Search

Aim. The purpose of this research is to employ a fuzzy approach to assess the system behavior of the washing unit in a paper plant using vague, uncertain and inaccurate data. The washing unit is the main operational part of a paper plant for which analysis of system behavior is important to choose an appropriate maintenance strategy. The analysis has been carried out for washing unit of a paper plant situated in northern India. Methods. The proposed approach comprises qualitative and quantitative analysis. In qualitative analysis, the basic arrangement of the washing unit is modelled by Petri Net model. In quantitative analysis, the fuzzy λ-τ approach has been used for analyzing the systems' failure behavior more accurately. Uncertainties in failure/repair data of every subsystem/component of the washing unit are quantified using trapezoidal fuzzy numbers. Results. To assess the performance and failure dynamic behavior of the washing unit quantitatively, six reliability parameters including failure rate, repair time, mean time between failure, expected number of failures, reliability and availability at three different spread levels have been evaluated employing trapezoidal fuzzy numbers. The fuzzified values of these reliability parameters of washing unit have been defuzzified employing center of area defuzzification technique. Further, crisp values and defuzzified values of these parameters using triangular fuzzy numbers have also been obtained. The results obtained by the proposed methodology have been compared with those obtained by fuzzy λ-τ approach based on triangular fuzzy numbers. The information/results obtained through the fuzzy λ-τ approach with trapezoidal fuzzy number are conservative in nature, therefore, these results may be used by system specialist/system analysts for the future plan of implementation. Conclusion. Using this approach, six reliability parameters are evaluated and the trend (increase or decrease) of these reliability parameters is examined for performance analysis of washing unit in a paper plant. Based on these investigations, suitable maintenance policy can be established that will assist maintenance manager/system analysts/engineers in improving system performance by implementing appropriate preventive maintenance procedures. As a result, it will help in achieving a long time system availability and maximizing overall productivity of the paper plant. The implications of this fuzzy reliability approach to industry maintenance and operation planning are quite beneficial. [ABSTRACT FROM AUTHOR]

Digital Signal Processing (DSP) plays an important role in the study of genes and genomics in today's time. DSP is applied to the DNA sequences and then by applying the various DSP algorithms like DFT, (Discrete Fourier Transform), DWT (Discrete Wavelet Transform). We can predict the coding region of DNA and also find out abnormality present in the coding region. This algorithm is used to find out the cancer cells. As cancer is caused due to some mutation or abnormalities present in the DNA. So this algorithm is tested in on the several cancer gene databases and normal gene databases present in the Gene bank and NCBI website that provides satisfactory results. [ABSTRACT FROM AUTHOR]

This paper investigates a single-server queuing system with heterogeneous service, failure, and maintenance. The proposed model features a server acting as both the main and backup server. System failure can occur at any stage. When a failure happens, instead of stopping the service entirely, the main server functions as a backup, providing service at a reduced rate. Once all jobs in the system have been serviced, the backup server enters the maintenance state. Following the repair process during maintenance, the server transitions to an idle state, awaiting incoming jobs. Explicit expressions for both transient and steady-state behaviours of the system are derived. Additionally, key system performance metrics are discussed in this paper, accompanied by graphical illustrations to visualize system size probabilities and performance indices. [ABSTRACT FROM AUTHOR]

The data mining is a tool of searching information from the data warehouse. Several mining algorithms exist in literature, one of the most common is the usual K-mean procedure. This generates centroids after every round of iteration. It is assumed that sample data is completely cleaned and noise free before the start of execution of the usual K-mean algorithm. If α% values are missing in sample data then after cleaning only (100-α)% values are available for the execution of the usual K-mean algorithm. Such bears a loss of information that affects the decision. This paper considers this problem and resolves such issue by replacing the missing data through imputed values calculated by the available values, called Mean Imputation (MI). It helps in financial risk analysis quite a lot because of risk prediction being taken on a larger sample (cleaned and imputed both). Several imputation procedures are available in literature. This paper considers the financial risk data as sample where the missing values of sample are imputed by the usual Mean-Imputation (MI) method and then on complete sample. Proposed MI-K-mean strategy is compared with no imputation usual procedure and found more efficient over the four-evaluation criterion of cluster formation while applying on risk data analysis. [ABSTRACT FROM AUTHOR]

The process capability index is an important tool used in quality control and process improvement. Generally, the index is estimated under the assumption of a normal distribution, although some other distributions are also recommended in the literature. This paper instead considers a three-parameter Weibull distribution and obtains an estimate of the process capability index under the Bayesian framework. Bayesian development is based on the use of non-informative priors and the posterior sample-based inferences are drawn using an important Markov Chain Monte Carlo technique, namely, the Gibbs sampler algorithm. Finally, a numerical illustration based on two real datasets is provided. [ABSTRACT FROM AUTHOR]

In the industrial systems there is a requirement that systems should work efficiently for long time. System performance is an important aspect for failure free operation but in real practice complete failure free operation of any production system is seldom possible. Detailed critical literature review for the past thirty three years of Reliability, Maintainability and Availability (RAM) approaches has been carried out which can help to improve performance of Complex systems. Review of some papers provided the detailed information about past and current scenario of RAM practices in research field and industries. Different RAM tools and techniques extracted from the review may be helpful in qualitative and quantitative analysis of the complex systems. In this paper, author tried to focuss on some major aspects of RAM approaches. [ABSTRACT FROM AUTHOR]

