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One or several component failures may lead to more related component malfunction and ultimately cause system reliability reduction. Based on this, we focus on the assessment system reliability of complex electromechanical systems (CEMSs) in a fault-propagation view. First, failure propagation model taking into consideration failure data based on ne...
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... In general, any fault in any component of any system has a tendency to propagate to other components, cause components' malfunctions, and finally create failures [18]. Simulating failure uncovers the impact of any fault at a component level on other different system components. ...
One of the most popular models that provide computer resources today is cloud computing. Today’s dynamic and successful platforms are created to take advantage of various resources available from service providers. Ensuring the performance and availability of such resources and services is a crucial problem. Any software system may be subject to faults that might propagate to cause failures. Such faults with the potential of contributing to failures are critical because they impair performance and result in a delayed reaction, which is regarded as a dependability problem. To ensure that critical faults can be discovered as soon as possible, the impact of such faults on the system must be tested. The performance and dependability of cloud-native systems are examined in this empirical study using fault injection, one of the chaos engineering techniques. The study explores the impacts and results of injecting various delay times into two cloud-native applications with diverse user numbers. The performance of the applications with various numbers of users is measured in relation to these delays, which accordingly reflects measuring the dependability of those systems. Firstly, the systems’ architecture were identified, and serverless with two Lambda functions and containerised microservices applications were chosen, which depend on utilising and incorporating cloud-native services. Secondly, faults are injected in order to quantify performance attributes such as throughput and latency. The results of several controlled experiments carried out in real-world cloud environments provide exploratory empirical data, which promoted comparisons and statistical analysis that we utilised to identify the behaviour of the application while experiencing stress. Typical results from this investigation include an overall reduction in performance that is embodied in an increase in latency with injecting delays. However, a remarkable result is noticed at a particular delay in which defects and availability problems appear out of nowhere. These findings assist in highlighting the value of using chaos engineering in general and fault injection in particular to assess the dependability of cloud-native applications and to find unpredicted failures that could arise quickly from defects that aren’t supposed to spread and result in dependability issues.
... When CNC electromechanical equipment function is lost, parts processing and manufacturing will stop running, which may lead to the failure of the production task. CNC electromechanical equipment failures have size; small failures will temporarily hinder the processing and manufacturing, while large failures may cause significant economic losses and even threaten the personal safety of the staff [4][5][6]. ...
This study addresses the fault diagnosis technology of CNC electromechanical systems in mechanical engineering equipment manufacturing, and explores the fault detection methods under the influence of structural coupling to improve the accuracy and efficiency of fault diagnosis. The study first analyzes the time-domain and frequency-domain features for fault diagnosis, including quantitative and dimensionless features used to identify different types of faults. Subsequently, the study explores feature dimensionality reduction methods, including algorithms such as PCA, LLE and t-SNE, and compares the effectiveness of their application in fault diagnosis. The research focuses on proposing a lightweight deep learning fault diagnosis framework called LTCN-BLS, which combines 2-DLTCN and 1-DLTCN branches, and an ILAEN-based BLS classifier to effectively extract and fuse time-domain and time-frequency-domain features of the data. The experimental results show that the LTCN-BLS framework has high accuracy and low network complexity in fault diagnosis, and has obvious advantages in early fault monitoring, degradation assessment, and robustness compared with traditional methods.
... System reliability refers to the ability of a system's components to perform correctly for a given period under specific conditions [1]. Estimating the reliability of complicated systems is often challenging due to their multiple components, the functional interdependence of these components, and complex topologies. ...
Reliability is a critical issue in vehicular networks. A deep learning (DL) method is proposed in this study to automatically predict the reliability of cognitive radio vehicular networks (CR-VANETs) ignored in the previous research. First, a dataset is generated based on a previously proposed method for the reliability assessment of CR-VANETs. Then, a model is proposed to predict the networks’ reliability using the DL method and compared with other machine learning methods. While machine learning methods have been applied in vehicular networks, they have not been used for reliability prediction. The proposed DL model is utilized in this research to predict CR-VANETs’ reliability. Based on the results, the DL model outperforms other machine learning methods for reliability prediction. The correlation coefficient and root mean square error of the test data for the DL model are 0.9862 and 0.0381, respectively. These results indicate the CR-VANETs’ reliability prediction accurately using the proposed method.
... Berna Dengiz [5] use of computer networks has been rapidly increasing recently to share expensive various resources, and provides access to main systems from distant locations. Shuai Lin [6] explains how component failures may lead to more related component malfunction and ultimately how it impacts on reliability reduction. Kerri Morgan [7] clarifies reliability polynomial with the failure probability 1-p.. Om Prakash Yadav [8] presents a method for estimating the reliability by using ANN. ...
