A risk assessment methodology for incorporating uncertainties using fuzzy concepts

This paper proposes a new methodology for incorporating uncertainties using fuzzy concepts into conventional risk assessment frameworks. This paper also introduces new forms of fuzzy membership curves, designed to consider the uncertainty range that represents the degree of uncertainties involved in both probabilistic parameter estimates and subjective judgments, since it is often difficult or even impossible to precisely estimate the occurrence rate of an event in terms of one single crisp probability.It is to be noted that simple linguistic variables such as ‘High/Low’ and ‘Good/Bad’ have the limitations in quantifying the various risks inherent in construction projects, but only represent subjective mental cognition adequately. Therefore, in this paper, the statements that include some quantification with giving specific value or scale, such as ‘Close to any value’ or ‘Higher/Lower than analyzed value’, are used in order to get over the limitations.It may be stated that the proposed methodology will be very useful for the systematic and rational risk assessment of construction projects.     

Human performance reliability: on-line assessment using fuzzy logic

This paper presents an on-line approach to monitoring human performance in terms of conditional reliability when one is performing a task. Unlike traditional human reliability analysis, this approach develops a dynamic model that is able to cope with constantly changing conditions that affect operator performance. A fuzzy knowledge-based assessment approach is developed in order to deal with uncertainty and subjectivity associated with human performance assessment. This technology includes three main parts/functions: (i) on-line performance monitoring; (ii) real-time performance forecasting; and (iii) performance reliability assessment. The technology is demonstrated in real-time and provides timely conditioned reliability information regarding task success/failure. In general, this technology offers human reliability assessment under highly dynamic circumstances.     

Applying fuzzy logic and constraint networks to a problem of manufacturing flexibility

The primary contribution is to present an application of fuzzy logic and constraint networks to a problem of manufacturing flexibility. The paper begins with a literature review showing the different approaches when measuring manufacturing flexibility. Next, it provides a brief review of fuzzy logic and its applications, explaining how it enhances the ability to model flexibility strategies. Then, the application is presented and its utility is demonstrated with an example from the production of printed circuit boards. Finally, the paper concludes with comments on how this model could be expanded to other applications.     

基于模糊证据理论的船舶安全评估

针对船舶安全评估过程中的诸多不确定因素，提出了一种基于模糊证据理论的安全评估方法,将证据体空间中的事件视为模糊子集，并引入模糊概率，更好地描述了专家意见（或知识），给出了质量分配函数的表示．最后，结合某船舶系统，给出了其安全评估的具体实现过程．结果表明，该方法可靠、有效.     

Linear defuzzified output of fuzzy controllers via mixed fuzzy logic operators

Abstract

The linear defuzzified output of a fuzzy controller with two fuzzy variable inputs and one output is discussed in this paper. Arbitrary amounts of triangular fuzzy numbers are employed to fuzzify the linguistic variables in fuzzy control rules. We show that the defuzzified output is exactly equivalent to a linear function of the inputs to the fuzzy controller by using three mixed fuzzy logic operators to evaluate the control rules.     

基于群体可拓模糊理论的地铁运营火灾风险评估

目的:预防地铁火灾的发生,为降低地铁火灾风险提供科学依据。方法:采用群决策、可拓学和模糊数学的方法建立基于群体可拓模糊理论的地铁运营火灾风险评估模型,并以N市某地铁站作为实例进行分析。结果:N市某地铁站的运营火灾风险水平处于"较安全"的状态,其中,D疏散能力和F_1内部环境是关键因素,需要采取一系列有效的安全对策措施提升因素的安全水平;A火源、F环境情况还有待加强;B防火性能、C灭火能力和E安全管理情况应持续严格管控。结论:基于群体可拓模糊理论的地铁运营火灾风险评估模型具有实用性,可为地铁运营火灾风险评估提供参考。     

一种实用的自组织模糊控制器设计方法

介绍一种基于模糊智能比例因子自调整的自组织模糊控制器设计方法 ,给出这种模糊控制器与常规模糊控制器在性能指标上的比较结果 .     