This paper focuses on estimating the product of two population means. Within this paper, we have introduced three distinct classes of estimators for product of two population means. These estimators take into account the known population mean of an auxiliary variable under the framework of stratified random sampling and the presence of non-response in the study variable. Basically, for case (I) we assume the non-response on the study variable and utilize the auxiliary information corresponding to the responding units of the study variable and in case (II), we utilize the complete dataset from the auxiliary variable while also accounting for non-response in the study variable. In case (III) we combined both the information of the auxiliary variable and assumed the non-response on the study variable. Expressions for bias and mean square error have been derived, extending up to the first-order derivative. We have also pinpointed some specific members of the proposed estimator. We have conducted a simulation study to evaluate the valuable insights into the performance of the suggested classes of estimators with the conventional estimator. [ABSTRACT FROM AUTHOR]

The control of the maintenance of the industrial installations, in particular of the costs due to the implementation of the preventive policies is very interesting because of the growing importance of this service in the chains of production. The objective of this paper is to minimize the preventive maintenance costs of a production unit. For this, a state of the art on the maintenance cost models according to the policy used is first made, then a synthesis of the optimization methods is made in order to deploy the exact resolution methods and the genetic algorithms. The result of this paper is the proposal of a cost model corresponding to a periodic maintenance policy with minimal repair to the failure and the optimization of the periodicities of the partial revisions of the production unit. [ABSTRACT FROM AUTHOR]

The prediction of time-varying volatility plays an important role in financial data. In the paper, a comprehensive analysis of the mean return and conditional variance of NSE index is performed to use GARCH, EGARCH and TGARCH models with Normal innovation and Student’s t innovation. Conducting a bootstrap simulation study which shows the Model Confidence Set (MCS) captures the superior models across a range of significance levels. The experimental results show that, under various loss functions, the GARCH using Student’s t innovation model is the best model for volatility predictions of NSE among the six models. [ABSTRACT FROM AUTHOR]

The real world is vague, unclear and full of ambiguity, and are inevitable. The classical statistics disregards the extreme, aberrant, uncertain values, and hence a new appropriate tool had to surface. The Analysis of Variance (ANOVA) method is used to compare the response variable's means between several groups that are specified by the factor variable. Another method of data analysis offered by ANOVA is one that is based on statistics and is experimental design-driven, or Design of Experiment (DOE). In DOE, there are single and two-factor experimental designs depending on, observing the effect of number of factor(s) on output variable as a primary interest. Among all the single factor experimental designs, Completely Randomized Design (CRD) is the simplest and flexible design. In this design, treatments are randomly allocated to the experimental units over the entire experimental material. Each treatment is repeated to increase the efficiency of the design. CRD is more appropriate to use when the data is homogenous. The objective that deals with the preparation and analysis of experiments is experimental design. The treatments are apportioned to the exploratory units at random in the fully randomized experimental design. When the observed data are fuzzy observations rather than precise numerical values, the CRD is expanded in this study. In this paper, an innovative Triangular Fuzzy Number (TFN) in the fuzzy Completely Randomized Design (FCRD) analysis statistical method for evaluating CRD model hypotheses on fuzzy data is presented. To convert the fuzzy totally randomized design model into two crisps CRD models using the suggested way, and then convert to lower and upper models are used in fuzzy hypothesis. Determine the fuzzy hypothesis for the fuzzy CRD model based on the hypotheses of the two crisp CRD models using the decision rules. The fuzzy test appears to be a competitive tool in circumstances with ambiguous data, particularly linguistic ambiguity because it is more adaptable than the conventional test of significance. This paper presents and illustrates a novel fuzzy triangular number-based approach to fuzzy CRD analysis. This paper also explores how flexible a CRD may be when handling uncertain elements. This study provides an example of a new method for fuzzy CRD analysis employing TFN. [ABSTRACT FROM AUTHOR]

This study conducts a quantitative research survey on the development of queueing networks over years. Development is a process of gradual change that takes place over many years, during which a theory slowly progress and attain a good state. Queueing theory has been through many developments which made its existence inevitable in every field. Queueing networks can be considered as a collection of nodes, where each node stands for a service facility. It has been proved to be a powerful and versatile tool for modelling facilities in manufacturing units and telecommunication networks. This paper presents the development in Queueing networks and its types over years. This paper's main objective is to give all the analysts and researchers the knowledge about the evolution that happened in Queueing networks over years. [ABSTRACT FROM AUTHOR]