... The RNN reliability estimation functions in designing of network are tested by evaluating it to a simply predicted bound and exact calculation. The backpropagation training method because it's having a powerful approximation capacity [6]. Simple ANN methods are having various limitations of unexplained behavior, network structure, duration of the network and so on [17]. ...
The main problem dispersed with in this paper is to find a novel method for the improvement in the reliability analysis of Computer Network. Reliability prediction are estimated during the life cycle of a computer network with the aim of estimating failure. In designing a variable size network, the serviceability, availability and reliability of the any network is a primary consideration. The reliability calculation in varying size network is a problem of NP-hard; it requires more calculation and effort with the amplifying no of nodes and links. Many different approaches have been taken for reliability and probability calculation for triumphant communication between any pair of computers. The paper presents a method for identifying n-terminal network reliability based on RNN technique. The method derived in this paper preceding inputs which increases the speed of computation. The approach works efficiently and overcome the difficulties of the previous approaches defined with neural network model and other reliability estimation techniques. It is proposed that the RNN model be used to replace the most time-consuming component of the system reliability evaluation approach. A variable-length sequence input can be handled by RNN. The main goal of this paper is to predict asperity of reliability which is highly correlated with performance of network in any unfavorable conditions.
... A system's reliability refers to its components' ability to perform correctly for a given period under specific conditions [1]. The assessment of a system's reliability is essential for improving the dependability of the system. ...
... For each Fuzzy value, a membership function is required. We utilize the most common Fuzzy membership function (triangular) [33], expressed by (1). ...
... As mentioned previously, we use a triangular Fuzzy membership function. Here, we determine the Fuzzy values and membership functions based on the following properties, resulting in asymmetric membership functions (see Fig. 4): (1) Assuming that the acceptable level of reliability is 90%, the lowest range of the failure probability (very low) is considered between 0 and 0.1. Moreover, Fig. 4 The Fuzzy membership functions of the PRFs' effects on the activities we consider a logarithmic increase for the Fuzzy membership function range by raising the failure probability (see Table 3) and (2) The sum of the overlapping membership functions' values at each point is considered to be 1 [41]. ...
Reliability is one of the main objectives of many systems, which may be part of man-machine systems, consisting of human operators and machines working under the specified conditions. Vehicular networks are systems in which safety information must be delivered reliably and quickly to ensure the driver’s correct and timely reaction. Hence, in this paper, we propose a general framework based on fuzzy arithmetic to perform a reliability assessment of different systems with various kinds of components. Then we apply the framework to a cognitive radio vehicular ad-hoc network (CR-VANET) with drivers (CRVD system). The reliability of a CRVD system depends on different environmental, vehicular, and human-related factors that change over time. The interactions between these factors are so convoluted and subjective. Hence, reliability estimation of the system with a crisp value is difficult. Moreover, there is a lack of consideration given to driver’s reaction in the system’s reliability estimations even though it is one of the most critical safety issues in intelligent transportation systems (ITS). The reliability analysis in the present study is performed for vehicular communications with and without considering the drivers. The analytical results are supported by simulations using NS3 and compared with existing methods. The evaluation results indicate that reliability is assessed more precisely when considering the driver as one of the system’s components.
... For most industrial operations, there is no standard framework to accurately establish and assess the consequences of odd behavior, failure, or unscheduled stoppages, and therefore, decisions related to asset replacements or maintenance are made based on experience and inaccurate frameworks that usually focus on the overall process as a whole and not as part of the business process, although failure propagation has been studied in order to assess reliability [16,17], the criticality of the elements embedded in the system has not been studied. These issues push the necessity to define key performance indicators (KPI) for production systems [18] accountable for dependency and hierarchy, measuring the effectiveness of the KPI impact on every singular element of an industrial process. ...
Wastewater treatment is a critical and necessary task every human settlement is obligated to address. If not, the consequences might be catastrophic, not just for humans but for the ecosystems as well, pushing research into finding new ways to improve wastewater treatment processes to make them safer and more efficient. Hence, there is a need to address matters, such as reliability and maintainability of Wastewater Treatment Plants (WWTP), when analyzing the availability and operational conditions. These should be addressed by analyzing the plant operational effectiveness impact (P-OEI), and in this article specifically, a WWTP study case to identify design flaws or improvement opportunities. A vital aspect of a complex system is to determine the contribution to resilience, reliability, and availability of every element embedded in the system. This is performed by adapting and applying the P-OEI methodology and real data of a WWTP located in Chile. This methodology breaks down the system into several levels of disaggregation similar to RBD methodology, analyzing the upstream for availability and the downstream for the P-OEI analysis from the system itself to the individual elements within subsystems. The potential impact on the overall system’s lack of efficiency is also quantified by an Expected Operational Impact (EOI) index, which is also calculated by the methodology. The P-OEI and EOI analyses performed in this study are powerful tools to assess the design and performance of complex systems and WWTP in particular.
