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The purpose of this study is to check the reliability of a multi-pin joint to be a fail-safe joint by considering different geometric and material parameters. The pin joints are made of uni-directional fiberglass that has been impregnated with epoxy composites incorporating 3% nano-clay.

This study incorporates the analysis of multi-pin joints experimentally, numerically and statistically using the Weibull approach. During analyses, geometrical parameters edge to diameter (E:D), longitudinal pitch to diameter (F:D), side edge to diameter (S:D) and transverse pitch to diameter (P:D) were analyzed using the Taguchi method with a higher-the-better L16 orthogonal array.

This study aims to develop multi-pin laminated joints to attain higher reliability, which have been designated as fail-safe joints for the intended application and which have higher joint strength. The study reveals that to achieve 99% reliability or 1% probability of failure using the Weibull approach, 24.4% load decrement from the experimental result recorded for three-pin joint configuration at E:D = 4, F:D = 5, S:D = 4 and P:D = 5. Similarly, for the four-pin configuration at E:D = 4, F:D = 4, S:D = 4 and P:D = 5, 23.07% of load decrement observed from the experimental result implies that the expected load with a 99% reliability offers a safe load.

A reliability analysis on multi-pin joints was not conducted in structural application. Composite materials are used because of high reliability and high strength-to-weight ratio. So, in the present work, reliability of the multi-pin joint is analyzed using Weibull distribution.

This study aims to evaluate the failure behavior of glass fiber-reinforced epoxy (GFRE) laminate subjected to cyclic loading conditions. It involves experimental investigation and statistical analysis using Weibull distribution to characterize the failure behavior of the GFRE composite laminate.

Fatigue tests were conducted using a tension–tension loading scheme at a frequency of 2 Hz and a loading ratio (R) of 0.1. The tests were performed at five different stress levels, corresponding to 50%–90% of the ultimate tensile strength (UTS). Failure behavior was assessed through cyclic stress-strain hysteresis plots, dynamic modulus behavior and scanning electron microscopy (SEM) analysis of fracture surfaces.

The study identified common modes of failure, including fiber pullouts, fiber breakage and matrix cracking. At low stress levels, fiber breakage, matrix cracking and fiber pullouts occurred due to high shear stresses at the fiber–matrix interface. Conversely, at high stress levels, fiber breakage and matrix cracking predominated. Higher stress levels led to larger stress-strain hysteresis loops, indicating increased energy dissipation during cyclic loading. High stress levels were associated with a more significant decrease in stiffness over time, implying a shorter fatigue life, while lower stress levels resulted in a gradual decline in stiffness, leading to extended fatigue life.

This study makes a valuable contribution to understanding fatigue behavior under tension–tension loading conditions, coupled with an in-depth analysis of the failure mechanism in GFRE composite laminate at different stress levels. The fatigue behavior is scrutinized through stress-strain hysteresis plots and dynamic modulus versus normalized cycles plots. Furthermore, the characterization of the failure mechanism is enhanced by using SEM imaging of fractured specimens. The Weibull distribution approach is used to obtain a reliable estimate of fatigue life.

This paper aims to discuss a comprehensive survey on fuzzy-based clustering techniques. The determination of an appropriate sensor node as a cluster head straightforwardly affects a network’s lifetime. Clustering often possesses some uncertainties in determining suitable sensor nodes as a cluster head. Owing to various variables, selection of a suitable node as a cluster head is a perplexing decision. Fuzzy logic is capable of handling uncertainties and improving decision-making processes even with insufficient information. Then, state-of-the-art research in the field of clustering techniques has been reviewed.

The literature is presented in a tabular form with merits and limitations of each technique. Furthermore, the various techniques are compared graphically and classified in a tabular form and the flowcharts of important algorithms are presented with pseudocodes.

This paper comprehends the importance and distinction of different fuzzy-based clustering methods which are further supportive in designing more efficient clustering protocols.

This paper fulfills the need of a review paper in the field of fuzzy-based clustering techniques because no other paper has reviewed all the fuzzy-based clustering techniques. Furthermore, none of them has presented literature in a tabular form or presented flowcharts with pseudocodes of important techniques.

This paper aims to explore the effect of bed temperature, primary layer thickness and infill pattern (rectilinear, honeycomb, triangular) on the mechanical properties of tensile strength and bending strength of 3D printed parts.

Samples in accordance to various ASTM standards were printed by fused deposition modelling (FDM) method by varying the various input paramaters such as bed temperature, primary layer thickness and infill pattern (rectilinear, honeycomb, triangular). Tensile and bending testing was carried out on the printed parts, and post to the testing, fractography has been carried out using scanning electron microscope.