In Heating, Ventilation, and Air Conditioning (HVAC) systems, faults can be occurred due to various reasons such as drift deviation, valve/fan failure, water clogging, air filter obstruction, temperature sensor failure and so on. Similarly in electrical machineries faults can be occurred due to multiple causes such as phase reversal, over or under voltage, starter open/short circuit, bearing problems, insulation breakdown, overloading, thermal unbalance, environmental as well as other technical issues. The faults analysis at various stages of electrical systems are critically important for reliable operation of the system. In view of reliability and safety operations of modern sophisticated electrical systems, faults analysis and its diagnosis are necessary to avoid unaccountable losses. The faults at various stages, its causes, methods of detection and diagnosis, fault classifications are included in this work. The comment on effectiveness methods of detection of fault and diagnosis are included for electrical systems. In the industries, systems are incorporated with monitoring capacity for detection of faults at easy and early stage. This paper mainly focused on advancements in fault detection and diagnosis (FDD) methods with short review of various recent methods. This includes system information representation, methods of FDD, description of faults, fault classification, and decision actions related to maintenance, providing a systematic overview of the current state of FDD. Furthermore, the paper underscores the pivotal roles of FDD in electrical systems, emphasizing its effectiveness in identifying faulty states and taking pre-emptive actions against potential failures or accidents. The discussion extends to developments of current research in FDD approaches for electrical machineries with system monitoring, accompanied by short review of diverse and valuable FDD methodologies. The study concludes by addressing comments on recent trends, future directions, challenges, and prospective solutions in the hybrid and dynamic landscape of FDD. [ABSTRACT FROM AUTHOR]

This paper introduces a novel probability distribution known as the Ejaz distribution (ED), which is characterized by two parameters. The study offers a comprehensive analysis of this distribution, including an examination of key properties such as moments, moment-generating functions, order statistics, and reliability functions. Additionally, the paper explores the graphical representation of essential functions like the probability density function, cumulative distribution function, and hazard rate function, enhancing our visual understanding of their behavior. The distribution's parameters are estimated using the widely accepted method of maximum likelihood estimation. Through real-world examples, the paper highlights the practical applicability of the Ejaz distribution, demonstrating its performance and relevance in diverse scenarios. [ABSTRACT FROM AUTHOR]

Characterization of a probability distribution gives a unique property enjoyed by that distribution. Various approaches are available in the literature to characterize distributions through record values. Many researchers have characterized Exponential, Pareto, and Power function distributions using moments, conditional expectation, and some other characteristics of record values. In this paper, we have characterized these three distributions through conditional variance of adjacent record values. The results have been verified using numerical computation. [ABSTRACT FROM AUTHOR]

The Strip-Plot Design (SPD) is plays an important role in the complete block designs and also using the agricultural, medical and industry fields. SPD is best suited for a two-factor experiment that has more treatments than can be accommodated by a complete block design. In a SPD, one factor is assigned to the horizontal strip plot, one factor is assigned to the vertical - strip plot and one factor is interaction plot. Also, few experimental materials may be rare while other test items may be available in altering doses of other therapeutic factors, which may be expensive or time-consuming. One of the main features of SPD involves three types of experimental errors: row - strip plot error, coloum - strip plot error and interaction plot error. Experimenting across processing steps is essential for studying the interaction of factors where certain factors come from one step and others arrive from the other. The strip-plot design is a very efficient design for investigating multiple-step processes in terms of both resources and time. Strip-plot designs are economical when the factors are hard to change and the process under research has three discrete stages. When we want to study interactions between factors where some factors are from one step and other factors from another step, it is important to conduct experiments across processing steps. The approach is flexible because it can handle experimental design problems involving factors acting at different levels, unlike the existing method. Graphs are widely used representations of both natural and human-made structures. Graph theory can be used to investigate "things that are connected to other things. "Fits nearly everywhere. Some tough problems become easier to solve when they are represented graphically. We reviewed the agricultural field yield of the strip-plot design and early work on the design of industrial strip-plot design in this paper. We have also described the model of strip-plot design. We, therefore, advise experimenters to ensure that their strip-plot designs contain a sufficient number of rows and columns so that valid statistical inference is possible. A bipartite graph is one in which the edges can be divided into two sets without going into sets. A complete bipartite graph is a bipartite graph that is completed. The complete tripartite graph in which the edges can be divided into three set without going into sets. The cubic graph is a graph in which all vertices have degree three. This paper describes the construction and Statistical Analysis of SPD using some particular types of graphs is discussed through numerical examples. [ABSTRACT FROM AUTHOR]

The paper examines the specificity of the modern intelligent control systems. The Big Data technology and Data Science algorithms open up great potential in train traffic management based on hazard prevention. An example is given of high reliability and acceptable accuracy of hazardous railway infrastructure failure prediction using methods based on artificial intelligence. A great deal of attention is given to economical methods of ensuring the required levels of functional safety of train control systems. For that purpose, the efficiency of the digital twin-based method was evaluated. It is shown that, under certain conditions, this method allows significantly reducing the cost of a control system while achieving an acceptably high level of functional safety. The method of virtual second channels is based on the same principle of using information redundancy rather than hardware redundancy. The paper presents and analyses the method of virtual second channels in respect to an axle counter-based train control system. It is established that it is possible to ensure a safety integrity level of an entire control system with a virtual second channel at least as high as SIL3. The above methods ensure, on the one hand, a reduction of the amount of equipment and significantly lower cost of the systems and, on the other hand, requires the creation of additional software and substantiation of the acceptability of the achieved level of functional safety. This matter is within the competence of the developer of the control system. [ABSTRACT FROM AUTHOR]

