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Article
Publication date: 13 December 2022

Jimut Bahan Chakrabarty, Soumya Roy and Shovan Chowdhury

In order to reduce avoidably lengthy duration required to test highly reliable products under usage stress, accelerated life test sampling plans (ALTSPs) are employed. This paper…

214

Abstract

Purpose

In order to reduce avoidably lengthy duration required to test highly reliable products under usage stress, accelerated life test sampling plans (ALTSPs) are employed. This paper aims to build a decision model for obtaining optimal sampling plan under accelerated life test setting using Type-I hybrid censoring scheme for products covered under warranty.

Design/methodology/approach

The primary decision model proposed in this paper determines ALTSP by minimizing the relevant costs involved. To arrive at the decision model, the Fisher information matrix for Type-I hybrid censoring scheme under accelerated life test setting is derived. The optimal solution is attained by utilizing appropriate techniques following a nonlinear constrained optimization approach. As a special case, ALTSP for Type-I censoring is obtained using the same approach. ALTSP under Type-I hybrid censoring using the variance minimization approach is also derived.

Findings

On comparing the optimal results obtained using the above mentioned approaches, it is found that the cost minimization approach does better in reducing the total cost incurred. Results also show that the proposed ALTSP model under cost function setting has considerably lower expected testing time. Interesting findings from the sensitivity analysis conducted using a newly introduced failure dataset pertaining to locomotive controls are highlighted.

Originality/value

The research introduces a model to design optimum ALTSP for Type-I hybrid censoring scheme. The practical viability of the model makes it valuable for real-life situations. The practical application of the proposed model is exemplified using a real-life case.

Details

International Journal of Quality & Reliability Management, vol. 40 no. 7
Type: Research Article
ISSN: 0265-671X

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Article
Publication date: 1 July 1996

Y.I. Kwon

Proposes Bayesian life test sampling plan for non‐repairable products with exponential lifetime distribution, which are sold under a warranty policy. It is assumed that the…

646

Abstract

Proposes Bayesian life test sampling plan for non‐repairable products with exponential lifetime distribution, which are sold under a warranty policy. It is assumed that the parameter of the lifetime distribution is a random variable varying from lot to lot according to a known prior distribution. Describes constructions of a cost model with three cost components: test cost, accept cost, and reject cost. Presents an algorithm for finding optimal sampling plans which minimize the expected average cost per lot. Describes sensitivity analyses for the parameters for the prior distribution.

Details

International Journal of Quality & Reliability Management, vol. 13 no. 5
Type: Research Article
ISSN: 0265-671X

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Article
Publication date: 3 August 2020

Jimut Bahan Chakrabarty, Shovan Chowdhury and Soumya Roy

The purpose of this paper is to design an optimal reliability acceptance sampling plan (RASP) using the Type-I generalized hybrid censoring scheme (GHCS) for non-repairable…

319

Abstract

Purpose

The purpose of this paper is to design an optimal reliability acceptance sampling plan (RASP) using the Type-I generalized hybrid censoring scheme (GHCS) for non-repairable products sold under the general rebate warranty. A cost function approach is proposed for products having Weibull distributed lifetimes incorporating relevant costs.

Design/methodology/approach

For Weibull distributed product lifetimes, acceptance criterion introduced by Lieberman and Resnikoff (1955) is derived for Type-I GHCS. A cost function is formulated using expected warranty cost and other relevant cost components incorporating the acceptance criterion. The cost function is optimized following a constrained optimization approach to arrive at the optimum RASP. The constraint ensures that the producer's and the consumer's risks are maintained at agreed-upon levels.

Findings

Optimal solution using the above approach is obtained for Type-I GHCS. As a special case of Type-I GHCS, the proposed approach is also used to arrive at the optimal design for Type-I hybrid censoring scheme as shown in Chakrabarty et al. (2019). Observations regarding the change in optimal design and computational times between the two censoring schemes are noted. An extensive simulation study is performed to validate the model for finite sample sizes and the results obtained are found to be in strong agreement. In order to analyze the sensitivity of the optimal solution due to misspecification of parameter values and cost components, a well-designed sensitivity analysis is carried out using a real-life failure data set from Lawless (2003). Interesting observations are made regarding the change in optimal cost due to change in parameter values, the impact of warranty cost in optimal design and change in optimal design due to change in lot sizes.