With increase in bed temperature tensile strength and flexural strength first increases then decreases. With the increase in primary layer thickness, tensile strength and flexural strength increase. With regard to infill patterns, triangular and honeycomb exhibit better tensile strength and better flexural strength.

The 3D printing is increasingly becoming important for manufacturing of engineering parts, determining the process parameters which could result in better mechanical and physical properties shall certainly help designers and manufacturers globally.

This work elucidates the effect of various process parameters of FDM on tensile and flexural properties of the samples.

The purpose of this paper is to investigate and understand academic English language-related challenges in listening and speaking faced by English as a foreign language (EFL) international Master students enrolled in various taught Master programs in a Malaysian university from the viewpoint/lens of 16 lecturers teaching the students.

This qualitative research relied upon 16 in-depth one-to-one interview sessions with 16 lecturers teaching the taught Master programs at a higher education (HE) institution in Malaysia for data collection. Data collected were coded and categorized according to themes via qualitative analysis software, NVivo.

It was found that academic English language-related challenges in listening and speaking from the viewpoint of the 16 lecturers are such as lack of discipline content knowledge to communicate, lack of confidence in communicating orally, difficulty in understanding lectures and other oral activities in the classroom, and coping with differences in learning culture.

This study suggests policies and programs to equip lecturers and university administrators to overcome the challenges faced by the students in their academic English language practices especially in listening and speaking to ensure meaningful academic adaptation in the current context.

The uniqueness of this study is that it is a retrospection of the lecturers teaching EFL and English as a second language (ESL) international Master students in taught Master programs in a Southeast Asian country. The focus of the retrospection is on academic English language-related challenges in listening and speaking faced by EFL international Master students who are currently pursuing their Master education at a HE institution in Malaysia.

The purpose of this article is to investigate the propagation characteristics (such as particle motion, attenuation and phase velocity) of a Rayleigh wave in a nonlocal generalized thermoelastic media.

The bulk waves are represented with Helmholtz potentials. The stress-free insulated and isothermal plane surfaces are taken into account. Rayleigh wave dispersion relation has been established and is found to be complex. Due to the presence of radicals, the dispersion equation is continuously computed as a complicated irrational expression. The dispersion equation is then converted into a polynomial equation that can be solved numerically for precise complex roots. The extra zeros in this polynomial equation are eliminated to yield the dispersion equation’s roots. These routes are then filtered for inhomogeneous wave propagation that decays with depth. To perform numerical computations, MATLAB software is used.

In this medium, only one mode of Rayleigh wave exists at both isothermal and insulated boundaries. The thermal factors of nonlocal generalized thermoelastic materials significantly influence the particle motion, attenuation and phase velocity of the Rayleigh wave.

Numerical examples are taken to examine how the thermal characteristics of materials affect the existing Rayleigh wave’s propagation characteristics. Graphical analysis is used to evaluate the behavior of particle motion (such as elliptical) both inside and at the isothermal (or insulated) flat surface of the medium under consideration.

The pressing issues of climate change and environmental degradation call for a reevaluation of how we approach economic activities. Both leaders and corporations are now shifting their focus, toward adopting practices and embracing the concept of circular economy (CE). Within this context, the Food and Beverage (F&B) sector, which significantly contributes to greenhouse gas (GHG) emissions, holds the potential for undergoing transformations. This study aims to explore the role that Artificial Intelligence (AI) can play in facilitating the adoption of CE principles, within the F&B sector.

This research employs the Best Worst Method, a technique in multi-criteria decision-making. It focuses on identifying and ranking the challenges in implementing AI-driven CE in the F&B sector, with expert insights enhancing the ranking’s credibility and precision.

The study reveals and prioritizes barriers to AI-supported CE in the F&B sector and offers actionable insights. It also outlines strategies to overcome these barriers, providing a targeted roadmap for businesses seeking sustainable practices.

This research is socially significant as it supports the F&B industry’s shift to sustainable practices. It identifies key barriers and solutions, contributing to global climate change mitigation and sustainable development.

The research addresses a gap in literature at the intersection of AI and CE in the F&B sector. It introduces a system to rank challenges and strategies, offering distinct insights for academia and industry stakeholders.

The purpose of this paper is to measure and analyze the competitive advantage of micro, small and medium enterprises (MSMEs) based upon the Porter’s diamond framework. The major objective is to contribute toward better understanding of various determinants of the diamond model in context within Indian MSMEs.

