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This study investigates the repetitive mixed sampling (MRS) plan based on the Cpk index that was proposed by Aslam et al. (2013a). They were the first to study the MRS plan, but they did not pay attention to the fact that submitting to the variable inspection a sample that was first submitted to the attribute inspection, truncates the X observations. In addition, they did not work with an accurate expression to calculate the probabilities of the Cpk statistic.

The authors presented the results based on their original sampling plan through Monte Carlo simulation and defined the theoretical results of their plan when the sample submitted to the variable inspection is no longer the same one submitted to the attribute inspection.

The β risks of the optimum sampling plans presented by Aslam et al. (2013a) are pretty high, exceeding 46%, on average – this same problem was also observed in Saminathan and Mahalingam (2018), Balamurali (2020) and Balamurali et al. (2020), where the β risks of their proposed sampling plans are yet higher.

In terms of originality, the authors can declare the following. It is not a big deal to propose new sampling plans, if one does not know how to obtain their properties. The miscalculations of the sampling plans risks are dangerous; imagine the situation where the acceptance of bad lots exceeds 50% just because the sampling plan was incorrectly designed. Yes, it is a big deal to warn that this type of problem is arising in a growing number of papers. The authors of this study are the pioneers to discover that many studies focusing on the sampling plans need to be urgently revised.

The purpose of this paper is to design a modified version of the double sampling plan to handle the inspection processes requiring a minimum sample size to assure the median life for the products under the new Weibull–Pareto distribution. The economic design of the proposed plan is also considered to assure the product's lifetime with minimum cost.

The authors have developed an optimization model for obtaining the required plan parameters by solving simultaneously two non-linear inequalities and such inequalities have been formed based on the two points on the operating characteristic curve approach.

The results show that the average sample number, average total inspection and total inspection cost under the proposed plan are smaller than the same of a single sampling plan. This means that the proposed plan will be more efficient than a single sampling plan in reducing inspection effort and cost while providing the desired protection.

The proposed modified double sampling plan designed to assure the median life of the products under the new Weibull–Pareto distribution is not available in the literature. The proposed plan will be very useful in assuring the product median lifetime with minimum sample size as well as minimum cost in all the manufacturing industries.

First is to develop the time truncated median control chart for the Rayleigh distribution (RD) and generalized RD (GRD), respectively. Second is to evaluate the performance of the proposed attribute control chart which depends on the average run length (ARL) and third is to include real life examples for application purpose of the proposed attribute control chart.

(1) Select a random sample of size n from each subgroup from the production process and put them on a test for specified time t, where t = ? × µe. Then, count the numbers of failed items in each subgroup up to time t. (2) Step 2: Using np chart, define D = np, the number of failures, which also a random variable follows the Binomial distribution. It is better to use D = np chart rather than p chart because the authors are using number of failure rather than proportion of failure p. When the process is in control, then the parameters of the binomial distribution are n and p0, respectively. (3) Step 3: The process is said to be in control if LCL = D = UCL; otherwise, the process is said to be out of control. Hence, LCL and UCL for the proposed control chart.

From the findings, it is concluded that the GRD has smaller ARL values than the RD for specified values of parameters, which indicate that GRD performing well for out of control signal as compared to the RD.

This developed control chart is applicable when real life situation coincide with RD and GRD.

Researcher can directly use presented study and save consumers from accepting bad lot and also encourage producers to make good quality products so that society can take benefit from their products.

This article dealt with time truncated attribute median control chart for non-normal distributions, namely, the RD and GRD, respectively. The structure of the proposed control chart is developed based on median lifetime of the RD and GRD, respectively.

The present work focuses on evaluating the physical and mechanical characteristics of geopolymer concrete (GPC) by replacing the sodium silicate waste (SSW) in place of traditional river sand. The aim is to create eco-friendly concrete that mitigates the depletion of conventional river sand and conserves natural resources. Additionally, the study seeks to explore how the moisture content of filler materials affects the performance of GPC.

SSW obtained from the sodium silicate industry was used as filler material in the production of GPC, which was cured at ambient temperature. Instead of the typical conventional river sand, SSW was substituted at 25 and 50% of its weight. Three distinct moisture conditions were applied to both river sand and SSW. These conditions were classified as oven dry (OD), air dry (AD) and saturated surface dry (SSD).

