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The reliability modeling and optimization of performance sharing systems (PSSs) are of vital importance due to their wide applications. Existing research mainly focuses on evaluating and maximizing the reliability of PSSs. However, in many practical systems, decision‐makers tend to prioritize the average cost of the system over its reliability. This paper studies the resource allocation optimization in common bus PSSs. In such systems, each unit has binary‐state random performance to satisfy the multi‐state random demand. The surplus performance can be shared via a common bus with transmission loss between the common bus and the unit. The performance allocation, performance transmission, and unsupplied demand incur costs. Resource allocation strategies are determined by optimization models considering different objective functions and constraints. Additionally, transmission loss between the common bus and the unit is considered. A genetic algorithm is employed to efficiently find the optimal allocation strategies. Numerical examples prove the effectiveness of the proposed models in improving system reliability and reducing system costs. [ABSTRACT FROM AUTHOR]

Tornadoes are intense localized convective windstorms that are among the most devastating natural hazards that occur in the United States. Although the probability of any tornado striking one particular building in any given year is quite low because of its small footprint, when strong tornadoes strike densely populated areas, the results can be catastrophic; the Joplin, MO tornado of 2011 caused 161 fatalities and nearly $3 billion in damages. Such losses are projected to increase in the future as a result of urbanization and economic development. ASCE Standard 7-22 on Minimum Design Loads has, for the first time, included new reliability-based design criteria for tornado loads. The objective of this paper is to provide archival documentation of the basis for these tornado-resistant load provisions in Chapter 32 of ASCE 7-22. This paper summarizes the significant challenges that were overcome in addressing the fundamental differences between effects of tornado and nontornadic winds and the higher uncertainties associated with tornado wind pressures that must be accommodated in the risk-informed framework of ASCE 7-22. These challenges were addressed through reliability analyses that led to new tornado load criteria that provide reasonable consistency with the reliability delivered by existing criteria for nontornadic winds. [ABSTRACT FROM AUTHOR]

The increasing demand for power has caused distortions in Nigeria's 330 kV transmission network. This is a result of the bulk of the lines being heavily loaded at the moment, which leads to voltage drops and inconsistent electrical delivery. To ensure system reliability, it is therefore crucial to make sure that the system maintains a constant state under specific conditions. This research presents the use of static synchronous compensators (STATCOM) in the Nigerian 330 kV transmission network to reduce power loss and improve the voltage profile. To solve the problem of insufficient voltage and power losses, a three-phase network is simulated using the MATLAB/Simulink software. A three-level, 48- pulse STATCOM was employed to rectify the problem after weak buses were identified through load flow analysis. A 48- pulse converter that handled the STATCOM was used to control harmonic distortions in the system. The outcomes show how crucial the reactive power control mechanism is for regulating the system's harmonics. However, the method was able to achieve real and reactive power losses of 12.5%. The STATCOM's 3-level 48- pulse converter also resulted in a total 4.64% reduction in total harmonic distortion (THD). [ABSTRACT FROM AUTHOR]

It is an established and already accomplished fact that probability-based methodologies (or probability/statistical distributions) play the roles of imperative tools in illustrating and describing applied phenomena. Paying attention to these previous facts, this paper considers the evolution of a new probability distribution. Thus, the main achievement of this paper leads to a new probability distribution as a result of combining the exponentiated exponential model with a tangent-based stratagem. The new model is called the tangent exponentiated exponential (TEE) distribution. For the TEE distribution, certain distributional properties and estimators of the model parameters are derived mathematically. The appraisal of the estimators of the TEE distribution is accomplished through a simulation study. Moreover, the applicability and virtuoso of the TEE distribution are exemplified via two data sets, which are taken from the music engineering (named Data 1) and reliability sector (named Data 2). By considering the p -value and three other important statistical tests/methods as diagnostic tools, we find that the TEE distribution is the most useful and optimal model for Data 1 and Data 2 compared to certain candidate probability distributions. [ABSTRACT FROM AUTHOR]

Over the past few years, photovoltaic (PV) installations have experienced a surge in popularity, primarily driven by growing environmental concerns. However, the rise of large-scale PV installations has brought about challenges, such as the risk of overvoltage and grid overload. Instances of voltage violations notably escalate with increased PV penetration, often leading to inverter shutdowns. These occurrences cast a shadow over the viability of implementing high PV penetration. Moreover, integrating a substantial intermittent power source into an outdated power grid raises concerns about the reliability of the entire power network. Enhancing the power system to accommodate significant intermittent power poses a considerable challenge, and retrofitting the entire system would be prohibitively expensive. To address these issues without incurring exorbitant costs, the adoption of flexible power point tracking (FPPT) emerges as a crucial solution. FPPT effectively reduces ripple current stress, thereby extending the lifespan of critical components in a grid-connected PV system, including PV panels, DC link capacitors, and PV inverters. The significance of this research is underscored through an analytical study that scrutinizes various system entities, considering maximum power point tracking (MPPT) and FPPT separately. Furthermore, theoretical observations are substantiated by simulation results on the Matlab platform, illustrating the practical impact of FPPT compared to MPPT. Analytical findings highlight an overall improvement in the lifespan of system components when FPPT is employed as a substitute for MPPT. [ABSTRACT FROM AUTHOR]

A transmission network is an important part of the power transformers to transmit the generated energy and power to the load centers. As such, the transmission network requires significant expansion costs to alleviate congestion as well as to supply an acceptable reliability level. In this matter, transmission network expansion planning (TNEP) is known as a large-scale mathematical problem including long-term effects of the power system. In this paper, long-term effect of demand response (DR) is explored on the loading rate of the system as well as subsequent line loading influence on line failure rates. To investigate the DR effectiveness on TNEP, its cost is addressed in the objective of the proposed mixed integer nonlinear planning model. Moreover, alleviating the failure rate of old lines can decrease the construction of new lines while providing the desirable reliability of the system. Furthermore, a decrease in the loading rate of existing transmission lines provides valuable gains at the horizon year. Thus, the value of the transmission system in the objective function would increase by DR. Besides, peak clipping prevents local marginal price (LMP) inflation and smoothens the LMP profile across the system buses; so congestion surpluses will decrease. Afterward, the sensitivity analysis in the simulation part is implemented to investigate how demand response can influence on value of LMP at different nodes. Eventually, the developed model is executed on IEEE 24-bus reliability test system for three scenarios in order to assess the efficiency of the proposed approach. [ABSTRACT FROM AUTHOR]