The aim of the paper is to develop a new Huntsberger type shrinkage estimator for the entropy function of the exponential distribution. The present paper proposes a Huntsberger type shrinkage estimator for the entropy function of the exponential distribution. This Huntsberger type shrinkage entropy estimator is based on test statistic, which eliminates arbitrariness of choice of shrinkage factor. For the developed estimator risk expressions under LINEX loss function and squared error loss function have been calculated. To assess the efficacy of the proposed estimator, numerical computations are performed, and graphical analysis is carried out for risk and relative risks for the proposed estimator. It is also compared with the existing best estimator for distinct degrees of asymmetry and different levels of significance. Based on the criteria of relative risk, it is found that the proposed Huntsberger type shrinkage estimator is better than the existing estimator for the entropy function of the exponential distribution for smaller values of level of significance and degrees of freedom. [ABSTRACT FROM AUTHOR]

In this paper we introduce the Exponential-Pareto mixture distribution. This distribution is associated as mixture of light and heavy-tailed data which arise in a wide class applications including risk analysis. Characteristic function, failure rate function, mean excess, conditional excess distribution are derived. It is proved that the limiting distribution of maxima among n values of rv’s with Exponential-Pareto distribution has Frechet-type form. The maximal likelihood estimation of parameters is discussed. The upper bound of uniform distance between Exponential-Pareto mixture and Pareto distributions is derived. [ABSTRACT FROM AUTHOR]

In this present paper, a class of Lorentzian almost paracontact metric manifolds known as the LPKenmotsu (Lorentzian para-Kenmotsu) is considered that accepts a connection of quarter-symmetric. In this work, it was found that an LP-Kenmotsu manifold is either φ-symmetric or concircular φ-symmetric with respect to quarter-symmetric metric connection if and only if it is symmetric with respect to the Riemannian connection, provided the scalar curvature of Riemannian connection is constant. [ABSTRACT FROM AUTHOR]

Profile monitoring is a critical tool for manufacturing industries to evaluate and maintain quality performance, as well as detect faults. The process of profile monitoring involves observing how variables interact with one another throughout a given period. This enables the understanding of any changes in their functional relationship over time. Generally, control charts are used for monitoring profiles. This paper proposes two new methods to enhance the monitoring of simple and multiple linear regression profiles in Phase II. The proposed methods are based on group runs (GR) and modified group runs (MGR) control charting schemes. The procedure to obtain optimal design parameters for the proposed methods is discussed in detail. The effectiveness of the suggested techniques is assessed through the ARL standard. The study found that the proposed GR and MGR monitoring methods displayed superior performance compared to other available monitoring methods in the literature. A real-life example is illustrated using proposed GR and MGR charting schemes. [ABSTRACT FROM AUTHOR]

In this paper, a quantitative research survey is carried out on discrete-time queueing models. In real-life scenarios, the idea of discrete-time queues has taken on a new meaning. This survey mainly focuses on the unfolding of discrete-time queueing models in recent decades, challenges implied on them and their influence in various fields. The ultimate goal of this paper is to provide enough information to all the researchers and analysts who toil in this field and wish to know more about these models. A few open issues and intriguing future research paths has been discussed. [ABSTRACT FROM AUTHOR]

This paper introduces a novel two - parameter continuous distribution. This distribution is derived from the mixture of the Exponential, Weibull and Ailamujia distributions. The derived distribution is named as "Idz distribution". The probability density function of the Idz distribution is derived and some of its plots are presented. It can be observed that the Idz distribution can generate right tailed unimodal, non-monotonic decreasing and exponential shapes. Further, survival and hazard functions of the Idz distribution are derived. It reveals that the hazard function of the Idz distribution can accommodate three types of failure rate behaviors, namely, non-monotonic constant, right tailed unimodal and nonmonotonic decreasing. Moreover, some properties of Idz distribution such as moments, mean, variance, moment generating function, order statistics and maximum likelihood estimates are derived. In addition, the proposed distribution is applied into a Breast Cancer data and compare with the Exponentiated Generalized Inverse Rayleigh distribution, the Ailamujia Inverted Weibull distribution and the New Extended Exponentiated Weibull distribution. Result shows that the Idz distribution gives better estimates as compared with the said distributions for a given dataset. [ABSTRACT FROM AUTHOR]

This paper deals with the estimation of stress strength reliability parameter R, which is the probability of Y less than X when X and Y are two independent distribution with different scale parameter and same shape parameter. The maximum likelihood method is used to find an estimator for R. We also obtain the asymptotic distribution of the maximum likelihood estimator of R. Based on this asymptotic distribution, the asymptotic confidence interval can be obtained. We also propose bootstrap confidence interval for the parameter R. Analysis of a simulated data and a real life data have been presented for illustrative purposes. [ABSTRACT FROM AUTHOR]

In this research paper, Confidence interval using Maximum likelihood estimation is obtained for Poisson type Length biased exponential class for the parameters. Failure intensity, mean time to failure and likelihood function for the parameter is obtained. Confidence interval has been derived for parameters using maximum likelihood estimation. To study the performance of confidence interval, average length and coverage probability are calculated using Monte Carlo simulation technique. From the obtained intervals it is concluded that Confidence interval for the parameter perform better for appropriate choice of execution time and certain values of parameters. [ABSTRACT FROM AUTHOR]

