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Quantum-dot cellular automata (QCA) is a promising technology, which seems to be the prospective substitute for complementary metal-oxide semiconductor (CMOS). It is a high speed, high density and low power paradigm producing efficient circuits. These days, most of the smart devices used for computing, make use of random access memory (RAM). To enhance the performance of a RAM cell, researchers are putting effort to minimize its area and access time. Multilayer structures in QCA framework are area efficient, fast and immune to the random interference. Unlike CMOS, QCA multilayer architectures can be designed using active components on different layers. Thus, using multilayer topology in the design of a RAM cell, which is not yet reported in the literature can improve the performance of RAM and hence, the computing device. This paper aims to present the modular design of RAM cell with multilayer structures in the QCA framework. The fundamental modules such as XOR gate, 2:1 multiplexer and D latch are proposed here using multilayer formations with the goal of designing a RAM cell with the provision of read, write, set and reset control.

All the modules used to design a RAM cell are designed using multilayer approach in QCA framework.

The proposed multilayer RAM cell is optimized and has shown an improvement of 20% in cell count, 30% in area, 25% in area latency product and 48.8% in cost function over the other efficient RAM designs with set/reset ability reported earlier. The proposed RAM cell is further analyzed for the fault tolerance and power dissipation.

Due to the multilayer structure, the complexity of the circuit enhances which can be eliminated using simple architectures.

The performance metrics and results obtained establish that the multilayer approach can be implemented in the QCA circuit to produce area efficient and optimized sequential circuits such as a latch, flip flop and memory cells.

This study examines the effect of housing environment on residents’ satisfaction and happiness using the data collected from selected residents of Gurugram, an urban locality in India.

Using the convenience-cum-judgmental sampling technique, data was collected from 321 residents of 17 gated private housing estates and tested by performing factor analysis and partial least squares – structural equation modeling.

The results revealed that maintenance service at housing estates significantly influences residents’ satisfaction followed by social infrastructure, dwelling attributes and residential amenities, whereas the accessibility aspect has no significant impact on residents’ satisfaction and happiness. Results also show a significant impact of social infrastructure on residents’ happiness, and most notably, residents’ satisfaction has a significant influence on their happiness.

The findings of this study are likely to provide valuable insight into housing stakeholders (government officials; real estate developers; property and construction professionals, i.e. planners, architects and maintenance managers) to improve the attributes in urban housing setting and neighborhood facilities to upsurge the residents’ satisfaction and happiness level toward the housing estates and townships, which leads to quality and happiness in residents’ life.

According to the authors’ knowledge, the present study is the first to provide an inclusive way toward showcasing the key antecedents of residents’ satisfaction and happiness in the Indian urban housing context. Authors anticipate that future researchers will find present research as a valuable contribution to the residents’ satisfaction and happiness in urban housing planning and revitalization of urban locations.

The purpose of this paper is to evaluate the reliability indices such as reliability, mean time to failure and sensitivity analysis.

A non-repairable multi-state complex system with two subsystems, namely, S₁ and S₂, is studied. The subsystems S₁ and S₂ are multi-state weighted r-out-of-n: G and s-out-of-m: G systems, respectively. Every component of the sub-system S₁ consists of linear (f, l, k): G system, and the sub-system S₂ consists of circular (f, l, k): G system. The subsystems are connected in series arrangement and components of these subsystems are arranged in parallel.

Markov stochastic process has been applied to obtain probability of components of the subsystems and various results discuss such as reliability, mean time to failure and sensitivity analysis with the help of the universal generating function.

In this work, reliability measures of the purpose system can be enhanced under the high profit.

The purpose of this research is to calculate and enhance the cheese cheddar manufacturing plant efficiency under actual workplace conditions by measuring reliability, availability and maintainability (RAM) indices. The authors highlight how RAM analysis is important in determining periodic maintenance and in scheduling and managing the appropriate maintenance policy.

The current work is conducted using statistical approaches to evaluate failure and repair statistics. The RAM estimation was calculated on the basis of quantitative data obtained over a span of 32 months. Descriptive statistics, Pareto analysis, as well as the presumption of independence were ensured through trend and serial correlation tests. In addition, the reliability and maintainability of the cheddar cheese processing plant and its machines were calculated at various mission periods.

The primary goal of the implementation approach is to understand the fault patterns and the accurate quantitative assessment of the reliability and maintainability of the cheddar production plant. The findings revealed the essential aspects of the line, which need improvement by an appropriate maintenance program.

This study is intended to serve to highlight the RAM assessment and its impact on the performance of the real-time system. The benefit of the technique is the continual control of the manufacturing process by means of acceptable indexes, whose use corresponds to a continuous improvement process.