We consider the effect of adding three different types of standby components to a k–out–of–n:F system based on the dynamic stress–strength model. For this purpose, the system reliability in the three different types of standby components, i.e., cold, warm and hot standby components, are calculated. Also, it is assumed that the stress and the strength components follow the Weibull distribution and the Weibull process, respectively. The maximum likelihood estimators of the redundancy system reliability are obtained. In addition, a simulation study is performed based on the Monte Carlo method. Finally, the results are illustrated via a practical example that is the time of successive failures of the air conditioning system of every member of a fleet of jet airplanes. [ABSTRACT FROM AUTHOR]

Estimating the reliability and maintainability (R & M) parameters is crucial in various industrial applications. It serves purposes such as evaluating system performance and safety, minimising the risk and cost of potential failures, and designing efficient maintenance strategies. This task becomes challenging for complex repairable systems, where failures can occur due to different causes and performance may be affected by various covariates (such as material, environment, and labour). Another challenge in R & M studies arises from the presence of censorship in failure times. Existing methodologies often fail to account for all the aforementioned aspects of system‐related data in R & M analysis. By incorporating valuable information from covariates and utilising data from censored failure times alongside complete failure data, the accuracy of R & M parameter estimation can be significantly improved. This paper develops reliability models for repairable systems with multiple failure causes in the presence of covariates. The system can also be subject to imperfect maintenance. The R & M parameters are then estimated by applying the Kijima Type I and II model's virtual age concept. The proposed technique is illustrated using two case studies on gas pipelines and aero‐engine systems. Through these case studies, we show that the proposed method not only provides more efficient estimates of the R & M parameters compared to the alternative approach, but it is also easier to apply and yields more straightforward interpretations. [ABSTRACT FROM AUTHOR]

HVDC is a promising interconnection solution for connecting asynchronous systems and ensuring power control. In Indonesia, a remote industrial system in Sumatra is experiencing load growth and has the option to draw power from the Sumatra system. However, due to frequency differences, the use of HVDC is crucial. The Generation Expansion Planning has proposed six converters but not their interconnection points. This study will determine the most reliable interconnection locations. The chosen converters are modular multilevel converters (MMCs) with high modularity. The converter reliability modeling considers voltage levels, the number of modules, and redundancy strategies. This modeling is then implemented at the power system level to obtain the best placement at the available high-voltage (HV) substation options. Determining the best placement is based on the optimal reliability index. The optimal placement also includes the option to convert from HV to medium-voltage (MV) interconnection. MV interconnection offers higher flexibility but tends to be more expensive. The availability for HV converters is 99.69%, while for MV converters, it is slightly higher, at 99.81%. Additionally, converting from HV to MV reduces the SAIFI (system average interruption frequency index) from 0.2668 to 0.2284 occurrences per year, lowering the interruption cost from 7.804 million USD to 5.737 million USD per year. The sensitivity of interruption, investment, and maintenance costs shows that converting at least one HV converter to MV remains economical. In this case study, the optimal converter placement includes Area VI–2, recommended for conversion from HV to a more distributed MV configuration, improving reliability and economic efficiency. [ABSTRACT FROM AUTHOR]

The redundancy allocation problem (RAP) is one of the most commonly used approaches for improving the reliability of systems. In previous studies, to simplify the problem model and mathematical solution methods, some real conditions were not emphasized in analysing the issue of RAP. But the present study, while considering these conditions, enables considering multiple goals, analysing repairable systems and examining the failure rate and repair rate appropriate to the type of components. Two goals of this purpose are maximizing the Mean Time To First Failure (MTTFF) and minimizing the total cost of the system, considering the weight and volume limitations and number of plugin components. To solve the problem model four Multi-objective meta-heuristic algorithms have been used: NSGA-II, MOPSO, PESA-II and MALO. In addition, the simulation method is used to estimate the first objective function of the problem. [ABSTRACT FROM AUTHOR]

As real-time systems are safety critical, guaranteeing a high reliability threshold is as important as meeting all deadlines. Periodic tasks are replicated to mitigate the negative impact of transient faults, which leads to redundancy and high energy consumption. On the other hand, energy saving is widely identified as increasingly relevant issues in real-time systems. In this paper, we formalize this challenging tri-criteria optimization problem, i.e., minimizing the expected energy consumption while enforcing the reliability threshold and meeting all task deadlines, and propose several mapping and scheduling heuristics to solve it. Specifically, a novel approach is designed to (i) map an arbitrary number of replicas onto processors, (ii) schedule each replica of each task instance on its assigned processor with less temporal overlap. The platform is composed of processing units with different characteristics, including speed profile, energy cost and fault rate. The heterogeneity of the computing platform makes the problem more complicated, because different mappings achieve different levels of reliability and consume different amounts of energy. Moreover, scheduling plays an important role in energy saving, as the expected energy consumption is the average over all failure scenarios. Once a task replica is successful, the other replicas of that task instance can be canceled, which calls for minimizing the overlap between any replica pair. Finally, to quantitatively analyze our methods, we derive a theoretical lower-bound for the expected energy consumption. Comprehensive experiments are conducted on a large set of execution scenarios and parameters. The comparison results reveal that our strategies perform better than the random baseline under almost all settings, with an average gain in energy consumption of more than 40%, and our best heuristic achieves an excellent performance: its energy saving is only 2% less than the lower-bound on average. [ABSTRACT FROM AUTHOR]

The reliability of multiprocessor systems is now a crucial concern in parallel computing, which can be characterized as connectivity and diagnosability. The s-extra connectivity (s-EC) κ s (G) of a network G is the minimum number of nodes whose deletion disconnects the network G, and every remaining component has no less than s + 1 nodes. The s-extra diagnosability (s-ED) t s (G) of a network G is the maximum cardinality of faulty nodes that can be identified, given that each remaining component has at least s + 1 nodes. This paper investigates the s-EC and s-ED of the complete cubic network CCN(n). Specifically, we initially demonstrate that the s-EC of CCN(n) is κ s (C C N (n)) = (s + 1) (n + 1) - s (s + 3) 2 for n ≥ 3 and 0 ≤ s ≤ n - 2 . Subsequently, we demonstrate that the s-ED under the PMC model is t s (C C N (n)) = (s + 1) (n + 1) - s (s + 3) 2 + s for n ≥ 3 and 1 ≤ s ≤ n - 2 . Similarly, under the MM* model, the s-ED is t s (C C N (n)) = (s + 1) (n + 1) - s (s + 3) 2 + s for n ≥ 6 and 1 ≤ s ≤ n - 2 4 . Finally, we conduct simulation experiments, and the results indicate that the s-EC consistently surpasses other known connectivities, including classical connectivity and s-component connectivity. Additionally, the s-ED consistently outperforms classical diagnosability and s-component diagnosability of CCN(n). [ABSTRACT FROM AUTHOR]