This paper is a condensed version of the keynote lecture presented at the opening of the fifth Eurasian conference on Risk in Baku, Azerbaijan, October 17 2023. It is mostly based on results of the content analysis of 1500+ peer reviewed papers related to reliability, resilience, risk and safety of infrastructure systems published over the last 25 years, provided by renowned international specialists in these topics. [ABSTRACT FROM AUTHOR]

This paper discusses issues related to the development of technologies and the relationship of this process with economic processes. Due to the rapid digitalization, the importance and role of artificial intelligence are growing. At the same time there are many problems and they are considered in this paper: unemployment of technical workers, a security problem that is associated with the confidentiality, the existing neural networks cannot be suitable for use in all industries etc. When using the generalization method, the authors have made relevant conclusions and recommendations for using Artificial Intellect: to solve the following universal tasks: automatic translation; getting business intelligence; recognition of visual signs; character recognition; information extraction; understanding and analyzing texts; image analysis; ensuring information security and protection against cyber-attacks; speech recognition; robotic tools for the implementation of tasks at different levels and in different fields. [ABSTRACT FROM AUTHOR]

Objective: This paper extends the analysis of imperfect preventive maintenance interspaced with minimal repairs. The aim is to find the intervals of future scheduled maintenance actions considering different recovery factors and costs. Methods: The optimal preventive maintenance scheduling are obtained by minimizing the overall maintenance costs. Minimal repairs interspersed with scheduled imperfect preventive maintenance actions are considered. The model parameters of the power law process are estimated using the maximum likelihood estimation method and a Differential Evolution algorithm is used to solve the maximization problem. Results: The optimal preventive maintenance periods for different levels of maintenance restoration with respect to corrective and preventive maintenance costs are found. Graphs are drawn to highlight the effect of future maintenance costs and the hazard function paths. It is shown that the preventive maintenance becomes more frequent as the equipment ages and the hazard function increases. Also, it is perceived that the scheduled maintenance intervals become shorter as the corrective maintenance becomes more expensive. Conclusion: A hazard rate model which considers minimal repairs interspersed with scheduled imperfect preventive maintenance provides a useful tool for defining the optimal maintenance policy. The results obtained in this paper show that maintenance cost varies widely according to the recovery factor of the maintenance action and that the optimal interval of two consecutive preventive maintenance actions strongly depends on the costs. [ABSTRACT FROM AUTHOR]

The problem of biasness and availability of auxiliary variable for the estimating population mean is a big concern, both can be handled by proposing unbiased estimators in the absence of auxiliary variable. So in this paper unbiased exponential type estimators of population mean have been proposed. The estimators are proposed in the absence of the instrumental variable called the auxiliary variable by taking the advantage of the population and the sample median of the study variable. To about the first order approximation, the theoretical formulations of the bias and mean square error (MSE) are obtained. The circumstances in which the suggested estimators have the lowest mean squared error values when compared to the existing estimators were also deduced. In comparison to the currently used estimators, it was discovered that the suggested estimators of population mean had the lowest MSE, hence highest efficiency. Also least influence from the data's influential observations when it came to accurately calculating the population mean for skewed data. The theoretical findings of the paper are validated by the numerical study. [ABSTRACT FROM AUTHOR]

In the subject of reliability engineering and statistics, a new reliability model is proposed, where survival analysis or life time data analysis is of major importance in the current scenario. The goal of this study is to introduce a new model that has applications to real data sets from the field of survival analysis. Deriving out the new model there are various methods to propose a new model, one of them is by using the method of transforming a variable to the variable of interest and there are numerous transformation methods which are in use right now. The newly proposed model is achieved by using the transformation method known as KM Transformation where it does not require any additional parameters to the baseline distribution which absolutely is an advantage. The model considered in this paper as baseline model is Inverse Weibull distribution with two parameters, one is a scale and other is a shape parameter. Inverse Weibull distribution is a continuous probability distribution which presently has great applications in real life phenomenon as well as so many modifications and advanced studies are introduced in this distribution from various fields. A proper study on the newly proposed model is done by deriving out its various functions and statistical properties such as Probability density function, Cumulative distribution function, Hazard rate function, Moments, Moment generating function, Characteristic function, Quantile function, Order statistics, etc. along with its Probability density function plot and Hazard rate function plot which have both upside-down and decreasing curves. Focusing on the inference procedures, the estimation of the parameters involved in this model is done by using the method of Maximum likelihood estimation. A simulation study for valuing the parameter consistency using two parameter combinations is carried out as well as a data analysis on an actual data set is also conducted. A comparison of the newly proposed model with other popular well-known models such as Inverse Weibull distribution (IW), KME distribution and KMW distribution using R programming language yielded that the new model is a better fit for the real data considered in this paper. The results and conclusions achieved throughout the paper are also mentioned at the last. [ABSTRACT FROM AUTHOR]

