factors but also gives the possibility to reduce the risk level of failures through means of addressing human-factors via trainings, motivation, etc. Finally, we discuss the opportunity to improve patient safety as result of the proposed HFdFMEA, used as technique for Human-Factor-based Risk Management (RiDeM)

Food safety risk analysis from the producers' perspective: prioritisation of production process stages by HACCP and TOPSIS

[EN] From the manufacturers perspective, the Hazard Analysis and Critical Control Point (HACCP) system nowadays represents the mainly way to implement the food safety risk management in food industries. Nevertheless, the identification and prioritization of hazards as the outcome of the first principle of HACCP is not sufficient to identify production process stages that more significantly and critically contribute to the consumer¿s risks. With this recognition, the present paper proposes a Quantitative Risk Assessment (QRA) approach based on HACCP and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) to individuate production process phases on which implementing corrective actions to improve the consumers¿ safety. The designed methodological approach is implemented on the smoked salmon manufacturing process of a real Sicilian industry.Certa, A.; Enea, M.; Galante, G.; Izquierdo Sebastián, J.; La Fata, CM. (2018). Food safety risk analysis from the producers' perspective: prioritisation of production process stages by HACCP and TOPSIS. International Journal of Management and Decision Making. 17(4):396-414. https://doi.org/10.1504/IJMDM.2018.095720S39641417

A Fuzzy Criticality Assessment System of Process Equipment for Optimized Maintenance Management.

yesIn modern chemical plants, it is essential to establish an effective maintenance strategy which will deliver financially driven results at optimised conditions, that is, minimum cost and time, by means of a criticality review of equipment in maintenance. In this article, a fuzzy logic-based criticality assessment system (FCAS) for the management of a local company’s equipment maintenance is introduced. This fuzzy system is shown to improve the conventional crisp criticality assessment system (CCAS). Results from case studies show that not only can the fuzzy logic-based system do what the conventional crisp system does but also it can output more criticality classifications with an improved reliability and a greater number of different ratings that account for fuzziness and individual voice of the decision-makers

A Framework for Sustainable Maintenance of Offshore Energy Structures

This paper proposes a structure for maintenance decision support suitable for application to renewable energy assets. The method combines subjective tacit knowledge of subject-area experts with well-structured Analytical Hierarchical Process (AHP) to elicit weights of criteria relevant for effects evaluation of possible failures modes towards support for component’s maintenance decisions. The Technique for Ordered Preference using Similarity to Ideal Solution (TOPSIS) algorithm is adopted for aggregating the evaluation scores and achieving priority indexing given the conflicting characteristics of some criteria. Part of the highlights of the Framework is the implementation of the group experts, as well as individual expert's elicitations in a complimentary manner that eliminates subjective opinions and achieves a repeatable evaluation score. The conclusion of the analysis is the prioritisation of the component’s failure; An indicative case study of offshore wind turbine jacket support structure is used to demonstrate the applicability of the approach and the analysis results-which shows priority failure modes for focused maintenance intervention as bending of Chord/Brace ( ), collapse of Chord/Brace ( ), buckling of Long piles ( ), and Truss( ), overturning of Skirt pile ( ), and fatigue of Long pile ( ), further demonstrates the capacity of the model to support maintenance decisions. Caution is exercised in the selection of criteria that would capture the objectives of the risk analyses by consulting wide range of industry experts. Keywords— AHP, Expert, Offshore energy, TOPSIS, Wind turbine Support Structur

Dynamic Risk Analysis of Construction Delays Using Fuzzy-Failure Mode Effects Analysis

Considering the tremendous losses in the worldwide economy caused by construction delays, it is essential to invest in minimizing the risks of delays. In order to make this happen, two measures should be taken: 1) The roots and fundamental causes of delay should be identified and strategies to mitigate their risks be developed (General remedy). 2) The most significant potential causes of delay in each project should be identified and these causes should be given priority to control (Project-Specific Remedy). The current research invests in both of the measures. To provide the general remedy, causes of delay in the construction industry of the United States is investigated through a national survey responded by the 224 construction experts with an average experience of over 27 years. The results of this study rank the criticality of the thirty main causes of construction delay in the U.S construction industry. The focus of the research is on the project-specific remedy. The research aims at designing a tool, which can prioritize different causes based on their criticality. This is crucial as there is often a large number of potential causes and investing in prevention of all of them is not practical. The designed tool is capable of identifying the most critical causes by assessing its status of the potential causes of delay in three elements of criticality which are: 1) The likelihood of occurrence of the cause, 2) the severity of the cause in creating delays (in case it happens), and 3) the resolvability or likelihood of handling the potential cause before it creates a delay, in case it happens. The three elements of assessment are inserted in a designed tool in Matlab®, which uses a fuzzy logic system to generate a “risk priority number’. This number is a representative of the riskiness of each potential cause. The next contribution of the research is a model that is capable of predicting the percentage of delay based on the “fuzzy risk priority number”. This model uses the output of the aforementioned fuzzy inference system to make a prediction about the percentage of delay. The model was tested by comparing its predictions with actual data (the delay that has actually happened) and has been able to predict the amount of delay with an error of less than 20%