As the proportion of SSW increased, there was a decrease in the slump of the GPC. The setting time was significantly affected by the higher percentage of SSW. The presence of angular-shaped SSW particles notably improved the compressive strength of GPC when replacing a portion of the river sand with SSW. When exposed to elevated temperatures, the performance of the GPC with SSW exhibited similar behavior to that of the mix containing conventional river sand, but it demonstrated a lower residual strength following exposure to elevated temperatures.

Exploring the possible utilization of SSW as a substitute for river sand in GPC, and its effects on the performance of the proposed mix. Analyzing, how varying moisture conditions affect the performance of GPC containing SSW. Evaluating the response of the GPC with SSW exposed to elevated temperatures in contrast to conventional river sand.

The development of high-strength engineered cementitious composite (ECC) gains a significant leap in structural engineering. Engineers have been looking for new formulations that combine outstanding compressive strength with increased flexural resistance. This research focuses on the main characteristics, techniques and prospective applications of high-strength ECC. The proposed work explores the composition of such concrete, emphasizing the use of novel additives, fiber reinforcements and optimal particle packing to produce excellent mechanical characteristics and demonstrating how high-strength ECC contributes to incorporate sustainability by potentially lowering the need for supplemental reinforcing and resulting in a lower environmental effect.

This research involves on studying the composition of high-strength ECC and geopolymer-based ECC, the use of novel additives, fiber reinforcements and optimal particle packing. It examines the capacity of high-strength ECC to sustain high loads with an allowable deformation without any catastrophic collapse. It discusses the sustainability aspects of high-strength ECC and its potential alternative as geopolymer-based ECC.

High-strength ECC offers an excellent compressive strength while also providing increased flexural capacity. Employment of copper slag (CS) as a filler material for the production of ECC results in 28.92% lower cost, when compared to the mix developed using conventional river sand. Whereas in the case of geopolymer-based ECC, the cost of production was found to be 31.92% lower than that of the conventional.

High-strength ECC is developed using conventional river sand and industrial by-product, CS as a filler material. The combination of achieving higher compressive strength with an increased use of industrial by-products leads to the development of sustainable high strength ECC. The potential use of high-strength ECC reduces the need for supplementary reinforcing and increases the structural lifetime, resulting in a lower environmental impact.

Following several prior editions and the acquisition of quantitative data indicating a 18% reduction in perceived caregiver burden and a 27% improvement in their quality of life regarding pain/mild discomfort, this present study aims to compile and examine the shared experiences of caregivers participating in the peer-to-peer Expert Caregiver Programme. The aim is to gain a deeper understanding of the programme’s inherent value.

This is a qualitative study of the Expert Caregiver Programme, a peer-to-peer support and learning initiative designed for informal caregivers of individuals with dementia. Over a span of two and a half months, this study observed a group of ten informal caregivers who were participants in the sixth edition of the Expert Caregiver Programme at a Sociosanitary Hospital in Catalonia.

The results have revealed the emergence of two distinct spirals. Firstly, the ongoing challenge of adapting to a degenerative process, coupled with the caregiver's sense of responsibility, leads to an overwhelming situation for the caregiver as far as caregiving and emotional management are concerned. This, in turn, exacerbates their feelings of isolation, fatigue and discouragement. On the other hand, the understanding of the disease and the sense of compassion towards the person with dementia have been identified as pivotal elements in the construction of an upward spiral, creating greater comfort for the caregiver. Consequently, these factors can be effectively addressed within the framework of a programme such as the Expert Caregiver.

The qualitative approach has allowed for a comprehensive and extensive exploration of the caregivers' experiences with individuals suffering from dementia. This has revealed the existence of a positive spiral that can be nurtured through peer support programmes.

In this study, response surface methodology (RSM) is applied to a three-point bending stiffness analysis of low-cost material (PLA) specimens printed using FDM technology to analyze the performance of different internal lattice structures (Octet and IsoTruss principally). The purpose of this study is to extend the definition from a discrete (lattice) model to an analytical one for its use in subsequent design phases, capable of optimizing the type of cell to be used and its defining parameters to find the best stiffness-to-weight ratio.

The representative function of their mechanical behavior is extrapolated through a two-variable polynomial model based on the cell size and the thickness of the beam elements characterizing it. The polynomial is obtained thanks to several tests performed according to the scheme of RSM. An analysis on the estimation errors due to discontinuities in the physical specimens is also conducted. Physical tests applied to the specimens showed some divergences from the virtual (ideal) behavior of the specimens.