In this article, we consider a particular type of coherent systems, in which, when the coherent system fails, either no active component remains or the remaining active components are connected in parallel. This work studies two coherent systems of such type with two components, four coherent systems with three components, and seven coherent systems with four components as examples. Lifetime as well as system signature of each of these coherent systems is given. We investigate the restart of such a coherent system using a single cold standby component. The reliability of a system is studied through the (reliability) characteristics such as reliability function, mean time to failure, mean residual life functions of the system. We compute signature-based exact expression for the reliability function of the considered coherent system, which is equipped with a cold standby component. Also, we obtain three different mean residual life functions of the system. So far, no attempt has been made to study such coherent systems in cold standby sparing; therefore, we have provided some new results. We illustrate the theoretical results by considering three particular coherent systems as examples. [ABSTRACT FROM AUTHOR]

The presence of probability-driven models is highly influential in setting the stage for vital decision-making in domains including reliability, engineering, music engineering, and other closely interconnected scenarios. With a deep understanding of the consequential roles played by probability-arisen models, we have developed and implemented a new probabilistic model. This model is constructed by utilizing the sine-based function and the exponentiated Weibull distribution, and it is known as the exponent power sine exponentiated Weibull (EPSE-Weibull) distribution. Point estimators are derived for the EPSE-Weibull distribution. These estimators are then evaluated through a simulation study. The significance of the EPSE-Weibull distribution is demonstrated through the analysis of reliability and music engineering data sets. In addition to the above, we also utilize two deep learning algorithms, namely Artificial Neural Networks (ANN) and Support Vector Regression (SVR), to forecast the same data sets. The findings indicate that the ANN model consistently exhibits higher levels of accuracy, as evidenced by its lower Root Mean Square Error (RMSE) and Mean Absolute Error (MAE) values compared to the SVR model for both data sets. These findings indicate that ANN is better at capturing the fundamental patterns in the underlying data sets. In addition, visual representations, such as bar charts and line charts, further emphasize the superior performance of the ANN across both data sets. [ABSTRACT FROM AUTHOR]

Due to the complex operating environment of LED lamp beads (hereinafter referred to as LED), the test method that only considers the action of multiple stresses alone ignores the mutual influence between stresses, making it difficult to accurately obtain the life indicators of LEDs, resulting in a large deviation in the theoretical life results. In this regard, this paper proposes a multi-stress accelerated degradation evaluation method considering generalized coupling and conducts an accelerated degradation test (ADT) to evaluate the life of LEDs. We identified three stress sources and designed five new high-gradient ADTs. Through experimental data, we found that the three stress sources are strongly coupled on this LED. Then, a generalized coupling maximum likelihood estimation method (MLE) for the entire sample was constructed, and the particle swarm algorithm was used to solve the parameters. Finally, the life of this LED was evaluated based on the experimental data. The results show that the life of the LED considering multiple-stress coupling is within 6.5% of the historical life scatter point, which is more in line with the actual working environment. [ABSTRACT FROM AUTHOR]

Satellite swarm networks have occupied a prominent position in many modern applications due to their low cost, simplicity of design, and flexibility. Reliability is an influential factor in the design of satellite networks with different structures. Usually, small satellites are based on COST components, which may reduce continues operability due to the lack of using backup system on board the sagecraft. Any failure in one subsystem means a complete loss of the function and data stored in this subsystem; hence the need for a reliable and applicable solution for this matter is a crucial topic. Using the redundancy strategy in satellite swarm networks increases reliability and availability. Blockchain is characterized by using a distributed ledger which enables the database to be replicated across nodes in the network and results in increasing transparency, security, and trust. This paper suggests adoption of blockchain technology in distributed multi-satellite mission swarm networks to provide a high level of reliability and availability of the entire system; the blockchain is usually used to secure system transactions in multilayer approach by storage of the key parameters in more than one node; here we suggest the adoption of this approach not only to secure satellite network transaction, but also to increase system reliability so that failure of one node can be recovered by other nodes. We compared this approach with similar traditional networks that do not use blockchain. The results show a higher reliability efficiency of 95.3% for applying blockchain technology compared to 64.3% without the use of blockchain, as well as a higher availability of 99% compared to 91%. [ABSTRACT FROM AUTHOR]

Objective: This study outlined the development of the barriers, prescribing practices, and guideline adherence for osteoporosis management according to the Clinicians' Osteoporosis Questionnaire (COQ) followed by an assessment of the content validity index and reliability test. Methods: The development of the COQ was performed in two stages. Stage I involved the development of the COQ, and stage II involved judgmental evidence and quantification of the questionnaire. Five panel experts related to the study area and five clinicians participated in the validity of the COQ assessment. Fifty clinicians took part in the reliability test evaluation by filling out the questionnaire twice at 2-week intervals. The content validity index (CVI) and content validity ratio (CVR) were analyzed using Microsoft Excel, while Cohen's kappa statistic was used to determine the test-retest reliability using SPSS version 29. Results: Forty items and three domains, namely, barriers, prescribing practices, and guideline adherence for osteoporosis management, were identified in the COQ (version 4.0). The scale-level CVI (S-CVI/Ave) for every domain was above 0.9, which is considered acceptable. The CVRs for all the items were above 0.7, except for two items in the barrier domain and two items in the guideline adherence domain. Two items were revised to improve the clarity of the item, and other items were retained based on consensus among the expert panel. Between the test and retest, the reliability of individual items ranged from moderate to almost perfect for the barrier domain (k = 0.42-0.86), prescribing practice domain (k = 0.79-0.87), and guideline adherence domain (k = 0.46-1). None of the items had "fair" or "poor" agreement. Thus, the 40-item COQ (version 4.0) was finalized following the content and face validity analysis. Conclusions: Through an iterative process, the development and assessment of the COQ showed a high degree of content validity and reliability in measuring the barriers, prescribing practices, and guideline adherence among clinicians managing osteoporosis. Future studies should aim to further validate this instrument across different populations and settings, as well as explore methods to enhance its reliability and validity. [ABSTRACT FROM AUTHOR]