Originality/value

The research presents an approach for designing optimal RASPs using Type-I generalized hybrid censoring. The study formulates optimum life test sampling plans by minimizing the average aggregate costs involved, which makes it valuable in dealing with real-life problems pertaining to product quality management.

Details

International Journal of Quality & Reliability Management, vol. 38 no. 3
Type: Research Article
ISSN: 0265-671X

Keywords

Available. Open Access. Open Access
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Publication date: 29 September 2023

Siqi Tu

This paper describes the parent–child relationships of upper-middle-class Chinese parents and their adolescent children who were “parachuted” to the United States for private high…

Abstract

This paper describes the parent–child relationships of upper-middle-class Chinese parents and their adolescent children who were “parachuted” to the United States for private high schools. With parents remaining in China and children in the United States, thousands of miles away, such a transnational educational arrangement complicates the already volatile parent–child relationships during the adolescent years. Through ethnographic interviews of 41 students and 33 parents, I demonstrate different forms of child–parent relationships in a transnational education setting: those who found that the further physical and temporal distance has brought the parent–child relationship closer through frequent communications, children who experienced “accelerated growth” yet questioned the necessity, and delicate parent–child relationships due to increasing transnational cross-cultural or intergenerational differences. These types of parent–child relationships are not comprehensive of all the lived experiences of the “parachute generation,” yet they shed new light on transnational education and the unintended emotional dimensions of educational migration. In a transnational context for an economically well-off group, parental absence or separation of children and parents is no longer a clear-cut concept and has different layers of meanings, taking into account the frequency of communication, duration of spring and winter breaks and the existence of third-party agents such as for-profit intermediaries (or educational consultants) and host families. The diverse patterns of parent–child relations reveal the heterogeneity and complexities of “doing family” across geographic spaces and global educational hierarchies, as well as the roles of communication technologies, the tempo of mobilities and educational intermediaries.

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Article
Publication date: 23 August 2019

Haiqing He, Ting Chen, Minqiang Chen, Dajun Li and Penggen Cheng

This paper aims to present a novel approach of image super-resolution based on deep–shallow cascaded convolutional neural networks for reconstructing a clear and high-resolution…

172

Abstract

Purpose

This paper aims to present a novel approach of image super-resolution based on deep–shallow cascaded convolutional neural networks for reconstructing a clear and high-resolution (HR) remote sensing image from a low-resolution (LR) input.

Design/methodology/approach

The proposed approach directly learns the residuals and mapping between simulated LR and their corresponding HR remote sensing images based on deep and shallow end-to-end convolutional networks instead of assuming any specific restored models. Extra max-pooling and up-sampling are used to achieve a multiscale space by concatenating low- and high-level feature maps, and an HR image is generated by combining LR input and the residual image. This model ensures a strong response to spatially local input patterns by using a large filter and cascaded small filters. The authors adopt a strategy based on epochs to update the learning rate for boosting convergence speed.

Findings

The proposed deep network is trained to reconstruct high-quality images for low-quality inputs through a simulated dataset, which is generated with Set5, Set14, Berkeley Segmentation Data set and remote sensing images. Experimental results demonstrate that this model considerably enhances remote sensing images in terms of spatial detail and spectral fidelity and outperforms state-of-the-art SR methods in terms of peak signal-to-noise ratio, structural similarity and visual assessment.

Originality/value

The proposed method can reconstruct an HR remote sensing image from an LR input and significantly improve the quality of remote sensing images in terms of spatial detail and fidelity.

Details

Sensor Review, vol. 39 no. 5
Type: Research Article
ISSN: 0260-2288

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Article
Publication date: 1 December 2001

Zoran Vojinovic and Vojislav Kecman

In this paper we are presenting our research findings on how effective neural networks are at forecasting and estimating preliminary project costs. We have shown that neural…

559

Abstract

In this paper we are presenting our research findings on how effective neural networks are at forecasting and estimating preliminary project costs. We have shown that neural networks completely outperform traditional techniques in such tasks. In exploring nonlinear techniques almost all of the current research involves neural network techniques, especially multilayer perceptron (MLP) models and other statistical techniques and few authors have considered radial basis function neural network (RBF NN) models in their research. For this purpose we have developed RBF NN models to represent nonlinear static and dynamic processes and compared their performance with traditional methods. The traditional methods applied in this paper are multiple linear regression (MLR) and autoregressive moving average models with eXogenous input (ARMAX). The performance of these and RBF neural network and traditional models is tested on common data sets and their results are presented.

