Process-oriented risk assessment methodology for manufacturing process evaluation

A process-oriented quantitative risk assessment methodology is proposed to evaluate risk associated with processes using modelling, simulation and decision-making approaches. For this purpose, risks involved in a process and the corresponding risk factors are identified through an objective-oriented risk identification approach. The identified risks are first analysed qualitatively in the failure mode effect and critical analysis process and then evaluated quantitatively in a simulation environment employing a process-based risk measurement model. To ease the decision-making process in case of multiple but heterogeneous risk measures, a global risk indicator is developed using the normalisation and aggregation techniques of the decision theory. Using the proposed methodology as a decision-making tool, alternative manufacturing scenarios (i.e. manufacturing process plans) are developed and ranked on the basis of desirability. Although the methodology is illustrated with a case study issued from the part manufacturing, it is also applicable to a wide range of other processes.     

Construction of event-tree/fault-tree models from a Markov approach to dynamic system reliability

While the event-tree (ET)/fault-tree (FT) methodology is the most popular approach to probability risk assessment (PRA), concerns have been raised in the literature regarding its potential limitations in the reliability modeling of dynamic systems. Markov reliability models have the ability to capture the statistical dependencies between failure events that can arise in complex dynamic systems. A methodology is presented that combines Markov modeling with the cell-to-cell mapping technique (CCMT) to construct dynamic ETs/FTs and addresses the concerns with the traditional ET/FT methodology. The approach is demonstrated using a simple water level control system. It is also shown how the generated ETs/FTs can be incorporated into an existing PRA so that only the (sub)systems requiring dynamic methods need to be analyzed using this approach while still leveraging the static model of the rest of the system.     

Multi‐bit Boolean model for chemotactic drift of Escherichia coli

Dynamic biological systems can be modelled to an equivalent modular structure using Boolean networks (BNs) due to their simple construction and relative ease of integration. The chemotaxis network of the bacterium Escherichia coli (E. coli ) is one of the most investigated biological systems. In this study, the authors developed a multi‐bit Boolean approach to model the drifting behaviour of the E. coli chemotaxis system. Their approach, which is slightly different than the conventional BNs, is designed to provide finer resolution to mimic high‐level functional behaviour. Using this approach, they simulated the transient and steady‐state responses of the chemoreceptor sensory module. Furthermore, they estimated the drift velocity under conditions of the exponential nutrient gradient. Their predictions on chemotactic drifting are in good agreement with the experimental measurements under similar input conditions. Taken together, by simulating chemotactic drifting, they propose that multi‐bit Boolean methodology can be used for modelling complex biological networks. Application of the method towards designing bio‐inspired systems such as nano‐bots is discussed.Inspec keywords: cell motility, microorganisms, Boolean functionsOther keywords: multibit Boolean approach, conventional BNs, high‐level functional behaviour, steady‐state responses, chemoreceptor sensory module, drift velocity, chemotactic drifting, multibit Boolean methodology, complex biological networks, bio‐inspired systems, multibit Boolean model, chemotactic drift, dynamic biological systems, equivalent modular structure, Boolean networks, simple construction, chemotaxis network, bacterium Escherichia coli, biological systems     

Engineering System Safety Analysis and Synthesis Using the Fuzzy Rule‐based Evidential Reasoning Approach

The main objective of this paper is to propose a framework for modelling, analysing and synthesizing system safety of engineering systems or projects on the basis of a generic rule‐based inference methodology using the evidential reasoning (RIMER) approach. The framework is divided into two parts. The first one is for fuzzy rule‐based safety estimation, referred to as a fuzzy rule‐based evidential reasoning (FURBER) approach. The second one is for safety synthesis using the evidential reasoning approach. In the FURBER framework, parameters used to define the safety level, including failure rate, failure consequence severity and failure consequence probability are described using fuzzy linguistic variables; a fuzzy rule base designed on the basis of a belief structure is used to capture uncertainty and nonlinear relationships between these three parameters and the safety level; and the inference of the rule‐based system is implemented using the evidential reasoning algorithm. Then the following steps involve synthesizing safety at higher levels of an engineering system to integrate all possible causes to a specific technical failure, or estimates made by a panel of experts. The synthesis is also based on the evidential reasoning approach. The final step describes the analysis and interpretation of the final synthesized safety of a system. The above framework has been applied to modelling system safety of an offshore and marine engineering system: the floating production storage offloading (FPSO) system. A series of case studies of collision risk between a FPSO and a shuttle tanker due to technical failure during a tandem offloading operation is used to illustrate the application of the proposed model. Copyright © 2005 John Wiley & Sons, Ltd.     