Recent advancements in power electronics have significantly improved photovoltaic (PV) inverters by equipping them with sophisticated monitoring capabilities. These enhancements provide economic advantages by facilitating swift failure detection and lowering monitoring costs. Educating users on the economic repercussions of undetected failures in specific inverter monitoring systems is crucial. This paper introduces a novel metric, "Cost of Detection", which assesses the financial impact of failures, considering the repair expenses and the "quality" of the monitoring system in place. The study analyzed fifteen inverter monitoring solutions, focusing on the variance in alerts generated by the manufacturers' standard and extra monitoring features. Employing the Failure Mode and Effects Analysis (FMEA) method, alerts were prioritized based on their importance for two PV system scenarios: a low-power residential system (5 kWp) and a medium-power industrial/commercial system (100 kWp). Lisbon, Rome, and Berlin were chosen as the locations for these systems. The economic impact of system failures is evaluated annually for each capacity and city. Given the differing costs and annual yields, comparing their economic performance over time is essential. This comparison utilizes the Net Present Value (NPV), which estimates an investment's worth by calculating the present value of all cash flows. The investment assessment includes only the costs of inverters and optimizers, excluding O&M expenses, licenses, and fees. Over five years, a higher NPV signifies a more economically advantageous solution. For residential systems, string inverters with optimizers have the highest NPV, surpassing those without optimizers by 17% across all three cities. The optimal monitoring solution in the industrial/commercial context was a string inverter with one optimizer for every two panels. Here, Rome emerged as the location with the most substantial NPV increase of 50%, followed by Berlin with 33% and Lisbon with 28%. [ABSTRACT FROM AUTHOR]

Researchers have studied instances of power line technical failures, the significant rise in the energy loss index in the line connecting the distribution transformer and consumer meters, and the inability to control unauthorized line connections. New, innovative, and scientific approaches are required to address these issues while enhancing the reliability and efficiency of electricity supply. This study evaluates the reliability of Internet of Things (IoT)-aided remote monitoring systems specifically designed for a low-voltage overhead transmission line. Many methods of analysis and comparison have been employed to examine the reliability of wireless sensor devices used in real-time remote monitoring. A reliability model was developed to evaluate the reliability of the monitoring system in various situations. Based on the developed models, it was found that the reliability indicators of the proposed monitoring system were 98% in 1 month. In addition, it has been proven that the reliability of the system remains high even when an optional sensor in the network fails. This study investigates various IoT technologies, their integration into monitoring systems, and their effectiveness in enhancing the reliability and efficiency of electrical transmission infrastructure. The analysis includes data from field deployments, case studies, and simulations to assess performance metrics, such as accuracy, latency, and fault detection capabilities. [ABSTRACT FROM AUTHOR]

Researchers have proposed the dynamic heterogeneous redundancy (DHR) architecture, which integrates dynamic, heterogeneous, redundant, and closed-loop feedback elements into the system, to fortify the reliability of the railway passenger service system (RPSS). However, there are at least two weaknesses with the common DHR architectures: (1) they need system nodes with enough computing and storage resources; (2) they have hardly considered the reliability of DHR architecture. To this end, this paper proposes a double-layer DHR (DDHR) architecture to ensure the reliability of RPSS. This architecture introduces a set of algorithms, which are optimized co-computation and ruling weight optimization algorithms for the data processing flow of the DDHR architecture. This set improves the reliability of the DDHR architecture. For the evaluation of the reliability of DDHR architecture, this paper also proposes two metrics: (1) Dynamic available similarity metric. This metric does not rely on the overall similarity of the double-layer redundant executor sets but evaluates the similarity of their performance under the specified interaction paths within a single scheduling cycle. The smaller its similarity, the higher its reliability. (2) Scheduling cycle under dual-layer similarity threshold. This metric evaluates the reliability of the RPSS under actual conditions by setting the schedulable similarity thresholds between the same and different layers of the dual-layer redundant executives in the scheduling process. Finally, analog simulation experiments and prototype system building experiments are carried out, whose numerical experimental results show that the DDHR architecture outperforms the traditional DHR architecture in terms of reliability and performance under different redundancy and dynamically available similarity thresholds, while the algorithmic complexity and multi-tasking concurrency performance are slightly weaker than that of the DHR architecture, but can be applied to the main operations of the RPSS in general. [ABSTRACT FROM AUTHOR]

This paper studies the reliability of consecutive k-out-of-n: G systems with protection blocks. The system consists of $ n $ n components, and it functions if at least $ k $ k consecutive components are operational. Protection blocks can be used to increase system reliability by reducing the failure rates of exactly $ k $ k consecutive components. However, the protection blocks also have their own failure rates. System reliability is assessed by calculating the probability of successful operation over a specified time period, taking into account the failure dynamics of both components and protection blocks. Binary decision diagram (BDD) is used to identify combinations of component states that lead to system success. The probability for each combination is then evaluated, considering the states of both the components and the protection blocks. By integrating these probabilities, the overall system reliability is determined. Numerical examples are provided to illustrate the application of this method. [ABSTRACT FROM AUTHOR]

I was born in Moscow on September 10, 1934. I wrote about my family and previous generations of Yastrebenetsky (a soldier under Emperor Nicholas I, a businessman, a doctor, a chemical engineer) in my book "Generations of Yastrebenetsky" [1]. After finishing the institute and postgraduate studies, 2/3 years of my life were connected with activity in the fields of reliability and safety of technical systems. This activity is the subject of the article. [ABSTRACT FROM AUTHOR]

Scenario-based verification defines the current state of the art for examining a vessel's control systems for reliability and safety. However, software updates after release can only be covered to a limited extent. To take changes to a deployed system into account, the design and test phase must be harmonized with the operational phase. For all phases, regulatory, technical and safety requirements provide the scope to which the development process and the scenario-based tests need to be aligned and whose specifications the System under Test (SuT) must adhere to during operation. For this reason, a procedure is needed that converts the requirements into a format that can be utilized across all phases and measured in a structured manner comparing the original system to the updated version. This work does so by combining scenario-based verification methods with formal composition and monitoring techniques based on contract-based design into an integrated development approach. It is shown how safety requirements can be transferred into a Verification Descriptor that in turn provides the foundation for the division into model-based system development, contract-based virtual integration testing and a scenario-based test environment. For the entire lifecycle of the System under Test (SuT) to be included, the extended scenario and contract descriptors are carried forward up to the operational phase, such that the previously defined properties of the SuT can be monitored and validated during runtime. The approach is designed alongside a minimal-viable system and evaluated on an actual implementation of a safety-critical maritime LiDAR-based positioning system. [ABSTRACT FROM AUTHOR]