Most industrial customers are looking for products that meet the functional performance needs and have predictable life cycle cost (LCC). Due to design problems and poor product support, these systems are not able to meet the customers' requirements. Major causes of customer dissatisfaction are often traced back to unexpected failures, leading to unexpected costs. However, with proper consideration of reliability, availability, maintainability and supportability (RAMS) in the design, manufacturing, and installation phases, the number of failures can be reduced and their consequences minimized. Based on a case study in a manufacturing company, an approach for integration of RAMS and risk analysis in design, development and manufacturing is presented. The importance of LCC analysis, use of feedback information, and integration of various information sources to facilitate easy RAMS implementation, in combination with risk analysis in the design phase, is discussed. An approach is suggested for integration of RAMS in the Stage Gate model for project and work process management, coordination and control, to reduce risk. A training program, developed and implemented during the study to create awareness and to improve learning and understanding of RAMS' aspects of existing and future products and processes, is also presented.

Dealers positioned at the downstream of the supply chains are those who can directly influence demand scenario for the manufacturer. However, manufacturer has to ensure that the influence is favorable by competitively fulfilling the anticipations of the dealers. In this regard, the purpose of this paper is focused on developing sustainable strategic relationships between manufacturer and dealer.

In this paper, the basic requirements of the dealers expected to be fulfilled by a manufacturer are analyzed by applying fuzzy Analytic Hierarchy Process and fuzzy Quality Function Deployment. The said approach is implemented in a case situation of a paint manufacturing company in India, and the results are analyzed to provide directions for the company to strategically align manufacturer–dealer relationships.

It was found that the case company has to focus mainly on promotions and advertisements, painters meet, and recognition offered to the dealers. Although pricing was also considered as one of the prominent aspects yet through competitive assessment the case company was found to be better off compared to its competitors.

As the results obtained in the current study are specific to a manufacturing environment, they cannot be generalized for all the companies. However, similar approach can be adopted for analyzing the customer requirements in order to achieve dealers’ attractiveness and satisfaction.

The application of proposed approach assists a manufacturer to pursue right strategy to practice for achieving dealer attractiveness and satisfaction. This will definitely help the supply chain managers to have the right requirements of the dealers’ are fulfilled on priority.

The purpose of this study is to extend the cubic B-spline quasi-interpolation (CBSQI) method via Kronecker product for solving 2D unsteady advection-diffusion equation. The CBSQI method has been used for solving 1D problems in literature so far. This study seeks to use the idea of a Kronecker product to extend the method for 2D problems.

In this work, a CBSQI is used to approximate the spatial partial derivatives of the dependent variable. The idea of the Kronecker product is used to extend the method for 2D problems. This produces the system of ordinary differential equations (ODE) with initial conditions. The obtained system of ODE is solved by strong stability preserving the Runge–Kutta method (SSP-RK-43).

It is found that solutions obtained by the proposed method are in good agreement with the analytical solution. Further, the results are also compared with available numerical results in the literature, and a reasonable degree of compliance is observed.

To the best of the authors’ knowledge, the CBSQI method is used for the first time for solving 2D problems and can be extended for higher-dimensional problems.

This study examines the scanning/strategy relationship in the context‐specific setting of the health care industry. It extends the current research on the strategy/scanning relationship to include performance. Results confirm the moderating role played by environmental scanning activities in the strategy/performing relationship, thus providing further evidence for the contingency relationship among the environment, the organization's internal processes, and performance.

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 optimize the performance for complex repairable system of paint manufacturing unit using a new hybrid bacterial foraging and particle swarm optimization (BFO-PSO) evolutionary algorithm. For this, a performance model is developed with an objective to analyze the system availability.

In this paper, a Markov process-based performance model is put forward for system availability estimation. The differential equations associated with the performance model are developed assuming that the failure and repair rate parameters of each sub-system are constant and follow the exponential distribution. The long-run availability expression for the system has been derived using normalizing condition. This mathematical framework is utilized for developing an optimization model in MATLAB 15 and solved through BFO-PSO and basic particle swarm optimization (PSO) evolutionary algorithms coded in the light of applicability. In this analysis, the optimal input parameters are determined for better system performance.

In the present study, the sensitivity analysis for various sub-systems is carried out in a more consistent manner in terms of the effect on system availability. The optimal failure and repair rate parameters are obtained by solving the performance optimization model through the proposed hybrid BFO-PSO algorithm and hence improved system availability. Further, the results obtained through the proposed evolutionary algorithm are compared with the PSO findings in order to verify the solution. It can be clearly observed from the obtained results that the hybrid BFO-PSO algorithm modifies the solution more precisely and consistently.

There is no limitation for implementation of proposed methodology in complex systems, and it can, therefore, be used to analyze the behavior of the other repairable systems in higher sensitivity zone.

The performance model of the paint manufacturing system is formulated by utilizing the available uncertain data of the used manufacturing unit. Using these data information, which affects the performance of the system are parameterized in the input failure and repair rate parameters for each sub-system. Further, these parameters are varied to find the sensitivity of a sub-system for system availability among the various sub-systems in order to predict the repair priorities for different sub-systems. The findings of the present study show their correspondence with the system experience and highlight the various availability measures for the system analyst in maintenance planning.