Estimation of the failure flow of a set of passenger car doors

An estimation of the failure flows is a prerequisite for the operation of industrial products. It is based on statistical data about failures that occur within technical items in the process of their operation. In the technical product documentation, this indicator shall be featured in the “Dependability parameter estimation” section. The dependability analysis of rolling stock is still affected by the difficulty of defining the methodology for evaluating this parameter at various system levels. For the purpose of analysing a multicomponent system, a reliability block diagram should be developed, and the possible replacement (redundant) elements should be taken into consideration. Multicomponent systems are often represented through various block diagrams, where, among others, the “m-out-of-n” structure may be used referring to a system with a parallel arrangement of elements that is operable when at least m elements operate. An example of such system is a set of passenger car doors. The manufacturers and customers may have different approaches to calculating technical system dependability. First, the required dependability indicator for the entire train is defined that, in turn, defines the dependability requirements for a car. At the same time, the dependability indicator for a car is determined by the respective values of its components (subsystems, units and parts). However, the nature of the relationship between a car and its components is not always taken into account. At the same time, car manufacturers can and should define in the regulatory documentation (and later supervise in operation) the dependability indicators for a set of doors (components of a car in our case) as a single system. However, the failure criteria of a set of doors are not always defined. This paper examines the method of calculating the failure flow for a set of passenger car doors based on operational data and the failure flow of a single door. Aim. To propose a method for calculating the failure flow of a set of 6 car doors by analysing the possible reliability block diagrams with subsequent transition to transition and state graphs.Conclusions. A number of block diagrams were developed for the purpose of dependability calculation of sets of passenger car doors based on the system failure criterion. The failure flow of a set of car doors was calculated according to the developed block diagrams. It is concluded that the Markovian method of calculating the failure flow is of higher priority than the logic-and-probability approach, since it takes into account the recovery factor. A Markovian method was proposed for calculating the failure flow and recovery time of a set of car doors for the “3-out-of-4” reliability block diagram.

The Mercury Environment: A Modeling Tool for Performance and Dependability Evaluation

It is important to be able to judge the performance or dependability metrics of a system and often we do so by using abstract models even when the system is in the conceptual phase. Evaluating a system by performing measurements can have a high temporal and/or financial cost, which may not be feasible. Mathematical models can provide estimates about system behavior and we need tools supporting different types of formalisms in order to compute desired metrics. The Mercury tool enables a range of models to be created and evaluated for supporting performance and dependability evaluations, such as reliability block diagrams (RBDs), dynamic RBDs (DRBDs), fault trees (FTs), stochastic Petri nets (SPNs), continuous and discrete-time Markov chains (CTMCs and DTMCs), as well as energy flow models (EFMs). In this paper, we introduce recent enhancements to Mercury, namely new SPN simulators, support to prioritized timed transitions, sensitivity analysis evaluation, several improvements to the usability of the tool, and support to DTMC and FT formalisms.

An Efficient Library for Reliability Block Diagram Evaluation

Reliability Block Diagrams (RBDs) are widely used in reliability engineering to model how the system reliability depends on the reliability of components or subsystems. In this paper, we present librbd, a C library providing a generic, efficient and open-source solution for time-dependent reliability evaluation of RBDs. The library has been developed as a part of a project for reliability evaluation of complex systems through a layered approach, combining different modeling formalisms and solution techniques at different system levels. The library achieves accuracy and efficiency comparable to, and mostly better than, those of other well-established tools, and it is well designed so that it can be easily used by other libraries and tools.

Fleet Resilience: Evaluating Maintenance Strategies in Critical Equipment

Resilience is an intrinsic characteristic of systems. Through it, the capacity of a system to react to the existence of disruptive events is expressed. A series of metrics to represent systems’ resilience have been proposed, however, only one indicator relates the availability of the system to this characteristic. With such a metric, it is possible to relate the topological aspects of a system and the resources available in order to be able to promptly respond to the loss of performance as a result of unexpected events. This work proposes the adaptation and application of such a resilience index to assess the influence of different maintenance strategies and topologies in fleets’ resilience. In addition, an application study considering an actual mining fleet is provided. A set of critical assets was identified and represented using reliability block diagrams. Monte Carlo simulation experiments were conducted and the system availability data were extracted. Resilience indexes were obtained in order to carry out the definition of the best maintenance policies in critical equipment and the assessment of the impact of modifying system redundancies. The main results of this work lead to the overall conclusion that redundancy is an important system attribute in order to improve resiliency along time.

Availability Evaluation and Maintenance Policy of Data Center Infrastructure

The convergence of communication networks and the demand for storage and processing capacities for large amounts of information, especially in recent years, has driven requests for everything-as-a-service and has been generating, on an increasing scale, demands for new data center constructions. However, to meet dependability attributes, the design of these infrastructures needs to consider, at least, the system’s availability to be achieved. In this paper, we evaluate the availability of a Tier 1 data center infrastructure, considering the use of blade systems. We use modeling techniques based on reliability block diagrams and stochastic Petri nets to simulate a maintenance policy encompassed at different service levels (SLA). The results show dependability metrics, focusing on the availability and maintenance of these networks. We highlight the most severe difficulties in achieving high availability when there is no component redundancy, and the intervals between maintenance are long.