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It is shown that the psychometric test reliability, based on any true-score model with randomly sampled items and uncorrelated errors, converges to 1 as the test length goes to infinity, with probability 1, assuming some general regularity conditions. The asymptotic rate of convergence is given by the Spearman–Brown formula, and for this it is not needed that the items are parallel, or latent unidimensional, or even finite dimensional. Simulations with the 2-parameter logistic item response theory model reveal that the reliability of short multidimensional tests can be positively biased, meaning that applying the Spearman–Brown formula in these cases would lead to overprediction of the reliability that results from lengthening a test. However, test constructors of short tests generally aim for short tests that measure just one attribute, so that the bias problem may have little practical relevance. For short unidimensional tests under the 2-parameter logistic model reliability is almost unbiased, meaning that application of the Spearman–Brown formula in these cases of greater practical utility leads to predictions that are approximately unbiased. [ABSTRACT FROM AUTHOR]

We explore the Redundancy Allocation Problem (RAP) under the objective of minimizing the cost of a production system of general topology in which system reliability is treated as a chance constraint. A novel simulation optimization-based solution method grounded in the concepts of the trust region and response surface methodology is proposed to efficiently solve the generalized RAP (GRAP) under random system survival times. The generalizability of the RAP model and efficiency of the solution method allows for our approach to be utilized in a wide variety of real-world applications. We demonstrate in a series of numerical experiments based on production systems of varying complexity that the finite convergence of the proposed method is much more efficient than the commonly-used genetic algorithm. It is shown that on a simple bridge network, only the proposed algorithm can find the true optimal solution to the GRAP under an allotted computational budget. On a complex network which includes series, parallel, and logical relationships, the proposed algorithm is also shown to find solutions to the GRAP which have substantially lower total system cost than those found by GA under a wide variety of scenarios. [ABSTRACT FROM AUTHOR]

This paper studies the reliability function of a weighted $k$ k -out-of- $n$ n system with multiple types of components. A weighted system with $M$ M different types of components is considered and two real-life scenarios for the operation of the system are defined. In the first one, it is assumed that the system operates if the accumulated weight of all active components is more than a predetermined threshold $k$ k , otherwise the system fails. In the second scenario, the system is assumed to operate if the total weight of the operating components of type $i$ i is more than or equal to the corresponding threshold ${k_i}$ k i , for at least $m$ m types of components, $m \le M$ m ≤ M. Our approaches in assessing the reliability function of the system lifetime rely on the notion of survival signature corresponding to multi-type weighted $k$ k -out-of- $n$ n system. The formulas for the proposed survival signature are presented and the corresponding computational algorithms are also given. To examine the theoretical results, the reliability function and other aging characteristics of a wind farm (system) consisting of three plants located in three different regions are assessed numerically and graphically. Finally, an allocation problem to determine the best choice for the distribution of each type in the weighted $k$ k -out-of- $n$ n systems is studied. [ABSTRACT FROM AUTHOR]

Today, with the growth of the population and increasing trend in the use of electrical energy, the importance of the reliability and stability of the power grid has increased. The ever-increasing development of the power grid and subsequent blackouts of the power grid can lead to serious problems in the daily life and economy of a country. In addition to economic damages, power losses in the power network can lead to dissatisfaction and decreased consumer confidence in the power grid. This research has been carried out to check the application of the genetic algorithm to calculate reliability indices including SAIFI, SAIDI, etc., and its impact on enhancing the reliability of the standard IEEE 33 and 69 bus distribution networks. Additionally, this study explores the GA effectiveness in minimizing both active and reactive power losses. The simulation results in MATLAB, show the constructive effect of applying the GA, shedding light on its potential to optimize the distribution network reliability and minimize power losses, offering valuable insights for power system optimization and reliability improvement. [ABSTRACT FROM AUTHOR]

The increasing use of drones for safety-critical applications, particularly beyond visual lines of sight and over densely populated areas, necessitates safer and more reliable designs. To address this need, this paper introduces a novel methodology integrating Null Controllability with the Model-Based Safety Assessment (MBSA) framework AltaRica 3.0 to optimize propulsor configurations and system architectures. The main advancement of this method lies in the automation of reliability modeling and the integration of controllability assessment, eliminating restrictions on the types of propulsor configurations and system architectures that can be evaluated and significantly reducing the effort required for each design iteration. Through a hexarotor drone case study, the proposed method enabled a high number of design iterations, efficiently exploring various aspects of the design problem simultaneously, such as configuration, system architecture, and controllability hypothesis, which is not possible with state-of-the-art techniques. This approach demonstrated significant reliability improvements by implementing and optimizing redundancies, reducing the probability of loss of control by up to 99%. The case study also highlighted the increasing difficulty of enhancing reliability with each iteration and confirmed that it is unnecessary to consider more than two simultaneous failures for design optimization. A comparison of reliability figures with previous studies highlights the crucial role of system architecture in effectively enhancing drone design reliability. This work advances the field by providing an effective multidisciplinary modeling framework for drone design, enhancing reliability in safety-critical applications. [ABSTRACT FROM AUTHOR]

This article examines the impact of meteorological conditions represented by ambient temperature, ambient humidity, wind speed, and daily precipitation sum on the reliability of low-voltage cable lines. Cable line reliability is crucial to the stability and safety of power systems. Failure of cable lines can lead to power outages. This can cause serious economic and social consequences, as well as threaten human safety, especially in the public sector and critical infrastructure. In addition, any interruption of cable lines generates costs related to repairs, operational losses, and possible contractual penalties. This is why it is so important to investigate the causes of power equipment failures. Many power system failures are caused by weather factors. The main purpose of this article is to quantify the actual impact of weather conditions on the performance and reliability of power equipment in distribution networks. Reliability indicators (failure rate, failure duration, restoration rate, and failure coefficient) for low-voltage cable lines were calculated as a function of weather conditions. Empirical values of the indicators were determined based on many years of observations of power lines operating in the Polish power system. An analysis of the conformity of their empirical distribution with the assumed theoretical model was also conducted. By quantifying the impact of specific weather factors on the operation of power equipment, it becomes possible to identify the ranges in which failures are most likely. [ABSTRACT FROM AUTHOR]