Uncertainty quantification in dynamic system risk assessment: a new approach with randomness and fuzzy theory

Quantifying uncertainty during risk analysis has become an important part of effective decision-making and health risk assessment. However, most risk assessment studies struggle with uncertainty analysis and yet uncertainty with respect to model parameter values is of primary importance. Capturing uncertainty in risk assessment is vital in order to perform a sound risk analysis. In this paper, an approach to uncertainty analysis based on the fuzzy set theory and the Monte Carlo simulation is proposed. The question then arises as to how these two modes of representation of uncertainty can be combined for the purpose of estimating risk. The proposed method is applied to a propylene oxide polymerisation reactor. It takes into account both stochastic and epistemic uncertainties in the risk calculation. This study explores areas where random and fuzzy logic models may be applied to improve risk assessment in industrial plants with a dynamic system (change over time). It discusses the methodology and the process involved when using random and fuzzy logic systems for risk management.     

Applying concepts of diffusion research in an informetric study

The frame of reference of the study consists of theoretical concepts adopted from the diffusion of innovations theory. The study focuses on the diffusion of a formerly national scientific journal toward a more international audience, and on factors that have influenced the diffusion. The study is part of a larger project aiming to construct a model that describes the diffusion of a scientific journal towards an international audience based on the diffusion theory and a model of information acquisition.     

A fuzzy logic modelling of dynamic scheduling in FMS

This paper is concerned with scheduling in flexible manufacturing systems (FMSs) using a fuzzy logic (FL) approach. Four fuzzy input variables: machine allocated processing time, machine priority, due date priority and setup time priority are defined. The job priority is the output fuzzy variable, showing the priority status of a job to be selected for next operation on a machine. The model will first select the machines and then assign operations based on a multi-criteria scheduling scheme. The performance of the approach is compared against established methods reported in the literature. The performance measures considered average machine utilisation, meeting due dates, setup times, work in process and mean flow times. The test results demonstrate the superiority of the fuzzy logic approach in most performance measures.     

A supplier selection model: a comparison of fuzzy logic and the analytic hierarchy process

This paper aims to compare two tools for decision makers that intend to support the decision of the selection of the appropriate supplier. Suppliers are crucial to both the efficiency and effectiveness of the performance of companies. A critical success factor of these companies is the selection of the appropriate supplier. A methodology is proposed to optimise the evaluation process based on different criteria. The proposed approach extends the one proposed by Ordoobadi (2009 Ordoobadi, SM. 2009. Development of a supplier selection model using fuzzy logic. Supply Chain Management: An International Journal, 14(4): 314–327. [Crossref], [Web of Science ®] , [Google Scholar], Development of a supplier selection model using fuzzy logic. Supply Chain Management: An International Journal, 14 (4), 314–327) who proposed the application of fuzzy logic (FL) where we use the same example case study in order to compare the analytic hierarch process (AHP) with FL. In this paper we demonstrate how we can achieve the same objective of expressing human assessments in the form of linguistic expressions by using AHP. Moreover, we demonstrate the capability to run a sensitivity analysis which helps to understand the causal relationships among the different factors. We demonstrate how this capability can help us to explain and predict the different relationships among criteria and alternatives. Moreover, we provide a measure that is able to capture the consistency of the decision maker's preferences. In our approach we provide a single unit of scale that is not only capable of ranking suppliers but also provides an understanding of the difference in scale between different suppliers which can then help to allocate resources accordingly. These facilities are not offered by Ordoobadi (2009 Ordoobadi, SM. 2009. Development of a supplier selection model using fuzzy logic. Supply Chain Management: An International Journal, 14(4): 314–327. [Crossref], [Web of Science ®] , [Google Scholar]). The proposed approach here can help companies to identify the best supplier in changing environments. The paper describes a decision model that incorporates a decision maker's subjective assessments and applies a multiple criteria decision making technique to manipulate and quantify these assessments. Unlike many similar studies, two techniques have been performed on the same case study in order to improve our understanding of the differences in the proposed techniques.     