Process Capability Analysis (PCA) helps to improve and monitor the quality of the manufacturing products in industries. The most commonly and traditionally applied indices are process capability index and process capability ratio. Many statistical tests require the condition that the data to be approximately normally distributed. When it comes to reality the data often do not follow a normal distribution. In such instances, different approaches are employed. Box-Cox Transformation (BCT) is one such methodology that is often used by quality practitioners relying on single transforming parameter lamda to transform the non-normal data into normal data. The widely used approach to decide the transforming parameter lamda is based on the rounded value of lamda instead of an optimal value of lamda. There are two transforming expressions available in BCT method. The choice of the value for lamda in BCT can have a significant impact on the results. This paper concentrates on the impact of data transformation in BCT method through two different expressions based on an optimal as well as a rounded value of lamda. The influence made by the estimates of process capability and process performance indices is also studied in this paper. The result of the analysis clearly indicates that the optimal value of lamda when employed in the first BCT transformation expression to estimate the process capability indices for non-normal data provides improvised results. For data analysis, Ms-Excel and Minitab 21 software has been used in this study. [ABSTRACT FROM AUTHOR]

This paper introduces an optimization approach to impute missing data within the K-means cluster analysis framework. The proposed method has been applied to Philippine climate data over the previous 18 years (2006-2023) with the goal of classifying the regions according to average annual temperature including the maximum and minimum. This dataset contains missing values which is the result of the weather stations' measurement failure for some time and there is no chance of recovery. As an effect, the regional groupings are greatly affected. This paper adapts a modified method of missing value imputation suitable for climate data clustering, inspired by the work of Bertsimas et al. (2017). The proposed methodology focuses on imputing missing values within observations by finding the value that minimizes the distance between the observation and a cluster centroid in which the Mahalanobis distance is used as the similarity measure. Consequently, the outcomes of clustering obtained through this optimization approach were compared with certain imputation techniques namely Mean Imputation, Expectation-Maximization algorithm, and MICE. The assessment of the derived clusters was conducted using the silhouette coefficient as the performance metric. Results revealed that the proposed imputation gave the highest silhouette scores which means that most of the observations were being clustered appropriately as compared to the results using other imputation algorithms. Moreover, it was found out that most of the areas showing the features of extreme condition are located in the middle part of the country. [ABSTRACT FROM AUTHOR]

This paper proposed a three parameter Maxwell-Gompertz distribution as an extension of Gompertz distribution. Some statistical properties of the distribution such as moments, survival and hazard functions, quantile function, Rényi entropy and order statistics were derived. Maximum likelihood method was used to estimate the model parameters. A simulation study was carried out in order to gain an insight into the performance on small, moderate and large samples. The flexibility of the new distribution was empirically demonstrated in comparison to four other extensions of Gompertz distributions using two real life datasets. [ABSTRACT FROM AUTHOR]

This paper relates to the reliability measures analysis of two identical unit system with reboot facility. Initially, one unit of the system is in operative mode and another unit is kept in cold standby mode. A technician is always available with the system to perform repairing and rebooting activities. Here, the system operative unit failed in safe mode and unsafe mode. During unsafe failure, repair activity cannot be done immediately but first rebooting is done to transform unsafe failure into safe failure, and then repair activity is performed as usual. Sometimes, the technician needs refreshments due to continuous work and provides better services after taking refreshments. The unit works like a new one after repair. The failure time of the unit in safe mode, unsafe mode and technician refreshment request time are assumed to be general while the repair time of the unit, rebooting delay time and technician refreshment time are taken as exponential. Reliability measures such as mean time to system failure, availability of the system, busy period of the repairman, the expected number of visits by the technician and profit values are calculated using tables. [ABSTRACT FROM AUTHOR]

This paper describes the role of queuing theory in developing queuing networks in companies. Queuing networks can be considered as a collection of nodes where each node stands for a service facility. It is a powerful and versatile tool for modeling facilities in manufacturing products. In the realm of service industries like scooter manufacturing, the queuing theory and simulation play a vital role. These concepts help in predicting queue lengths and waiting durations when multiple scooters are manufactured and distributed using first come first serve discipline. Tables are used to explore the availability of furnished scooters in the companies and their comparative study analyzes the waiting scooters and space availability in the companies. [ABSTRACT FROM AUTHOR]

One of the lifetime distributions is the Iwueze distribution, which is constructed by combining the exponential and gamma distributions. In this paper, confidence intervals (CIs) are proposed for the parameter of the Iwueze distribution using the likelihood-based, Wald-type, bootstrap-t, and bias-corrected and accelerated (BCa) bootstrap methods. We evaluated the performance of the proposed CI methods through Monte Carlo simulation in terms of their coverage probability (CP) and average length (AL) in various scenarios. Furthermore, we had also derived the explicit formula for the Wald-type CI, which is straightforward for computation. The simulation results showed that the likelihood-based and Wald-type CIs returned satisfactory results according to coverage probabilities, even for the setting of small sample sizes. On the other hand, both the bootstrap-t and BCa bootstrap CIs yield CPs lower than the nominal confidence level when sample sizes are small. However, as the sample sizes increase, the CP of all CIs tend to approach the nominal confidence level. The parameter values also have a minor influence on the CP of all CIs when the sample size is fixed. Moreover, the AL of all CIs decreases as the sample size increases. The Wald-type and likelihood-based CIs have very similar ALs for all parameter values. In general, the bootstrap-t CI tends to yield the shortest interval. The effectiveness of all CIs was demonstrated by applying them to medical and engineering data, yielding results consistent with those of the simulation study. [ABSTRACT FROM AUTHOR]