As for an operation system, having a solid and reliable composition structure is the basis for the effective implementation of combat tasks and the prerequisite for giving full play to the system effectiveness. In order to estimate the continuous running capability of the operation system architecture in case of under attack or faults occurrence, starting from the perspectives of point connectivity and edge connectivity, a reliability analytics method for the operation architecture is proposed based on the connectivity among its components. The proposed method is demonstrated by case studies, and can be used for operation systems design and contribution. [ABSTRACT FROM AUTHOR]

Reliability optimization is a process aimed at improving the effectiveness and efficiency of maintenance activities within an organization. This optimization can concern various aspects, including failure prevention, resource management, cost reduction, and improving the operational availability of equipment. In this work, our study aims to implement a comprehensive maintenance strategy for the 1600T press at Algal + company with the primary objectives of preventing breakdowns, minimizing unplanned downtime, optimizing productivity, extending the lifespan of equipment, ensuring safety, and improving the competitiveness and profitability of the company. The problem of reliability and availability of the 1600T press at the Algal + company can be addressed by a systematic approach to industrial maintenance. By adopting a holistic approach to industrial maintenance, Algal + company can improve the reliability and availability of its equipment, thereby reducing unplanned downtime and optimizing overall productivity. By systematically applying FMECA to the 1600T press, the optimization efforts become data-driven and focused on addressing the most critical risks. This, in turn, significantly contributes to optimizing the reliability and availability of the equipment, reducing unplanned downtime, and enhancing overall operational efficiency. [ABSTRACT FROM AUTHOR]

Probability-arisen models play a considerable role in preparing a crucial stage for decision-making concerning reliability, engineering, and more closely related scenarios. Bearing in mind the consequential roles of probability-arisen models, we introduce and implement a new probabilistic model that has arisen by using the sine function, namely, the sine very flexible Weibull (SVF-Weibull) distribution. The proposed SVF-Weibull distribution is a result of a combination of the very flexible Weibull distribution with the sine-based strategy. For the SVF-Weibull distribution, point estimates are obtained. The assessment of the point estimates of the SVF-Weibull distribution is done via a simulation study. Finally, the consequential role of the SVF-Weibull distribution, illustrated by considering reliability and music engineering data sets. Furthermore, we implement some machine learning tools for predicting the reliability and music engineering data sets. The performances of the machine learning tools are assessed across many hidden variables. Our findings suggest that the artificial neural network method is more optimal than other methods for predicting the reliability and music engineering data sets. [ABSTRACT FROM AUTHOR]

AbstractTraditionally, the Gaussian assumption, implied by the Wiener process, is widely admitted for modeling degradation processes. However, when degradation data exhibit heavy tails, this assumption is not suitable. To overcome this limitation, this article proposes a novel class of tail-weighted multivariate degradation model, which is built upon Student-t process. The model is able to account for both between-unit variability and process dependency, while allowing the adjustment of tail heaviness through tuning the parameter of the degree of freedom. For reliability assessment, we derive the system reliability function and present an efficient Monte Carlo method for its evaluation. Further, we introduce an expectation–maximization algorithm for parameter estimation and design a bootstrap method for interval estimation. Comprehensive simulation studies are conducted to validate the effectiveness of the inference method. Finally, the proposed methodology is applied to analyze two real-world degradation datasets. [ABSTRACT FROM AUTHOR]

An m-consecutive-k-out-of-n: F ( m / C / k / n :   F ) system consists of n linearly ordered components such that the system fails if and only if there are at least m nonoverlapping runs of k consecutive failed components. Our motivation in this work is to obtain efficient formulas for the signature and reliability of the m / C / k / n :   F system with independent and identical (i.i.d) components that are easy to implement and have a low computational time. We demonstrate that the reliability formula derived for this system requires less computational time than the m / C / k / n :   F system formula currently in use. For the minimal and maximal signatures of the m / C / k / n :   F system, we provide precise equations. In addition, the average number of faulty components at the time of an m / C / k / n :   F system failure and mean time to failure (MTTF) of an m / C / k / n :   F system are analyzed through the system signature. [ABSTRACT FROM AUTHOR]

This article deals with a repairable k-out-of-n: G system with retrial feature and two maintenance policies. All components in the system have two failure modes, mode a failure and mode b failure. When a component fails, the failed component will be repaired instantly if the repair equipment is idle. Otherwise, it enters into a retrial orbit and tries again after some time until it is repaired. The single repair equipment may be subject to breakdown in a busy period, and in order to improve system reliability, the idle repair equipment will be performed preventive maintenance. The Markov process theory and Laplace transform method are adopted to compute the reliability indexes of the system. Also, four optimization design models are constructed to determine the optimal repair rates of the components with two failure modes, and the minimization problems of the total expected cost function per unit time and the cost-effectiveness ratio are solved. To verify the correctness of the model, numerical analysis is executed to demonstrate the impact of each parameter on system reliability indexes, the optimal solutions of different optimization design models are obtained by using differential evolution algorithm and genetic algorithm. [ABSTRACT FROM AUTHOR]

Edge computing provides a real-time guarantee for the industrial internet. Server deployment is the first step to building an edge computing system, and the deployment strategy has a huge impact on system delay and reliability. Industrial environments place higher demands on reliability than other common environments. However, existing research on edge server deployment assumes that the server will not fail and thus rarely considers edge server reliability while reducing delay. This paper focuses on edge server deployment approach for delay reduction and reliability enhancement in the industrial internet. Firstly, a basic edge server deployment model is established to optimize server load balancing and delay. On this basis, an edge server deployment model with enhanced reliability is established. This model improves system reliability by adding fault-tolerant servers when deploying edge servers. When some edge servers in the system fail, the fault-tolerant servers will intervene in time and start working to replace the failed edge servers. To solve the optimal deployment strategy, an Improved Grey Wolf-Genetic Algorithm-based deployment algorithm is proposed. The deployment algorithm improves the traditional genetic algorithm's performance to find the global optimal solution by improving the initialization and mutation part of the genetic algorithm. The deployment algorithm selects appropriate wireless access points (WAPs) to deploy fault-tolerant edge servers among a large number of WAPs. Simulation results show that the established fault-tolerant model can significantly improve system reliability while reducing system delay. The proposed algorithm performs better compared with existing algorithms in terms of convergence speed and finding the optimal deployment location. [ABSTRACT FROM AUTHOR]