Toward clean environment: evaluation of solar electric power technologies using fuzzy logic

The rapid expansion of the use of solar energy power plants worldwide is a subject that is being followed with interest. Fuzzy logic methodology is used for evaluating the solar thermal power technology, it compresses huge amount of data into smaller sets, and it has the ability to decide between different solar technologies on the basis of their benefits and costs. The most often considered solar technologies were parabolic trough, central receiver, dish sterling engine, compact linear Fresnel reflector (CLFR), solar chimney, photovoltaic (PV), and solar pond. The aim of our research is to provide the needed information to make a judgment or a decision of adopting the most preferred solar technology in terms of installation and development using fuzzy set methodology. The criteria of the evaluation were based on different parameters, i.e., power capacity, efficiency, availability, capacity factor, storage capability, cost, maturity, water usage, land usage, and safety. The key barriers and features for each technology on the basis of benefit-to-cost ratios are addressed. The results showed that CLFR was found to be the best choice in terms of research, development, and implementation, followed by parabolic trough technology, then the central receiver technology, dish sterling engine, solar chimney, PV, and solar pond, according to the order of preference.     

Modeling uncertainty in risk assessment: An integrated approach with fuzzy set theory and Monte Carlo simulation

Modeling uncertainty during risk assessment is a vital component for effective decision making. Unfortunately, most of the risk assessment studies suffer from uncertainty analysis. The development of tools and techniques for capturing uncertainty in risk assessment is ongoing and there has been a substantial growth in this respect in health risk assessment. In this study, the cross-disciplinary approaches for uncertainty analyses are identified and a modified approach suitable for industrial safety risk assessment is proposed using fuzzy set theory and Monte Carlo simulation. The proposed method is applied to a benzene extraction unit (BEU) of a chemical plant. The case study results show that the proposed method provides better measure of uncertainty than the existing methods as unlike traditional risk analysis method this approach takes into account both variability and uncertainty of information into risk calculation, and instead of a single risk value this approach provides interval value of risk values for a given percentile of risk. The implications of these results in terms of risk control and regulatory compliances are also discussed.     

Security risks and probabilistic risk assessment of glazing subject to explosive blast loading

A probabilistic risk assessment (PRA) procedure is developed which can predict risks of explosive blast damage to built infrastructure. The present paper focuses on window glazing since this is a load-capacity system which, when subject to blast loading, has caused significant damage and injury to building occupants. Structural reliability techniques are used to derive fragility and blast reliability curves (BRCs) for annealed and toughened glazing subjected to explosive blast, for a variety of threat scenarios. The probabilistic analyses include the uncertainties associated with blast modelling, glazing response and glazing failure criteria. Damage risks are calculated for an individual window and for windows in the facade of a multi-storey commercial building. If threat probabilities can be estimated then the paper shows illustrative examples of how this information, when combined with risk-based decision-making criteria, can be used to optimise risk mitigation strategies.     

Evaluation of leagility in supply chains using fuzzy logic approach

In the changing business environment, manufacturing firms can survive by catering to the dynamic demands of the modern customers. Lean principles imply zero inventory and agile principles necessitate safety inventory to tackle volatile market conditions. The leagile paradigm is gaining importance in the contemporary scenario which includes both lean and agile principles. This article presents the conceptual model of leagility imbibed with lean and agile principles. A fuzzy logic approach has been used for the evaluation of leagility in supply chains. This article is used to compute the performance of supply chains using both lean and agile concepts as leagility supply chains using a fuzzy logic approach.     