The Neural Modules Network with Collective Relearning for the Recognition of Diseases: Fault- Tolerant Structures and Reliability Assessment

The article presents the architecture of multi-level information-analytical system (IAS) based on the neural modules network (NMN). This network consists of neural modules which are placed at the three levels (local, region and nation geographically distributed medical centers). Procedures of learning and collectiverelearning of neural modules consider region particularities and are based on analysis, generalization and exchange of experience related to diagnosis of diseases. These procedures provide modification and filtering parameters used as input for the further learning of local and regional neural modules.A few fault-tolerant structures of NMN-based IAS are researched taking into account different options of server and communication redundancy. Reliability block diagrams for redundant IAS structures are developed and formulas for calculation of probability of upstate are analyzed.

Assessment of availability of street light system: A study of Warri, Delta State, Nigeria

The study computes the availability of street lighting system in Warri. This system under study consists of subsystems that are known as workstations. A generator and sets of street light make up a workstation. The power source and the street lighting were modeled into series and parallel combinations. Reliability Block Diagrams and Path Tracing Method were employed assuming independent failure of the components. The availability of the set of street lightings, workstations and hence the availability of the system were determined. Results of the study show that users in Cemetery road had the least availability of 62.19% for the period. The implication is that users travelling along this road experienced wide variation of light that could lead to accidents. Keywords: Availability, Street Lighting and Reliability block diagram

Verification of the IEC 61508 PFH formula for 2oo3 configuration using Markov chains and Petri nets

PurposeThe purpose of this paper is to check the consistency of the IEC 61508 standard formula related to the average failure frequency (PFH: the probability of dangerous failure per hour) for a commonly used safety instrumented system (SIS) architecture in the process industry: 2-out-of-3 voting (2oo3), also known as Triple Modular Redundancy (TMR).Design/methodology/approachIEC 61508 standard provided PFH formulas for different SIS architectures, without explanations, assuming that the SIS puts the equipment under control into a safe state on the detection of dangerous failure. This assumption renders the use of classical reliability approaches such as fault trees and reliability block diagrams impractical for PFH calculation. That said, the consistency verification was performed thanks to a dynamic and flexible reliability approach, namely Markov chains following these steps: (1) developing the multi-phase Markov chains (MPMC) model for 2oo3 configuration, (2) deducing the related classical Markov chains (CMC) model and (3) deriving a new PFH formula for the 2oo3 architecture based on the CMC model and thoroughly comparing it to that given in the IEC 61508. Moreover, 2oo3 architecture has been modeled through Petri nets for numerical comparison purposes. That comparison has been carried out between the numerical results obtained from IEC 61508 formula, the newly derived formula, Markov chains and Petri nets models.FindingsThe newly obtained formula for 2oo3 configuration contains extra terms compared with the IEC 61508 one. Therefore, this latter formula induces an underestimated PFH results, which is dangerous from a safety point of view. This fact was corroborated by the numerical comparison.Research limitations/implicationsThis paper does not consider the different configurations given in IEC 61508.Originality/valueIn our knowledge, no verification works have been conducted before on the IEC 61508 PFH formulas with shutdown capability. Therefore, the nonaccuracy of the PFH formula related to the 2oo3 has not been stated before. This paper proposes a new and more accurate formula.

Assessment of Barriers to Knowledge and Experience Transfer in Major Maintenance Activities

Systematic failure analysis generally enhances the ability of engineering decision-makers to obtain a holistic view of the causal relationships that often exist within the systems they manage. Such analyses are made more difficult by uncertainties and organisational complexities associated with critical and inevitable industrial maintenance activities such as major overhauls, outages, shutdowns, and turnarounds (MoOSTs). This is perhaps due to the ratio of tasks-to-duration typically permitted. While core themes of MoOSTs including planning, contracts, costing, execution, etc., have been the focus of most research activities, it is worth noting that the ability to successfully transfer and retain MoOSTs knowledge is still under-investigated. Effectively implementing a case study-based approach for data collection, the current study explores the harmonisation of various risk assessments (i.e., fault tree analysis and reliability block diagrams) and multicriteria decision analysis (MCDA) tools to investigate perceived barriers to MoOSTs knowledge management and experience transfer. The case study selected for this study is a dual process line all-integrated cement manufacturing plant (the largest of such process configuration in its region). The justification for this choice of industry was driven by the volume and frequency of MoOSTs executed each year (typically 4–1 per process line), thereby providing a good opportunity to interact with industrial experts with immense experience in the management/execution of MoOSTs within their industry. A multilayered methodology was adopted for information gathering, whereby baseline knowledge from an earlier conducted systematic review of MoOSTs practices/approaches provided fundamental theoretical trends, which was then complemented by field-based data (from face-to-face interviews, focus group sessions, questionnaires, and secondary information from company MoOSTs documentation). During the analysis, fault tree analysis (FTA) and reliability block diagrams (RBDs) were simultaneously used to generate the causal relationships and criticality that exist between identified barriers, while the MCDA (in this case analytical hierarchy process) was used to identify and prioritise barriers to MoOSTs knowledge management and experience transfer, based on sensitivity analysis and consistency of approach. The primary aim of this study is to logically conceptualise core barriers/limiters to knowledge in temporary industrial project environments such as MoOSTs, as well as enhance the ability of decision-makers to prioritise learning efforts. The results obtained from analysis of data identify three major main criteria (barriers) and 23 subcriteria ranked according to level of importance as indicated from expert opinions.