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The quality of production is an essential factor for the performance measure of a system; a casting process is the same section. It is a type of metal-forming practice in which the required shape of metal is acquired by pouring molten metal into the mold cavity and allowing it to solidify. Casting is done to provide strength and rigidity to the parts of a system for bearing mechanical impacts. The purpose of this paper is to investigate the various aspects which affect the casting process in the foundry industry, in order to optimize the quality of casting, with the assumption that sufficient repair facility is always available.

The considered casting system can have many defects such as the mold shift defect, blowhole defect, defect of shrinkage and porosity, defect of inclusion, defect of cold shut and much more. The studied system can be in three states during the process, namely, good state, failed state and degraded state. The system can repair after minor failures as well as a major failure. The average failure rates of various defects of the system considered as constant and repairs follow the general time distribution. The system is analyzed with the help of the supplementary variable technique and the Laplace transformation for evaluating its various performance measures in order to improve its performance/production.

This work provides a strong understanding of the casting industry, that which failure affects the production of casting and how much. For better understanding, the results have been demonstrated with the help of graphs.

In the present paper, a mathematical model based on the casting process in manufacturing industry has been developed.

Ensuring safe operation of a urea fertilizer plant (UFP) is a vital aspect for its functioning and production. Clearly the safe operation of such systems can only be archived with proper and effective maintenance scheduling and through controlling its failures as well as repairs of the components. Also for this, the concern plant management must have the information regarding the failures that affects the system's performance most/least. The objective of this study is to analyze mathematically the factors that are responsible for the failure/degradation of the decomposition unit of UFP.

The considered system has been modeled by the aid of Markov's birth–death process with two types of failures for its components: variable (which are very similar in practical situations) and constant. The mathematical model is solved by the help of Laplace transform and supplementary variable technique.

In the present paper, the availability, reliability and mean time to failure (MTTF) are computed for the decomposition unit of the UFP. The critical components that affect the reliability and MTTF of the decomposition unit are identified through sensitivity analysis.

In this paper, a mathematical model based on the working of the decomposition unit of a UFP has been developed by considering two types of failure, namely, variable failures rates and constant failure rates (which has not been done in the literature for the decomposition unit). Conclusions in this paper are good references for the improvement of the same.

To analyze the performance of multistate cloud computing transition system through the various reliability measures is the purpose of this paper.

In this article, a mathematical model for a multistate cloud computing transition system with various types of failures has been analyzed by using the Markov process, supplementary variable technique and Laplace transformation.

Various reliability measures such that reliability, availability, mean time to failure (MTTF), mean time to repair and cost analysis have also been analyzed. This article presents some geographic illustrations for the practical utility of the model.

The authors developed a mathematical model to analyze the reliability of the cloud computing transition system by considering the possible failures.

The purpose of this paper is to evaluate the reliability and signature reliability of solar panel k-out-of-n-multiplex system with the help of universal generating function.

Energy scarcity and global warming issues have become important concerns for humanity in recent decades. To solve these problems, various nations work for renewable energy sources (RESs), including sun, breeze, geothermal, wave, radioactive and biofuels. Solar energy is absorbed by solar panels, referred to as photovoltaic panels, which then transform it into electricity that can be used to power buildings or residences. Remote places can be supplied with electricity using these panels. Solar energy is often generated using a solar panel that is connected to an inverter for power supply. As a result, a converter reliability evaluation is frequently required. This paper presents a study on the reliability analysis of k-out-of-n systems with heterogeneous components. In this research, the universal generating function methodology is used to identify the reliability function and signature reliability of the solar array components. This method is commonly used to assess the tail signature and Barlow-Proschan index with independent and identically distributed components.

The Barlow-Proschan index, tail signature, signature, expected lifetime, expected cost and minimal signature of independent identically distributed are all computed.

This is the first study of solar panel k-out-of-n-multiplex systems to examine the signature reliability with the help of universal generating function techniques with various measures.

In today's era of a digital world, mobile phones have now become an essential part in everyday life. The selection of the best mobile phone among the available alternatives is a complex decision making it a problem for the customers. Mobile phone manufactures are facing a lot of problems for launching/introducing a mobile phone according to the requirement of customers and it depends on a number of criteria/attributes such as: technical specifications, price, brand etc.

In the presented work, the above-discussed problem has been considered as a Multi-Criteria Decision Making MCDM problem and an approach based on Kano model with Fuzzy AHP and TOPSIS has been proposed to solve the problem. The Kano model has been used for identifying the different Kano categories of all the features through a customer survey. Fuzzy AHP has been applied to achieve the weights of each feature in order to introduce a best mobile phone for the customers. TOPSIS has been used for ranking of alternatives.

main features with different other sub-features have been selected for the study. Different features have been considered as categories and their Kano categories have been found out. The importance of these features has also been calculated by Fuzzy-AHP in terms of their evaluated weights. Different mobile phones have been ranked by TOPSIS according to their features calculated by Fuzzy-AHP. The proposed approach seems effective for identifying/classifying different attributes/features of mobile phones according to customer's requirements.

Here, different features of a mobile phone have been considered for designing a suitable mobile phone. Thus, this work can help a designer to design and select a suitable feature for a customer-oriented mobile phone.

The purpose of this paper is to investigate the reliability measures, namely, availability, reliability, mean time to failure and expected profit. The authors also analyse the sensitivity of these reliability measures.

Depending upon the real industrial relevance, a generalized system which is easily repairable, extremely reliable and of high quality is expected by the rapid growth of the digital economy. Considering reliability, as one of the performance measure, the authors have designed a complex system which consists of three subsystems, namely, A, B and C in series configuration. The subsystem A consists of n numbers of units which are arranged in parallel configuration, subsystem B consists of two sub-subsystems X and Y align parallel to one another, where X is a type of 1-out-of-n:F. Failure and repair rates are assumed to be follow the general distribution.

The system is deeply studied by the usage of the supplementary variable technique, Laplace transformation and Markov’s law. Various conclusive results such as availability and reliability of the system, mean time to failure, cost and sensitivity analysis have been discussed further.

Through the systematic view of reliability measures of the proposed system, performance of the system can be enhanced under high profit.

The purpose of this paper is to analyse the performance of a wind electric generating power plant through the study of reliability measures. The enhancement of the performance of the wind power plant using various approaches is also an objective of this paper.

This paper describes two models of a wind electric generating power plant using the Markov process and supplementary variable technique and solved with the help of Laplace transformation. The first model has been analyzed without fault coverage and Gumbel-Hougaard family of copula, while the second model of the wind power plant employs fault coverage and Gumbel-Hougaard family of copula which are used to enhance the performance. The proposed methodology is then illustrated in detail considering numerical examples.

Numerous reliability characteristics such as availability, reliability and mean time to failure to examine the performance of the wind power plant have been investigated. Through the comparative study of both the models, the authors concluded that the plant can generate electricity over long periods of time by covering more and more detected faults, which is made possible with two types of repair facility.

In this work, the authors have developed a mathematical model based on a wind electric generating power plant. This work incorporates not only the component failures that stop or degrade the working of the plant but also deals with the catastrophic and repair strategy of the plant.