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Although Multi-Layer Ceramic Capacitors (MLCC) are known for its better frequency performance and voltage handling capacity, but under various environmental conditions, its reliability becomes a challenging issue. In modern era of integration, the failure of one component can degrade or shutdown the whole electronic device. The lifetime estimation of MLCC can enhance the reuse capability and furthermore, reduces the e-waste, which is a global issue.

The residual lifetime of MLCC is estimated using empirical method i.e. Military handbook MILHDBK2017F, statistical method i.e. regression analysis using Minitab18.1 as well as intelligent technique i.e. artificial neural networks (ANN) using MATLAB2017b. ANN Feed-Forward Back-Propagation learning with sigmoid transfer function [3–10–1–1] is considered using 73% of available data for training and 27% for testing and validation. The design of experiments is framed using Taguchi’s approach L16 orthogonal array.

After exploring the lifetime of MLCC, using empirical, statistical and intelligent techniques, an error analysis is conducted, which shows that regression analysis has 97.05% accuracy and ANN has 94.07% accuracy.

An intelligent method is presented for condition monitoring and health prognostics of MLCC, which warns the user about its residual lifetime so that faulty component can be replaced in time.

Capacitors are one of the most common passive components on a circuit board. From a tiny toy to substantial satellite, a capacitor plays an important role. Untimely failure of a capacitor can destruct the entire system. This research paper targets the reliability assessment of tantalum capacitor, to reduce e-waste and enhance its reusable capability.

The residual lifetime of a tantalum capacitor is estimated using the empirical method, i.e. military handbook MILHDBK2017F, and validated using an experimental approach, i.e. accelerated life testing (ALT). The various influencing acceleration factors are explored, and experiments are designed using Taguchi's approach. Empirical methods such as the military handbook is used for assessing the reliability of a tantalum capacitor, for ground and mobile applications.

After exploring the lifetime of a tantalum capacitor using empirical and experimental techniques, an error analysis is conducted, which shows the validity of empirical technique, with an accuracy of 95.21%.

The condition monitoring and health prognostics of tantalum capacitors, for ground and mobile applications, are explored using empirical and experimental techniques, which warns the user about its residual lifetime so that the faulty component can be replaced in time.

Accessibility to a precise tool for healthcare management and self-precaution among diabetic patients is an absolute necessity. This paper aims to develop and validate diabetes-related awareness instrument (DRAI) – an instrument that measures diabetics awareness about risk factors and prevention strategies.

The reliability and validity of the DRAI were tested with a sample of 112 diabetics. The construct validity of the DRAI was measured using exploratory and confirmatory factor analysis. Item discrimination, reliability, usefulness and validity of the items were determined by performing Cronbach's alpha, item difficulty and discrimination index analysis.

The study finds DRAI – a reliable and valid instrument to assess diabetics awareness towards diabetes mellitus, its associated risk factors and prevention strategies. The value of Cronbach's alpha for all three constructs was above the threshold level of 0.70. Under exploratory factor analysis, “Kaiser–Meyer–Olkin” test value of 0.805 exhibits a meritorious sample adequacy and “Bartlet's test of Sphericity” was statistically significant with p = 0.032. Therefore, results of confirmatory factor analysis (CFA) revealed that all fitness indices of the model to be excellent fit.

The present instrument can help to determine whether the individual is susceptible to diabetes, timely prevention and reduction in the incidence of diabetes mellitus.

DRAI is the first of its kind tool to assess the awareness and knowledge about diabetes-related risk factors and prevention strategies in such a demographically diverse population of India.

This study aims to perform the experimental work on a laboratory-constructed steel truss bridge model on which hammer blows are applied for excitation. The vibration response signals of the bridge structure are collected using sensors placed at different nodes. The different damaged states such as no damage, single damage, double damage and triple damage are introduced by cutting members of the bridge. The masked noise with recorded vibration responses generates challenge to properly analyze the health of bridge structure.

The analytical modal properties are obtained from finite element model (FEM) developed using SAP2000 software. The response signals are analyzed in frequency domain by power spectrum and in time-frequency domain using spectrogram and Stockwell transform. Various low pass signal-filtering techniques such as variational filter, lowpass sparse banded (AB) filter and Savitzky–Golay (SG) differentiator filter are also applied to refine vibration signals. The proposed methodology further comprises application of Hilbert transform in combination with MUSIC and ESPRIT techniques.

The outcomes of SG filter provided the denoised signals using appropriate polynomial degree with proper selected window length. However, certain unwanted frequency peaks still appeared in the outcomes of SG filter. The SG-filtered signals are further analyzed using fused methodology of Hilbert transform-ESPRIT, which shows high accuracy in identifying modal frequencies at different states of the steel truss bridge.

The sequence of proposed methodology for denoising vibration response signals using SG filter with Hilbert transform-ESPRIT is a novel approach. The outcomes of proposed methodology are much refined and take less computational time.

