A method to take account of inhomogeneity in mechanical component reliability calculations

YesThis paper proposes a method by which material inhomogeneity may be taken into account in a reliability calculation. The method employs Monte-Carlo simulation; and introduces a material strength index, and a standard deviation of material strength to model the variation in the strength of a component throughout its volume. The method is compared to conventional load-strength interference theory. The results are identical for the case of homogeneous material, but reliability is shown to reduce for the same load as the component volume increases. The case of a tensile bar is used to explore the variation of reliability with component volume

FRAM for systemic accident analysis: a matrix representation of functional resonance

Due to the inherent complexity of nowadays Air Traffic Management (ATM) system, standard methods looking at an event as a linear sequence of failures might become inappropriate. For this purpose, adopting a systemic perspective, the Functional Resonance Analysis Method (FRAM) originally developed by Hollnagel, helps identifying non-linear combinations of events and interrelationships. This paper aims to enhance the strength of FRAM-based accident analyses, discussing the Resilience Analysis Matrix (RAM), a user-friendly tool that supports the analyst during the analysis, in order to reduce the complexity of representation of FRAM. The RAM offers a two dimensional representation which highlights systematically connections among couplings, and thus even highly connected group of couplings. As an illustrative case study, this paper develops a systemic accident analysis for the runway incursion happened in February 1991 at LAX airport, involving SkyWest Flight 5569 and USAir Flight 1493. FRAM confirms itself a powerful method to characterize the variability of the operational scenario, identifying the dynamic couplings with a critical role during the event and helping discussing the systemic effects of variability at different level of analysis

Risk Assessment of a Tunnelling Process Using Machinery Failure Mode and Effects Analysis (MFMEA)

Abstract In recent years, risk management associated with safety and reliability of the process especially in oil and gas industry has been widely used. For this purpose, different methods of risk analysis have been developed and successfully applied. Greater levels of complexity in tunnelling using TBM (Tunnel Boring Machine) especially in gassy tunnels with a large volume of water coming out of them, allow higher chances of failure that may increase the potential for tunnelling facilities to become more hazardous. When there is an ever increasing awareness of hazardous risks that need to be managed by the industrial community, the risks need to be analyzed. This paper presents the results of a study on risk management in a tunnel excavation with TBM. MFMEA was applied to analyze the risks of a tunnelling process. In order to apply MFMEA, 7 main systems and components involved in a tunnelling process were selected and split into subsystems. In total, 71 failure modes were then postulated for all subsystems. In the next step, the effects of every failure of each subsystem were listed. Safeguards or controls that might prevent or mitigate the effects of each failure were then listed. In the final step, essential 1 remedial actions to prevent or mitigate the failure were recommended. Risk Matrix was developed for each possible failure to be used for risk ranking. For this purpose the Risk Priority Number (RPN) was estimated for each failure mode to identify the most critical failures. The results revealed that, the failure of the ventilation system (RPN=480) is the most critical failure. The TBM failure due to bad rock condition (RPN=240) and rolling stock failure due to unleveled rails (RPN= 200) are the next significant critical failures. The findings from this study were applied to a long tunnel under construction and significantly reduced the accidents during the tunnelling period. Tracking of the accidents occurred during the next 2 years showed that MFMEA is a perfect method for risk management in tunnelling process as well. Key Words: Hazards Identification; Risk Analysis; Risk Management, Tunnelling

Optimal control of the heave motion of marine cable subsea-unit systems

One of the key problems associated with subsea operations involving tethered subsea units is the motions of support vessels on the ocean surface which can be transmitted to the subsea unit through the cable and increase the tension. In this paper, a theoretical approach for heave compensation is developed. After proper modelling of each element of the system, which includes the cable/subsea-unit, the onboard winch, control theory is applied to design an optimal control law. Numerical simulations are carried out, and it is found that the proposed active control scheme appears to be a promising solution to the problem of heave compensation

Warranty Data Analysis: A Review

Warranty claims and supplementary data contain useful information about product quality and reliability. Analysing such data can therefore be of benefit to manufacturers in identifying early warnings of abnormalities in their products, providing useful information about failure modes to aid design modification, estimating product reliability for deciding on warranty policy and forecasting future warranty claims needed for preparing fiscal plans. In the last two decades, considerable research has been conducted in warranty data analysis (WDA) from several different perspectives. This article attempts to summarise and review the research and developments in WDA with emphasis on models, methods and applications. It concludes with a brief discussion on current practices and possible future trends in WDA

Metamodel-based importance sampling for the simulation of rare events

In the field of structural reliability, the Monte-Carlo estimator is considered as the reference probability estimator. However, it is still untractable for real engineering cases since it requires a high number of runs of the model. In order to reduce the number of computer experiments, many other approaches known as reliability methods have been proposed. A certain approach consists in replacing the original experiment by a surrogate which is much faster to evaluate. Nevertheless, it is often difficult (or even impossible) to quantify the error made by this substitution. In this paper an alternative approach is developed. It takes advantage of the kriging meta-modeling and importance sampling techniques. The proposed alternative estimator is finally applied to a finite element based structural reliability analysis.Comment: 8 pages, 3 figures, 1 table. Preprint submitted to ICASP11 Mini-symposia entitled "Meta-models/surrogate models for uncertainty propagation, sensitivity and reliability analysis