Model validation: a systemic and systematic approach

The term ‘validation’ is used ubiquitously in association with the modelling activities of numerous disciplines including social, political, natural, physical sciences, and engineering. There is however, a wide range of definitions which give rise to very different interpretations of what activities the process involves. Analyses of results from the present large international effort in modelling radioactive waste disposal systems illustrate the urgent need to develop a common approach to model validation. Some possible explanations are offered to account for the present state of affairs. We believe that a rigorous approach to validation must necessarily be based on a thorough understanding and application of the theory of simulation and modelling. The methodology developed treats model validation and code verification in a systemic and systematic fashion. In fact, this approach may be regarded as a comprehensive framework to assess the adequacy of any simulation study.     

Database development and uncertainty treatment for estimating pipe failure rates and rupture frequencies

Estimates of failure rates for nuclear power plant piping systems are important inputs to Probabilistic Risk Assessments (PRA) and risk informed applications of PRA. Such estimates are needed for initiating event frequencies for Loss of Coolant Accidents and internal flooding events and for risk informed evaluations of piping system in-service inspection programs. A critical issue in the estimation of these parameters is the treatment of uncertainties, which can exceed an order of magnitude deviation from failure rate point estimates. Sources of uncertainty include failure data reporting issues, scarcity of data, poorly characterized component populations, and uncertainties about the physical characteristics of the failure mechanisms and root causes. A methodology for quantifying these uncertainties using a Bayes' uncertainty analysis method was developed for the EPRI risk informed in-service inspection program and significantly enhanced in subsequent applications. In parallel with these efforts, progress has been made in the development of pipe failure databases that contain the quantity and quality of information needed to support piping system reliability evaluations. Examples are used in this paper to identify technical issues with previous published estimates of pipe failure rates and the numerical impacts of these issues on the pipe failure rates and rupture frequencies are quantified.     

An analytical framework for reliability growth of one-shot systems

In this paper, we introduce a new reliability growth methodology for one-shot systems that is applicable to the case where all corrective actions are implemented at the end of the current test phase. The methodology consists of four model equations for assessing: expected reliability, the expected number of failure modes observed in testing, the expected probability of discovering new failure modes, and the expected portion of system unreliability associated with repeat failure modes. These model equations provide an analytical framework for which reliability practitioners can estimate reliability improvement, address goodness-of-fit concerns, quantify programmatic risk, and assess reliability maturity of one-shot systems. A numerical example is given to illustrate the value and utility of the presented approach. This methodology is useful to program managers and reliability practitioners interested in applying the techniques above in their reliability growth program.     

Graphical fault tree analysis for fatal falls in the construction industry

The current study applied a fault tree analysis to represent the causal relationships among events and causes that contributed to fatal falls in the construction industry. Four hundred and eleven work-related fatalities in the Taiwanese construction industry were analyzed in terms of age, gender, experience, falling site, falling height, company size, and the causes for each fatality. Given that most fatal accidents involve multiple events, the current study coded up to a maximum of three causes for each fall fatality. After the Boolean algebra and minimal cut set analyses, accident causes associated with each falling site can be presented as a fault tree to provide an overview of the basic causes, which could trigger fall fatalities in the construction industry. Graphical icons were designed for each falling site along with the associated accident causes to illustrate the fault tree in a graphical manner. A graphical fault tree can improve inter-disciplinary discussion of risk management and the communication of accident causation to first line supervisors.     

A novel framework for the reliability modelling of repairable multistate complex mechanical systems considering propagation relationships

Due to the propagation, amplification, and concatenation in a failure process, the reliabilities of repairable multistate complex mechanical systems (RMCMSs) may be affected by a significant fluctuation due to a small exception associated with a reliability indicator. Focused on the problems arising from the lack of propagation relationships among fault modes, functional components, and failure causes in conventional reliability models, a novel framework for reliability modelling is proposed to comprehensively analyse the reliabilities of RMCMSs. First, the reliability models are abstracted as weighted and directed networks with five layers. Second, an improved failure mode and effects analysis (IFMEA) method combined with the D‐number method and VIKOR approach is presented to determine the importance of reliability nodes. Third, a cut set of the reliability model is generated by any exception of a reliability indicator by considering the propagation relationships, and the reliability sensibility index is defined to characterize the fluctuations in system reliability. The effectiveness of the proposed framework is demonstrated in an actual reliability modelling application. As an intuitive method, the proposed framework inherits the advantages of conventional models but overcomes the drawbacks of these existing methods. Therefore, this method can be flexibly and efficiently used in the reliability modelling of RMCMSs. Moreover, the approach provides a foundation for comprehensive and dynamic reliability analysis and the failure mechanism mining of RMCMSs, and it can be used in other engineering applications.     