Extent review of the literature has been done to identify various critical factors contributing to developing a competitive advantage. Exploratory factor analysis and internal consistency tests were performed to verify scales validity and reliability of measuring instrument (questionnaire). In research design, a case study approach has been used, in which MSMEs operating in the pharmaceutical, electrical and electronics, automobile, food and textile sectors were considered.

Study findings indicate that the pharmaceutical sector is more competitive followed by food (112.491) as revealed by the high value of surface area i.e. 150.931. The competitiveness among MSME sectors is mostly affected by demand conditions followed by firm strategy, structure and rivalry. Moreover, the score of diamond axes indicates significant difference with respect to determinants. For instance, in the textile sector, the determinants such as factor conditions and related and supporting industries scored low, for example, 4.710 and 4.280, respectively, which indicates it needs to be strengthened as this sector stands at last position with minimum surface area, for example, 67.398.

Owing to the time and resource constraints, this study was conducted in MSMEs situated in the state of Himachal Pradesh, India, and thus generalizations of results are rather limited.

This study is one of the original being undertaken by authors which helps to underline the importance of various determinants which may help the MSME units to improve competitiveness by implementing effective competitive strategies. The study could be extended to other regions of the country.

This study is a result of extended research on competitiveness and provides an instrument to measure firm ability to be competitive. CEO’s, managers and policy makers from industries as well as government will be able to use this to evaluate their competitive positioning and identify key problem areas which required improvements.

This paper examines the mediating role of manufacturing strategies in the relationship between competitive strategies and firm performance.

This study gathered 250 responses from firms in a developing country's key manufacturing sectors, including mechanical, electronics, automotive, textile and food. First, descriptive statistics were applied to fix outliers like respondent biases, missing values and normality issues. Second, exploratory factors analysis (EFA) ensured data adequacy and homogeneity through Kaiser–Meyer–Olkin (KMO) and Bartlett tests. Finally, confirmatory factors analysis (CFA) was used to identify the interactions (direct, indirect and total effects) between latent variables representing manufacturing strategies (quality, cost, delivery and flexibility), competitive strategies (cost-leadership and differentiation) and firms' performance (sales growth and profitability). In total, two structural equation modelling (SEM) models (SEM-I, SEM-II) were created to test the hypotheses.

Of the 40 items identified by the literature review, four were outliers, and three could not satisfy the EFA criteria (eigenvalue >1). Only 33 items could therefore reach CFA. SEM–I and SEM-II study results found no direct relationship between competitive strategies and firm performance (−0.03 = β = 0.08; p > 0.05). However, the findings revealed that cost-leadership could be an appropriate strategic choice and improved firms' performance if the quality and delivery are focussed (0.20 = β = 0.87; p < 0.001). While competitive strategies impact manufacturing strategies positively, the latter is only a mediator between the cost-leadership strategy and the firms' performance.

This research shows that the cost-leadership approach currently seems viable; however, flexibility and cost requirements were not satisfied due to infeasible product differentiation. These results will be beneficial to executives interested in investing in India's industries.

The study's goal was to identify the factors contributing to the practical completion of Kaizen events (KEs). The effect of the work-study man's characteristics, the supervisor's conduct and the autonomy of the Kaizen team are analysed in this study.

Data were collected from 249 respondents working in the manufacturing sector in India, mainly those who had been involved in Kaizen projects. Three-step procedures, namely, exploratory factor analysis, confirmatory factor analysis and partial least squares, have been applied to test the research hypotheses through structural equational modelling.

The exploratory factor analysis extracted in-role performance, creative performance and human aspect as latent variables explaining work-study man's performance (eigenvalue = 1). The study's findings indicate that the performance of work-study man (in-role, creative and human) and supervisors' conduct is directly related to the success of KEs. It was shown that supervisors might influence the outcomes of KEs only by moderating the human aspects. Additionally, the degree of autonomy of the Kaizen team was found having a significant positive relationship with the success of KEs.

The current study suggests that in-role and creative performance are prime assets of a work-study man. At the same time, the human aspect is a delicate issue that can affect the supervisor's behaviour. Therefore, the study implies that work-study men have the tactics and abilities to work with other co-workers to make a Kaizen project successful.

Although the significance of Kaizen projects has been widely emphasised, past research has failed to establish what factors contribute to the success of Kaizen efforts. Similarly, the supervisor's critical role has been highlighted several times. However, it is unclear how their conduct influences the relationship between work-study man's performance and the effectiveness of Kaizen projects. This study contributes significantly to organisational culture and human resource management by answering these questions.