In this study, we explore a new probability distribution termed as the Length-Biased Transmuted Mukherjee-Islam (LBTMI) distribution. This exploration enhances the conventional Transmuted Mukherjee-Islam distribution by integrating a weighted transformation approach. The paper examines the probability density function and the corresponding cumulative distribution function associated with the LBTMI distribution. A comprehensive examination of the unique structural properties of the proposed model is carried out, including the survival function, conditional survival function, hazard function, cumulative hazard function, mean residual life, moments, moment generating function (MGF), characteristic function (CF), cumulant generating function (CGF), likelihood ratio test, ordered statistics, entropy measures, and Bonferroni and Lorenz curves. To ensure precise estimation of model parameters, the study employs the maximum likelihood estimation method, contributing significantly to the advancement of statistical modelling in this domain. [ABSTRACT FROM AUTHOR]

The main objective of the paper is to optimize the availability and profit values of the utensil industry. There are three distinct units in the utensil industry and two of them work in reduced state. It is assumed that unit A is failed in complete failure mode while units B and C completely failed through partial failure mode. The system is in a failing condition when one of the units completely fails. There is a qualified technician to fix the fault in the system. Timelines for failure and repair are unrelated to one another. The repair time is exponential while the failure time distribution is general. Many factors, including mean time to system failure, availability, busy period, estimated number of server visits and profit values are calculated from tables. [ABSTRACT FROM AUTHOR]

In this paper we show that there exists an internal dependence of the simultaneous measurements made by the two pairs of linear polarizers operated in each leg of the apparatus in Aspect's version of Einstein-Podolsky-Rosen Gedankenexperiment. The corresponding Shannon-Kolmogorov's information flow linking a polarizer from one leg to a polarizer from the other leg is proportional to the absolute value of this function of dependence. It turns out that if Bell's inequality is violated, then this information flow is strictly positive, that is, the experiment performed at one leg is informationally dependent on the experiment at the other leg. By throwing out the sign of absolute value, we define the signed information flow linking a polarizer from one leg to a polarizer from the other leg which, in turn, reproduces the probabilities of the four outcomes of the simultaneous measurements, predicted by quantum mechanics. We make an attempt to illustrate the seeming random relation between the total information flow, the total signed information flow, and the violation of Bell's inequality in terms of a kind of uncertainty principle. [ABSTRACT FROM AUTHOR]

In this paper, we consider a system with a finite number of components. It is assumed that the system architecture is a series format. The system fails when any one of the components fails. The case where the lifetimes of the components, are independently distributed and have pathway density is considered. Then the survival function, hazard function, the expected time to failure, general moments, etc. of the system lifetime are computed. It is shown that the hazard function can have many types of shapes, including bathtub shapes. The estimation of stress-strength reliability is considered based on the method of maximum likelihood estimation when both stress and strength variables follow the pathway model. Finally, to show the applicability of the proposed model in a real-life scenario, remission time data from cancer patients is analyzed. [ABSTRACT FROM AUTHOR]

n this present paper, we classify and explore the geometrical significance of a class of Lorentzian almost paracontact metric manifolds namely Lorentzian para-Kenmotsu (briefly LP-Kenmotsu) mani- folds whenever the manifolds are either conformally flat or conformally symmetric. It was found that a conformally flat LP-Kenmotsu manifold is of constant curvature and a conformally symmetric LP-Kenmotsu manifold is locally isomorphic to a unit sphere. At the end, we obtain the scalar curvature of φ-conformally flat LP-Kenmotsu manifolds [ABSTRACT FROM AUTHOR]

In this paper, we analysed the multiple working vacation queuing model with reneging under a single server policy. Reneging describes the situation where a customer or entity decides to leave the queue before being served. The presence of reneging behaviour affects queue and service efficiency, as customers leaving the queue prematurely can impact overall system performance and customer satisfaction. In this model, customers arrive at a service facility and form a queue to be served by a single server. The arrival follows the Poisson distribution, and the service follows the exponential process. Batches of customers are served under the General Bulk Service Rule. In GBSR, rather than individual customer arriving at a queue one by one, customers arrive in groups or batches. Thus, each batch of service contains a minimum of 'a' units and a maximum of 'b' units of customers. The steady-state equation, the various performance measures for the system, and particular cases of the described model are derived. [ABSTRACT FROM AUTHOR]

This paper investigates the estimation of the unknown parameter in the XLindley distribution using record values and inter-record times, both in classical and Bayesian frameworks. It also delves into Bayesian prediction of a future record value. We also study the problem of estimation and prediction for the XLindley distribution based on lower records alone. A simulation study, as well as an analysis of a real data example, are conducted for comparison and illustration. The numerical findings underline that including the inter-record times in the study may enhance the performance of the estimators and predictors. [ABSTRACT FROM AUTHOR]

The paper deals with the cost benefit analysis of a two non-identical unit cold standby system model with the implementation of preventive maintenance (PM) on the priority unit after it has operated for a random duration. The objective is to evaluate the economic viability and performance of such system. A single repairman is consistently available within the system, responsible for both PM and repair of each failed unit. The priority in repair is given to priority (p) unit over ordinary (o) unit. The failure time distribution of each unit is assumed to be exponential while the repair time distribution of both the unit is taken as inverse Gaussian. The PM time and time to PM of the priority unit are correlated having their joint distributions as bivariate exponential. By considering the regenerative point technique, various measures of system effectiveness are obtained. [ABSTRACT FROM AUTHOR]