SAPHIRE ‘Recover Cut Sets’ editor: a technique for automating the manipulation of PRA cut sets

The accident sequence cut sets generated for a probabilistic risk analysis generally require some manipulation to account for special modelling concerns. This paper presents a method of efficiently manipulating cut sets, specifically for the modelling concerns of (a) post-accident operator recovery actions, (b) common cause failure modelling, and (c) removal of mutually exclusive events. The method presented consists of logic rules that define a cut set search criteria and changes to be applied to the cut sets meeting the search criteria. While this method of cut set manipulation is demonstrated using the ‘Recover Cut Sets’ editor in the SAPHIRE risk assessment computer code, it is proposed that this methodology could become a standard method for cut set manipulation.     

Development of a framework for the risk assessment of Na-Tech accidental events

Natural events impacting on chemical and process plants may cause severe accidents, triggering the release of relevant quantities of hazardous substances. The present study focused on the development of the tools needed to build up a general framework allowing the extension of quantitative risk assessment procedure to include the analysis of the industrial accidents caused by natural events. Specific methods and models were developed to allow the quantitative assessment of risk caused by two categories of “Na-Tech” accidents: accidents triggered by earthquakes and accidents triggered by floods. The approach allows the identification of the different damage modes expected for process equipment and of the accidental scenarios that may be triggered. The damage models developed allow the calculation of the damage probability of equipment items due to the natural events. A specific methodology was issued to take into account the consequences of the possible contemporary failure of several process units due to the impact of the natural event. The procedure allows the calculation of the overall individual and societal risk indexes including the multiple-failure scenarios caused by the impact of natural events. The overall methodology was applied to the analysis of specific case studies.     

A recursive, time-averaged approach for fault tree quantitative analysis

A new approach in fault tree quantitative analysis, based essentially on the recursive evaluation of time-averaged reliability parameters associated with a fault tree, is presented. The methodology is a complete one covering the following problems: the evaluation of averaged unavailabilities or unreliabilities, failure and repair rates and failure and repair intensities associated with the basic events involved in a fault tree, the evaluation of unavailability or unreliability, occurrence rates and occurrence intensities associated with the top event of a fault tree, evaluation of the importance and sensitivity associated with basic events, and implicants according to different definitions. At this stage in the development of the methodology the common cause failures are not considered. Although in practice the presented algorithms have shown, in the cases of large fault trees, difficulties related to the computing speed and memory capabilities of present personal computers, the methodology remains valuable, at least by the new theoretical results.     

The assessment of the damage probability of storage tanks in domino events triggered by fire

An approach aimed to the quantitative assessment of the risk caused by escalation scenarios triggered by fire was developed. Simplified models for the estimation of the vessel time to failure (ttf) with respect to the radiation intensity on the vessel shell were obtained using a multi-level approach to the analysis of vessel wall failure under different fire conditions. Each vessel “time to failure” calculated by this approach for the specific fire scenario of concern was compared to a reference time required for effective mitigation actions and related to the escalation probability. The failure probability of each vessel was correlated to the probability of scenarios involving multiple vessel failure as a consequence of the primary fire, thus allowing a comprehensive assessment of domino scenarios triggered by fire. The application of the methodology to the analysis of several case-studies allowed the estimation of the quantitative contribution of escalation events triggered by fire to the overall individual and societal risk indexes.     

Towards a Predictive Design Methodology Based on the Physical Modelling of the Fracture of Fiber Composites

A predictive design methodology based on modelling the fracture stress (notched tensile strength) and post-fatigue residual strength of laminated fiber composites is presented. The approach is based explicitly on the development of models of the physical processes by which damage accumulates at a notch-tip and the application of these models to cross-ply laminates for a variety of material systems, including thermosetting and thermoplastic matrices containing carbon, glass and Kevlar fiber reinforcements. The effects of temperature and humidity on composite fracture can also be examined in the context of this modelling strategy.A pre-requisite of the model is that it has to be calibrated for each material system by performing tensile tests on notched and unnotched cross-ply laminate. From this initial calibration, which takes relatively little time, it is possible to apply the model to a prediction of the dependence of fracture stress on notch size; to an understanding of the effects of laminate stacking sequence (within the same cross-ply family) on fracture stress; and to provide insight into the effects of thermal or load cycling history on fatigue damage-growth and residual or fatigue strength.The advantages and deficiencies of this modelling strategy are assessed, as well as the applicability of such a physical modelling approach to the predictive design and failure of composite materials in general.     

Supply chain risk modelling and mitigation

In today’s global competitive environment, supply chains are more susceptible to vulnerability due to the increasing occurrence of internal and external risk events. In addition, the trend associated with lean management, which involves reducing inventory, leads to more dependency of supply chain partners on each other which exacerbates risk exposure of companies in the supply chain. This creates the need for more effective management of supply chain risks. In this research, a methodology based on Bow-Tie analysis and optimisation techniques is proposed to quantify and mitigate supply chain risks. The proposed methodology takes into consideration risk interconnections, and it identifies the best combination of mitigation strategies under budget constraints. A real case study from a high-end server manufacturing environment is presented. Results from the case study showed that the proposed methodology for risk modelling and mitigation can effectively be used to quantify the risks and achieve the required risk reduction at minimum cost while considering risk correlations.     