An approach of fuzzy logic evaluation and control in SPC

Quality control plays an important part in most industrial systems. Its role in providing relevant and timely data to management for decision‐making purposes is vital. A method that uses statistical techniques to monitor and control product quality is called statistical process control (SPC), where control charts are test tools frequently used for monitoring the manufacturing process. Engineers or managers can evaluate an abnormal process by using SPC zone rules in control charts. In the conventional use of the zone rules the user is only able to determine whether or not the process is out of control. What action should be taken to adjust the process is uncertain and is evaluated based on knowledge of the system and past experiences. This paper explores the integration of fuzzy logic and control charts to create and design a fuzzy–SPC evaluation and control (FSEC) method based on the application of fuzzy logic to the SPC zone rules. A simulation program implementing FSEC was written in Borland C++ 5.0 and simulation results were obtained and analysed. The abnormal processes simulated were automatically adjusted for each of the zone rules tested and showed an improved performance after the control action, thus confirming the merit of the technique as a special method with the specific numerical control action based on a quality evaluation criterion. Copyright © 2000 John Wiley & Sons, Ltd.     

Automated interpretation of LIBS spectra using a fuzzy logic inference engine

Automated interpretation of laser-induced breakdown spectroscopy (LIBS) data is necessary due to the plethora of spectra that can be acquired in a relatively short time. However, traditional chemometric and artificial neural network methods that have been employed are not always transparent to a skilled user. A fuzzy logic approach to data interpretation has now been adapted to LIBS spectral interpretation. Fuzzy logic inference rules were developed using methodology that includes data mining methods and operator expertise to differentiate between various copper-containing and stainless steel alloys as well as unknowns. Results using the fuzzy logic inference engine indicate a high degree of confidence in spectral assignment.     

Security assessment of gas networks

A measure of the severity of a pipeline failure is the minimum reduction in load in the network necessary to ensure that no node falls below its minimum pressure. The expected loss of sales is calculated as the product of the minimum reduction in load and the expected duration of the period during which the pipeline will be in the inoperable state, and thus reflects both the severity and the frequency of the failure. Consequently, this index, whose evaluation involves network theory, optimization and probability theory, serves as a measure of the insecurity of the gas network. The security index can be evaluated for all points within a system, providing a basis of comparison between the relative vulnerability of different parts. The relative level of security of different design proposals can also be assessed using this index.     

Applying a risk assessment approach for cost analysis and decision-making: a case study for a basic design engineering project

Abstract

Many uncertainties and cost variations occur in the work activities of a project, thereby causing many possibilities of under-estimating or over-estimating for a bid price. A comprehensive study for each process of risk management should be investigated to achieve project objectives. However, a limited number of studies have a comprehensive viewpoint to indicate the benefits of risk management and the effect on project performance for the engineering design stage of engineering–procurement–construction (EPC) projects, especially in the basic design stage. This research was conducted to identify and analyze the risks associated with a Basic Design Engineering (BDE) project for a high value-added petrochemical plant in Taiwan. First, a project risk management work flow was proposed as an effective tool to minimize the project risks and maximize the management capacity of practitioners. Second, the cost effect of project risks was described by conducting a case study for the design process of a high value-added petrochemical plant using a Monte Carlo simulation. A risk register was identified to support the data required for conducting simulation analysis. The results of this paper provide reference points for risk management planning of project execution and help project managers evaluate particular risks at the engineering design stage of EPC projects to avoid cost overruns.     

Dynamic response of a semiconductor gas sensor analysed with the help of fuzzy logic

Semiconductor gas sensors are essentially not selective to detect a single chemical species in a gaseous mixture and also the response of the sensor in most cases is influenced by the variations of ambient humidity and temperature. One of the solutions is the analysis of the dynamic response of a single sensor with modulated temperature. For the non-linear output signal the fast Fourier transform transform was calculated. The zero-order amplitude and the phases of higher harmonics were selected. These quantities served as input data for the fuzzy model of the sensor. The hybrid fuzzy sensor model, based essentially on Takagi-Sugeno-Kang (TSK) theory, comprised a two-level optimization algorithm. The authors elaborated that algorithm, utilizing conjugate gradient and genetic algorithm methods. At the output of the fuzzy model the concentrations of ethanol with minimized influence of humidity variations were obtained.