An acceptance sampling plan is a sampling procedure with a set of rules for making decisions about a lot of products. The decision is based on the number of defectives in a sample. The sampling inspection plans which are developed for taking decision about a lot based on lifetime of the product are called reliability sampling plans. In this paper, we have developed Acceptance sampling plan (ASP) based on truncated life tests when the lifetime of a product follows the exponentiated generalized inverse Rayleigh distribution (EGIR). The minimum sample sizes needed to ensure the specified life percentile are obtained for a fixed value of the consumer™s confidence level. The operating characteristic values according to the different quality levels are obtained and the minimum ratios of the mean life to the specified life are calculated. The important tables based on the suggested acceptance sampling plan are calculated and illustrated. [ABSTRACT FROM AUTHOR]

In this study, we employ a weighted transformation approach to introduce a novel model that generalises the Transmuted Mukherjee-Islam distribution. The resulting generalized distribution is referred to as the Weighted Transmuted Mukherjee-Islam (WTMI) distribution The paper thoroughly explores the probability density function (PDF) and the corresponding cumulative distribution function (CDF) associated with the WTMI distribution. A thorough investigation of the distinctive structural properties of the proposed model is conducted, including survival function, conditional survival function, hazard function, cumulative hazard function, mean residual life, moments, moment generating function (MGF), characteristics function (CF), cumulant generating function (CGF), likelihood ratio test, ordered statistics, entropy measures, and Bonferroni and Lorenz curves. The maximum likelihood estimation method is employed for the precise estimation of model parameters. [ABSTRACT FROM AUTHOR]

This paper proposes a procedure for formulating the software reliability growth model using the non-homogeneous poisson process. We consider the software reliability growth model, which includes imperfect debugging, change points, and testing effort. Nevertheless, when formulating their software reliability models, the majority of scientists make the assumption of a constant detection rate per fault. When software is tested, they all suppose that each fault has an equal chance of being detected and that the rate is equal between generations. In practice, the fault detection rate varies depending on the test teams' abilities, program size, and software properties. Troubleshooting, even in the most realistic situations relevant to the error reintroduction rate due to incomplete debugging phenomena. In this case, changes in error detection and error introduction rates during software development program. Therefore, here we incorporate the generalized logic test workload function and change points. Parameters in software reliability modeling. Estimated using the least squares estimation method unknown parameters of the new model. Therefore, in our newly proposed model, we collect software testing data. use data from a practical application to illustrate the proposed model. Experimental results show that the proposed SRGM framework for imperfect debugging of integrated test jobs and change points has fairly accurate prediction capabilities. [ABSTRACT FROM AUTHOR]

Juice is a non-fermented beverage that is obtained by squeezing fruits to increase immunity. Generally, juice contains calcium, vitamin, iron, etc. to give the refresh tests. There are multiple steps to store the juice at large levels such as storing, grinding pasteurization, etc. In this paper, the performance and reliability measures of a juice plant are discussed. The juice plant has three distinct units. Unit A has washing and storage tank, unit B has grinding, blending, evaporation and pasteurization, and unit C has bottling, labeling and packing units. If any unit partially fails then the system works to a limited extent. A technician is always available to repair the failed unit. The system fails when one unit completely fails. In this paper, the failure time and repair time follow general distributions. The regenerative point graphical technique is used to explore the reliability measures. [ABSTRACT FROM AUTHOR]

In an engineering setup, one is interested to know and determine the reliability of the system of different components. These components are usually subjected to different kinds of stress, and the reliability of the components needs to be estimated under stress. In this paper, we aim to estimate the reliability of a multicomponent stress-strength model assuming that the components of the system are working independently with a common life distribution. The system follows a comparatively new distribution named as; Generalized X-Exponential bathtub failure rate distribution. This paper studies the usefulness of this distribution in terms of estimating the maximum likelihood estimate of the reliability parameter and its asymptotic confidence intervals. Paper uses methods of parametric estimation and reliability estimation. Results are computed using Monte Carlo simulation for small samples. Real data set is presented to evaluate the performance of Generalized X Exponential Distribution (GXED) reliability estimator. Findings show that with the usage of proposed distribution, estimator of reliability parameter fits very well to the real-world situations. [ABSTRACT FROM AUTHOR]

The record values data have received the attention of researchers in statistics for over seven decades. Through these decades the records have played a significant and widely utilized role for statistical inference in parameter estimation, predicting future values, hypothesis tests, as well as stressstrength tests, and characterizing distributions. In this paper, the types of record values, some distributional properties, and statistical inferences of record values and their applications are reviewed. The purpose of this paper is to shed light on the role of record values in statistical inference. Therefore, we will examine this issue from two perspectives, the first perspective being estimation and the second perspective being prediction. These are through some of the most important lifetime distributions are Exponential, Weibull, Gumbel, Geometric, Pareto, Generalized exponential, Rayleigh, Lomax, and Nadarajah-Haghighi distributions. I hope that the findings of this paper will be useful for researchers in various fields and lead to further enhancement of research in record values theory and its applications. [ABSTRACT FROM AUTHOR]