State estimation of discrete event systems for RUL prediction issue

This paper concerns Remaining Useful Life (RUL) estimation of discrete event systems. For that purpose, physics-based models with partially observed stochastic Petri nets are used to represent the system and its sensors. The advantage of the proposed modelling approach is to provide a realistic representation of the system, including the interaction between the normal behaviours and the failure processes. From the proposed modelling and collected measurements, timed trajectories, which are consistent with the observations, are obtained. Based on the event dates, our approach consists in evaluating the probabilities of the consistent behaviours using probabilistic models. State estimation is obtained as a consequence. The most probable future degradations, from the current state, are then considered and a method for fault prognosis is presented. Finally, the prognosis result is used to estimate the RUL as a time interval. A case study is proposed to show the applicability of the proposed method.     

A genetic algorithms-based approach for design of manufacturing systems: An industrial application

This paper presents a design methodology and a genetic algorithm-based approach for redesign of a manufacturing system for a small steel pre-fabricated building manufacturer. Through the application of celular manufacturing principles, we discuss the application of the design methodology that takes a topdown approach to determine system needs and a bottom-up integrated design approach to develop the configurations of the manufacturing system. The integrated design approach uses a genetic algorithm and an AutoCAD interface to minimize the inter and intra cell material movements during cell formation. A selected set of solutions obtained are further analysed using discrete event modelling and simulation. The final results presented indicate a substantial improvement in overall performance compared to the original layout. The company has implemented a modified version of the final solution and has achieved the significant improvements in material handling and overall productivity.     

Modular dynamic biomolecular modelling with bond graphs: the unification of stoichiometry,thermodynamics, kinetics and data

Renewed interest in dynamic simulation models of biomolecular systems has arisen from advances in genome-wide measurement and applications of such models in biotechnology and synthetic biology. In particular, genome-scale models of cellular metabolism beyond the steady state are required in order to represent transient and dynamic regulatory properties of the system. Development of such whole-cell models requires new modelling approaches. Here, we propose the energy-based bond graph methodology, which integrates stoichiometric models with thermodynamic principles and kinetic modelling. We demonstrate how the bond graph approach intrinsically enforces thermodynamic constraints, provides a modular approach to modelling, and gives a basis for estimation of model parameters leading to dynamic models of biomolecular systems. The approach is illustrated using a well-established stoichiometric model of Escherichia coli and published experimental data.     

Methodology for evaluation of possible consequences of accidental atmospheric releases of hazardous matter

Sites exist with high levels of risk of accidental atmospheric releases. These releases can be hazardous nuclear, chemical, and biological matter. Such accidents may occur during transport of waste, or they may be due to natural hazards, human errors, terror acts or various operations at high risk. Considering the operation of lifting and transport of the sunken Kursk nuclear submarine as an example, a methodology for risk assessment is described. This methodology includes two approaches: (1) probabilistic analysis of possible atmospheric transport pathways using trajectory modelling, and (2) evaluation of possible contamination and consequences using real-time operational atmospheric dispersion modelling. The first approach can be applied in advance of an operation during the preparation stage, the second in real time during the operation stage. For the cases considered in this study, the results of trajectory modelling are supported by the operational dispersion modelling, i.e., the westerly flow is dominant during fall occurring 79% of the time. Hence, September-October 2001 was more appropriate for the lifting and transport of the Kursk nuclear submarine in comparison with summer months, when atmospheric transport toward the populated regions of the Kola and Scandinavian Peninsulas was dominant. The suggested methodology may be applied to any potentially dangerous object involving a risk of atmospheric release of hazardous material of nuclear, chemical or biological nature.     

Morphology-controllable modeling approach for a porous scaffold structure in tissue engineering

Heterogeneous structures represent an important new frontier for twenty-first-century engineering. In this paper, based on the shape function in the finite element method, a morphology-controllable modelling approach for constructing tissue engineering (TE) bone scaffold with various irregular pores is presented. The modelling approach consists of both irregular element modelling and the whole bone scaffold modelling. Accepting the elements’ information after all-hex mesh generation as inputs, the basic pore-making element can be mapped into various irregular elements based on the shape function. In the bone scaffold modelling, the Boolean difference between the contour model of the solid entity and the pore model which can be constructed by the Boolean operation union would generate a porous bone scaffold model. Compared to the stochastic geometry method and the discrete element packing method, the bone scaffold model obtained in this paper has a continuous, smooth contour and various irregular pores. Moreover, a decrease in computational complexity is achieved in this paper.