... e systematic studies are usually developed considering techniques and methodologies as Reliability Block Diagrams (RBDs) [11,12], Fault Trees (FTs) [13], Reliability Graphics (RGs) [14], Petri Nets (PNs) [15], and Monte Carlo simulation [16][17][18] among others. More recently, other techniques have emerged such as Multistate Systems [19], Graph Topology [20], and fuzzy approaches [3] which have allowed to reveal subjacent connections rising from the process dynamic. Another approach would be to implement specially designed algorithms to assess availability and reliability, such as computing the Equivalent Availability (EA) index that makes use of the shared load between pieces of equipment working under lower loads than their nominal capacity allowing the use of different combinations of equipment to achieve the availability goal [21]. ...
This article proposes an original probabilistic modelling methodology named Virtual Standby (VSB), which enables a practical simulation, analysis, and evaluation of the impact on availability and reliability achieved by potential buffering policies on the performance of complex production systems. Virtual Standby (VSB) corresponds to a design and operational characteristic where some machines under a failure scenario are capable to provide for a limited time, continuity to the subsystems downstream before suffering delay which is currently not considered when assessing availability. This feature plays a relevant role on the propagation of the effect of a failure; indeed, it could prevent the propagation by guaranteeing the isolation time needed to recover from its failure, controlling and reducing the production losses downstream. A case study of the preliminary treatment process of a wastewater treatment facility (WWTF) is developed bearing in mind the systemic behaviour in the event of a failure and the specific features of each equipment. VSB is a big advantage for the representation of this complex processes because, among other things, it considers the impact of buffering policies on the perceived availability of the system. This model allows determining different production levels, with a better and easier fitting of the reliability, availability, and production forecast of the process. Finally, the comparison between the VSB simulation results with traditional procedures that do not consider the operational continuity under a failure scenario confirms the strength and precision of the proposal for complex systems.
... In addition, recommendations to reduce the probability and consequences of an incident should be offered [13]. The fault tree analysis is typically applied in the reliability analysis [14][15][16].FTA is a graphical design technique [17].It is concerned with the identification and analysis ofconditions and factors that cause the occurrence of a defined top event [18]. FTA is a systematic safety analysis tool that proceeds deductively from the occurrence of an undesired event [19]. ...
The purpose of this work is to check the calculations to consolidate the safety instrumented system (SIS) in order to preserve the safety of the plant and the environment,and consider the consequences in case of failure. The application of our study will be focused ontheNaphta Stabilizer-B Reflux Drum in Skikda refinery using the combination of HAZOP-LOPA-Fault Tree methods. The aim of this paper is to verify that the intended safety integrity level of a safety instrumented system is achieved. Otherwise propose a solution to ameliorate the safety instrumented system to mitigate the studied scenario. In case of failure of the safety instumented system, severe damage to the installation and serious impact on the environment will be considered; the use of petri nets allows us to model the behavior of the system. So the objective of our work is to ensure that the appropriate and efficient safety system is installed.
... In the polychromatic theory [17] and its expanding application [18,19] ...
With the increasing complexity of modern engineering and wide application of intelligent manufacturing technology, the type and quantity of product data continue to climb, and the corresponding version iteration rate continues to accelerate. In order to achieve effective unified management and maintenance of product data and to track version evolution accurately, this paper proposes an improved polychromatic graphs-based BOM multi-view management and version control method for complex products. Firstly, the framework was established for BOM multi-view management and version control, whose mechanism was also elaborated. According to the model of multi-view-version product structure, the expression method of product structure was discussed at different stages of product life cycle. Furtherly, with multi-object constraints sets were introduced, a version control model was established based on the improved polychromatic graphs, whose definition and principle were also detailed. Finally, application cases were discussed to verify the feasibility and universality of the proposed models and methods.
... Their results showed that the network keeps the most robust when nodes with the low degree or links with high flight flow are removed. Lin et al. proposed a reliability assessment framework concerning the complex electromechanical systems from a network and the percolation theory [8,9]. Based on the proposed approaches, the reliability of the high-speed train was assessed and the effectiveness of the proposed method was verified. ...
The identification of key components is very important for the real-life system. Because the complex network is a powerful tool to analyze the behavior of the complex network, we explore the key nodes by using the complex networks. First, we utilize the degree, the betweenness, the closeness centrality, the eigenvector centrality and the Pagerank to reflect the importance of the node. Then the machine components are abstracted as a node, and the interactions are abstracted as an edge. According to the topology structure of the high-speed train, it is found that the high-speed train has the scale-free feature. By removing the nodes in the light of the sequence of nodes, we can obtain the effective measure and analyze the key nodes of the high-speed train performance degradation caused by the failure. The simulation results show that the node with the high PageRank value and degree is critical for the network. This work may contribute to the discovery of the key components in the high-speed train.