The study allowed to validate the RSM models proposed to predict the behavior of the system as the size, thickness and type of cells vary. Changes in stiffness and weight of specimens follow linear and quadratic models, respectively. This generally allows to find optimal design points where the stiffness-to-weight ratio is at its highest.

Although the literature provides numerous references to studies characterizing and parameterizing lattice structures, the industrial/practical applications concerning lattice structures are often still detached from theoretical research and limited to achieving functioning models rather than optimal ones. The approach here described is also aimed at overcoming this limitation. The software used for the design is nTop. Subsequent three-point bending tests have validated the reliability of the model derived from the method’s application.

This paper aims to study the influence of bed temperature on the properties of printed parts and their structural stability.

Material extrusion is a manufacturing technique in which a part is completed layer by layer with molten filament. The first layer is deposited on a build platform called bed, which is usually at a controlled temperature above room temperature. The density, coefficient of thermal expansion and Young’s modulus were determined as a function of the bed temperature. The complex permittivity was determined at different temperatures, with the aim of analyzing the influence of the bed temperature and isothermal treatments on the characteristics of the amorphous phase.

The Young’s modulus presented a non-monotonic behavior, while the coefficient of thermal expansion did not present a clear dependence on the bed temperature. However, a contraction of the dimensions of the parts was observed after heating at temperatures above the glass transition. With treatments at temperatures lower than the glass transition temperature, no changes were observed. However, with treatments at temperatures higher than this, changes in the mobile amorphous region were inferred.

Issues related to the use of parts manufactured by 3D printing after a posterior heating were analyzed: an improvement in the Young’s modulus and a slight variation of the coefficient of thermal expansion were observed. However, a significant variation in dimensions was detected, mainly for the lowest bed temperatures. This is important for possible applications at temperatures above 60°C.

The aim of this review is to present together the studies on textile-based moisture sensors developed using innovative technologies in recent years.

The integration levels of the sensors studied with the textile materials are changing. Some research teams have used a combination of printing and textile technologies to produce sensors, while a group of researchers have used traditional technologies such as weaving and embroidery. Others have taken advantage of new technologies such as electro-spinning, polymerization and other techniques. In this way, they tried to combine the good working efficiency of the sensors and the flexibility of the textile. All these approaches are presented in this article.

The presentation of the latest technologies used to develop textile sensors together will give researchers an idea about new studies that can be done on highly sensitive and efficient textile-based moisture sensor systems.

In this paper humidity sensors have been explained in terms of measuring principle as capacitive and resistive. Then, studies conducted in the last 20 years on the textile-based humidity sensors have been presented in detail. This is a comprehensive review study that presents the latest developments together in this area for researchers.

This study aims to improve the mechanical properties of an object produced by fused deposition modelling with high-grade polymer.

The study uses an ensembled surrogate-assisted evolutionary algorithm (SAEA) to optimize the process parameters for example, layer height, print speed, print direction and nozzle temperature for enhancing the mechanical properties of temperature-sensitive high-grade polymer poly-ether-ether-ketone (PEEK) in fused deposition modelling (FDM) 3D printing while considering print time as one of the important parameter. These models are integrated with an evolutionary algorithm to efficiently explore parameter space. The optimized parameters from the SAEA approach are compared with those obtained using the Gray Relational Analysis (GRA) Taguchi method serving as a benchmark. Later, the study also highlights the significant role of print direction in optimizing the mechanical properties of FDM 3D printed PEEK.

With the use of ensemble learning-based SAEA, one can successfully maximize the ultimate stress and percentage elongation with minimum print time. SAEA-based solution has 28.86% higher ultimate stress, 66.95% lower percentage of elongation and 7.14% lower print time in comparison to the benchmark result (GRA Taguchi method). Also, the results from the experimental investigation indicate that the print direction has a greater role in deciding the optimum value of mechanical properties for FDM 3D printed high-grade thermoplastic PEEK polymer.

This study is valid for the parameter ranges, which are defined to conduct the experimentation.

This study has been conducted on the basis of taking only a few important process parameters as per the literatures and available scope of the study; however, there are many other parameters, e.g. wall thickness, road width, print orientation, fill pattern, roller speed, retraction, etc. which can be included to make a more comprehensive investigation and accuracy of the results for practical implementation.

This study deploys a novel meta-model-based optimization approach for enhancing the mechanical properties of high-grade thermoplastic polymers, which is rarely available in the published literature in the research domain.