The present work is devoted to the analysis of the most important reliability indicators of components of electrical devices of mining dump trucks, and analytical methods of their evaluation are proposed. A mathematical model for calculating the reliability of electrical devices integrated into the electrical systems of quarry dump trucks is presented. The model takes into account various loads arising in the process of operation and their influence on reliability reduction. Optimisation of maintenance and repair schedules of electrical equipment has revealed problems for research. One of them is the classification of electrical equipment by similar residual life, which allows the formation of effective repair and maintenance cycles. The analysis of statistical data on damages revealed the regularities of their occurrence, which is an important factor in assessing the reliability of electrical equipment in mining production. For quantitative assessment of reliability, it is proposed to use the parameter of the average expected operating time per failure. This parameter characterises the relative reliability of electrical equipment and is a determining factor of its reliability. The developed mathematical model of equipment failures with differentiation of maintained equipment by repeated service life allows flexible schedules of maintenance and repair to be created. The realisation of such cycles makes it possible to move from planned repairs to the system of repair according to the actual resource of the equipment. [ABSTRACT FROM AUTHOR]

AbstractA multi-state m-out-of-r-within-k-out-of-n system has found great importance in reliability theory because of its wide applications in engineering systems. In previous studies, usually all the components of the m-out-of-r-within-k-out-of-n system were considered to be binary and that too in a steady state, despite the fact that there are numerous complex systems where the components of this type of system can be multi-state and dynamic in nature i.e., their states change over time. To deal with this circumstance, the current research presents an algorithm, based on the Lz-transform to determine the reliability indices of the considered system in the dynamic setup. The Markov process is assumed to be followed by the components of the considered system and is mended only after they entirely fail. In the proposed research, reliability, availability, instantaneous mean expected performance and mean performance deficiency are obtained for the considered system. Finally, a case study of the photovoltaic system is studied to implement and validate the proposed method. [ABSTRACT FROM AUTHOR]

This research investigates the reliability estimation in multicomponent stress-strength model when both the stress and strengths are drawn from Weighted Exponential-Lindley distribution. Reliability assessment is carried out using classical and Bayesian approaches. The Bayes estimates of the reliability in the multicomponent stress-strength model are derived under a squared error loss function using informative and non-informative priors for the parameters. Further, Lindley's approximation and Gibbs sampling method are used to develop Bayes estimators for the system's reliability due to the lack of explicit forms. Additionally, an asymptotic confidence interval and the highest probability density credible interval are constructed to gauge system performance. A simulation study is conducted to assess the performance of reliability estimators. Finally, a real data set is analysed for illustrative purposes. [ABSTRACT FROM AUTHOR]

The service life assessment of previous fatigue stress has a fundamental role in estimating the reliability of products like fiber optical connectors, and should replicate use in severe environments in telecommunications systems. However, the vibration prediction models used in the literature present limitations in vibration life prediction. In this paper, we propose using the insertion loss fatigue life and including it in the Weibull distribution to determine the Weibull parameters ƞ and β to evaluate fiber optic connector reliability R(t) under environmental and mechanical testing stress. We analyzed the failure data of a standard telecommunication fiber optical connector under a program of service life stress testing against that of a fiber optical connector under only mechanical vibration stress testing. The fiber connectors were monitored during the vibration testing to review the transient change of the optical signal. Their results showed that the reliability of the fiber connectors submitted to the service life program was R t = 0.694 , while that of the fiber connectors submitted to mechanical vibration only was R t = 0.970 . In addition, the analysis showed that the service life testing consumed 70.2% of the product's lifetime. We present in Numerical Validation the steps to determine the acceleration factors of the vibration test developed. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this study is to propose a simplifying approach for modelling a reliability test. Modelling the reliability tests of printed circuit board (PCB)/microelectronic component assemblies requires the adoption of several simplifying assumptions. This study introduces and validates simplified assumptions for modeling a four-point bend test on a PCB/wafer-level chip scale packaging assembly. Design/methodology/approach: In this study, simplifying assumptions were used. These involved substituting dynamic imposed displacement loading with an equivalent static loading, replacing the spherical shape of the interconnections with simplified shapes (cylindrical and cubic) and transitioning from a three-dimensional modelling approach to an equivalent two-dimensional model. The validity of these simplifications was confirmed through both quantitative and qualitative comparisons of the numerical results obtained. The maximum principal plastic strain in the solder balls and copper pads served as the criteria for comparison. Findings: The simplified hypotheses were validated through quantitative and qualitative comparisons of the results from various models. Consequently, it was determined that the replacement of dynamic loading with equivalent static loading had no significant impact on the results. Similarly, substituting the spherical shape of interconnections with an equivalent shape and transitioning from a three-dimensional approach to a two-dimensional one did not substantially affect the precision of the obtained results. Originality/value: This study serves as a valuable resource for researchers seeking to model accelerated reliability tests, particularly in the context of four-point bending tests. The results obtained in this study will assist other researchers in streamlining their numerical models, thereby reducing calculation costs through the utilization of the simplified hypotheses introduced and validated herein. [ABSTRACT FROM AUTHOR]

A ring-connected microgrid cluster can be formed by connecting geographically closed microgrids for mutual power sharing to increase the system's reliability. Real-time power balance within individual microgrids and power sharing among the microgrids of an islanded microgrid cluster would be challenging during contingencies if they are not properly sized and controlled. We propose a technique to design a ring-connected microgrid cluster that has several distributed energy resources. The amount of power flow via interconnecting cables was decided considering the size of the energy storage of the neighboring microgrids. A control system was designed to minimize the effect of severe transients in the neighboring microgrids in the network. The performance of the proposed technique was verified using a ring-connected microgrid cluster with four microgrids derived based on a real distribution system. The results illustrated that the proposed ring-connected microgrid cluster could maintain the power balance of the networked microgrid during the contingencies of neighboring microgrids, increasing the resiliency of the system compared to the radial and islanded operations. [ABSTRACT FROM AUTHOR]