This study aims to include the diagnosis of an old concrete deck steel truss rural road bridge in the damaged and retrofitted state through vibration response signals.

The analysis of the vibration response signals is performed in time and time-frequency domains using statistical features-root mean square, impulse factor, crest factor, kurtosis, peak2peak and Stockwell transform. The proposed methodology uses the Hilbert transform in combination with spectral kurtosis and bandpass filtering technique for obtaining robust outcomes of modal frequencies.

The absence or low amplitude of considered mode shape frequencies is observed both before and after retrofitting of bridge indicates the deficient nodes. The kurtosis feature among all statistical approaches is able to reflect significant variation in the amplitude of different nodes of the bridge. The Stockwell transform showed better resolution of present modal frequencies but due to the yield of additional frequency peaks in the vicinity of the first three analytical modal frequencies no decisive conclusions are achieved. The methodology shows promising outcomes in eliminating noise and visualizing distinct modal frequencies of a steel truss bridge.

The findings of the present study help in analyzing noisy vibration signals obtained from various structures (civil or mechanical) and determine vulnerable locations of the structure using mode shape frequencies.

The literature review gave an insight into few experimental investigations related to the combined application of Hilbert transform with spectral kurtosis and bandpass filtering technique in determining mode frequencies of a steel truss bridge.

This research aims to examine the impact of friction stir processing (FSP) treatment on an aluminum alloy, especially the AD31T alloy derived from the Al-Fe-Mg-Si system. The aim is to assess the influence of different processing techniques on the microstructure and physical and mechanical characteristics of the material, with a specific focus on structural and bulk imperfections inside the stir zone (SZ).

The study demonstrates that augmenting the linear velocity of the tool within the 25–100 mm/min range results in significant enhancements. The enhancements include a decrease in the heat-affected zone (HAZ), a reduction in the extent of volume defects inside the SZ and a more uniform deformation. The microstructural analysis results are corroborated by data acquired from microhardness and electrical conductivity studies, confirming the beneficial influence of modifying the tool’s linear velocity on the material parameters.

This study provides significant observations on the changes in microstructure and the generation of flaws throughout the process of FSP of AD31T alloy. These results have practical implications for improving the characteristics of the alloy and optimizing the production conditions.

All samples exhibit a distinct reduction in electrical conductivity within the initial third of the sample, aligning with the transitional region between the base metal (BM) and the HAZ. This underscores the importance of understanding the transitional zones during FSP.

This paper presents the performance analysis of the automatic ticket vending machine (ATVM) through the functioning of its different hardware and software failures.

Frequent failures in the working of ATVM have been observed; therefore, the authors of the paper intend to analyze the performance measures of the same. Authors have developed a mathematical model based on different hardware and software failures/repairs, which may occur during the operation, with the help of the Markov process. The developed model has been solved for two kinds of failure/repair rates namely variable failures (very much similar to real-time failure) and constant failures. Lagrange's method and Laplace transformation are used for the solution of the developed model.

Reliability and mean time to failure of the ATVM are determined. Sensitivity analysis for ATVM is also carried out in the paper. Critical components of the ATVM, which affect the performance of the same, in terms of reliability and MTTF are also identified.

A mathematical model based on different hardware and software failures/repairs of ATVM has been developed to analyze its performance, which has not been done in the past.

This study aims to identify SHRM (strategic human resource management) essential practices for the TQM (total quality management) program regarding an Indian tire manufacturing company and formulate an inclusive interrelationship to prioritize them.

Semistructured interview with ten experts from the company was made to give SHRM practices scores. The SLR (systematic literature review) and TOPSIS (technique for order of preference by similarity to ideal solution) techniques are used to establish the model for 12 key practices and rank them afterward.

The findings clearly show that strategic planning and staffing, teamwork and leadership development have appeared as the top three essential practices. Simultaneously, performance measurement and evaluation, work design and analysis and promotion are identified as the bottom three practices. These essential practices are identified as contributing attributes.

The findings prioritize the SHRM practices as contributing attributes that help other tire manufacturing industries identify their key practices. Moreover, it provides the necessary inputs comprised of ten experts' decisions to become more active and well prepared.

The novelty of this study is to identify the key practices by using SLR and measured by the TOPSIS method to rank and consider a tire manufacturing company as a case-based approach to gain high productivity and competitive advantage.

The purpose of this paper is to analyse the main components of a wireless communication system, e.g. input transducer, transmitter, communication channel and receiver on the basis of their interconnection for evaluating the various reliability measures for the same.

Markov process and mathematical modelling is used to formulate a mathematical model of the considered system (on the basis of various failures/repairs).

Reliability of the wireless communication system with respect to its components failure is obtained and explained with the graphs. Also, critical components of the system are identified with the aid of sensitivity analysis. At last, mean time to failure with variation in various failures is obtained.

In the present paper, a mathematical model based on the working of the wireless communication system has been developed. Conclusions in this paper are good references for the improvement in the same.