The reliability was evaluated for frame construction with mortise and tenon (MT), dowel, and non-glued and glued staple joints made of beech wood. The moment capacities of the T-shaped joints were determined under static vertical loads. The MT joint had an average moment capacity of 204 Nm, followed by dowel joints (154 Nm). In staple joints, joint strength increased after gluing. A three-seat sofa frame was defined and theoretically subjected to loads on arm rails, side rails, and back posts. Moment levels on the joint of the frame were obtained by using the stiffness method. To measure the reliability, these moment levels were assumed to be normally distributed with a coefficient of variation of 10%; accordingly, the normal distribution of the data sets was transformed into a normal standard distribution, and then, the reliability of each joint on the frame was obtained by using probabilistic approaches. MT joints were found to have the highest moment capacity and, correspondingly, the highest reliability (99.99%). Gluing the staple joints increased the strength, so their reliabilities were increased. In designing frame construction, the critical joints should be determined, and then, the joinery system with the higher reliability should be used. [ABSTRACT FROM AUTHOR]

This article discusses fundamental issues associated with the functional reliability of selected fire alarm systems (FASs) in operation during building fires. FASs operate under diverse external or internal natural environmental conditions, and the operational process of FAS should take into account the impacts of physical phenomena that occur during fires. Their operation is associated with the constant provision of reliability. FAS designers should also consider the system's reliability when developing fire control matrices, tables, algorithms, or scenarios. All functions arising from an FAS control matrix should be implemented with a permissible reliability level, RDPN(t), prior to, as well as during, a fire. This should be assigned to the controls saved in the fire alarm control unit (FCP). This article presents the process by which high temperatures generated during a fire impact the reliability of FAS functioning. It was developed considering selected critical paths for a specific scenario and the control matrix for an FAS. Such assumptions make it possible to determine the impact of various temperatures generated during a fire on the reliability of an FAS. To this end, the authors reviewed that the waveform of the R(t) function changes for a given FAS over time, Δt, and then determined the fitness paths. The critical paths are located within the fire detection and suppression activation process, using FAS or fixed extinguishing devices (FEDs), and the paths were modeled with acceptable and unacceptable technical states. The last section of this article defines a model and graph for the operational process of a selected FAS, the analysis of which enables conclusions to be drawn that can be employed in the design and implementation stages. [ABSTRACT FROM AUTHOR]

This study examines reliability of equipment (RoE) through three approaches: equipment design reliability, human reliability (HR), and maintenance‐based reliability. HR plays a key role in minimizing human error (HE) and subsequently enhancing RoE. Given that equipment reliability is influenced by numerous factors, these technologies come with various constraints, multiple outputs, and inputs. Compared to mathematical programming and analytical models, simulation methods in the field of reliability are relatively limited. However, system dynamics (SD) modeling is well‐suited to capture dynamics and complexity of systems, making it a valuable tool for long‐term strategic decision‐making. In this study, a combination of SD and regression approaches has been employed to explore the relationship between reliability and key variables such as HE and profit. Initially, the variables influencing reliability are identified, and then SD is utilized to understand the processes and interactions among these variables. Furthermore, linear regression is employed to establish the relationship between affective variables, reliability, and HE. To validate the results obtained from the proposed method, a sensitivity analysis is conducted. The results demonstrate the effectiveness of the proposed model. Simulation results indicate that implementing policies such as employee training and preventive maintenance significantly enhances RoE, leading to increased sales and profits for the organization. Therefore, managers should prioritize these variables and allocate adequate attention and resources to them. [ABSTRACT FROM AUTHOR]

The main objective of this research is to improve the reliability of the electrical system under study by reducing both the frequency of outages (SAIFI) and the downtime of electrical service (SAIDI). These problems are largely affected by adverse weather conditions, vegetation growth, and bird contact. To carry out the analysis, the 5011 urban feeder of Canton La Troncal was selected, since it presents critical values in terms of reliability compared to other feeders. The proposed methodology involves a mathematical model of heuristic optimization based on the Particle Swarm Optimization (PSO) algorithm. Two scenarios are defined for the modeling: the first focuses on relocating the existing recloser and the second on analyzing the impact of adding additional protection equipment. These scenarios are validated and demonstrate their effectiveness, achieving an improvement of 29.05% in the first case and 70.93% in the second case within a real conventional distribution system. [ABSTRACT FROM AUTHOR]

In engineering practice, some weighted-k-out-of-n: G systems often show multiple performance levels, resulting in multi-failure-mode mechanism. For these complex degradation systems, a novel reliability model with heterogeneous components is proposed on account of the number of working components, the total weight, and the sojourn time in some a stage, where different weights and thresholds are taken into account in different stages, and so do failure modes. After presenting the indispensable definitions of first passage time and the system lifetime, the system reliability indexes are derived by the Copula method to depict the dependence between components. Furthermore, maximum likelihood estimation of the Copula parameters is adopted and a Copula-based expression for component importance in each type is obtained. Finally, the reliability of the overall supercharging subsystem of an advanced fighter air energy system, as an example of weighted-k-out-of-n: G system with multi-failure modes is analyzed by the suggested model, which offers the comparison of independent and dependent cases. Meanwhile, sensitivity analysis is available to point out the effects on the system. [ABSTRACT FROM AUTHOR]

Lifetime data has two distinguishing features: they are usually censored and have non-normal distributions. Generally speaking, censoring schemes can be classified into (i) censoring schemes with replacement and (ii) censoring schemes without replacement. Replacement during a life testing means that once observing a failure item, it is replaced by a new one. While there is a relatively large body of literature regarding control charts under censoring schemes without replacement, i.e., the second type schemes, designing control charts for the first type schemes has not yet received considerable attention. In this paper, two types of control charts are developed to monitor the lifetime data of an exponentially distributed item. To obtain the information of the lifetime data, failure censoring is conducted: n items are randomly selected and put on the test simultaneously. The test continues until observing r (r≤n) failures. During the test, once observing a failure time, it is replaced by a new one. Development of Shewhart type and exponentially weighted moving average control charts under failure censoring with replacement is the main novelty of the current study. Comparative and simulation studies are conducted. ARL curves are also derived with respect to different parameters of the process. [ABSTRACT FROM AUTHOR]

Employability is a set of skills, achievement, personal attributes which makes the student more employable. This research paper tries to explore the factors which can be most influencing for the purpose of enhancing employability skills amongst students. The research is based on survey where simple technique of data collection through Google form is used. As we know that before starting collection of primary data the pilot study is very important. This study focuses on testing the reliability and validity of the designed questionnaire. The questionnaire focuses on questions related to teaching pedagogies, parts of teaching pedagogies which are important other than classroom teaching and to check if the students are kept well informed about their analysis of their skills. In this study SPSS is used to test the reliability and validity of the research instrument. [ABSTRACT FROM AUTHOR]