Details

Construction Innovation, vol. 1 no. 4
Type: Research Article
ISSN: 1471-4175

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Article
Publication date: 27 July 2012

Ghassan Hossari

The purpose of this paper is to put forward an innovative approach for reducing the variation between Type I and Type II errors in the context of ratio‐based modeling of corporate…

281

Abstract

Purpose

The purpose of this paper is to put forward an innovative approach for reducing the variation between Type I and Type II errors in the context of ratio‐based modeling of corporate collapse, without compromising the accuracy of the predictive model. Its contribution to the literature lies in resolving the problematic trade‐off between predictive accuracy and variations between the two types of errors.

Design/methodology/approach

The methodological approach in this paper – called MCCCRA – utilizes a novel multi‐classification matrix based on a combination of correlation and regression analysis, with the former being subject to optimisation criteria. In order to ascertain its accuracy in signaling collapse, MCCCRA is empirically tested against multiple discriminant analysis (MDA).

Findings

Based on a data sample of 899 US publicly listed companies, the empirical results indicate that in addition to a high level of accuracy in signaling collapse, MCCCRA generates lower variability between Type I and Type II errors when compared to MDA.

Originality/value

Although correlation and regression analysis are long‐standing statistical tools, the optimisation constraints that are applied to the correlations are unique. Moreover, the multi‐classification matrix is a first in signaling collapse. By providing economic insight into more stable financial modeling, these innovations make an original contribution to the literature.

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Article
Publication date: 6 September 2017

Ahmed Naser and Basil Darras

The purpose of this paper is to present a model to predict the micro-hardness of friction stir processed (FSPed) AZ31B magnesium alloy using response surface methodology (RSM)…

158

Abstract

Purpose

The purpose of this paper is to present a model to predict the micro-hardness of friction stir processed (FSPed) AZ31B magnesium alloy using response surface methodology (RSM). Another objective is to identify process parameters and through-thickness position which will give higher micro-hardness values. Moreover, the study aims at defining the factor that exhibits the most effect on the micro-hardness. Friction stir processing (FSP) machine can then be fed with the optimized parameters to achieve desirable properties.

Design/methodology/approach

An experimental setup was designed to conduct FSP. Several AZ31B magnesium samples were FSPed at different combinations of rotational and translational speeds. The micro-hardness of all the combinations of process parameters was measured at different through-thickness positions. This was followed by an investigation of the three factors on the resulting micro-hardness. RSM was then used to develop a model with three factors and three levels to predict the micro-hardness of FSPed AZ31 magnesium alloy within the covered range. The analyses of variance in addition to experimental verification were both used to validate the model. This was followed by an optimization of the response.

Findings

The model showed excellent capability of predicting the micro-hardness values as well as the optimum values of the three factors that would result in better micro-hardness. The model was able to capture the effects of rotational speed, translational speed, and through-thickness position. Results suggest that micro-hardness values were mostly sensitive to changes in tool rotational speed.

Originality/value

FSP is considered to be one of the advanced microstructural modification techniques which is capable of enhancing the mechanical properties of light-weight alloys. However, the lack of accurate models which are capable of predicting the resulted properties from process parameters hinders the widespread utilization of this technique. At the same time, RSM is considered as a vital branch of experimental design due to its ability to develop new processes and optimize their performance. Hence, the developed model is very beneficial and is meant to save time and experimental effort toward effective use of FSP to get the desired/optimum micro-hardness distribution.

Details

Multidiscipline Modeling in Materials and Structures, vol. 13 no. 3
Type: Research Article
ISSN: 1573-6105

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Article
Publication date: 6 February 2017

Bruna Teodoro Barbosa, Jéssica Ferreira Rodrigues and Sabrina Carvalho Bastos

People are increasingly concerned about food and health and are seeking enriched products. One way to add nutritional value to yogurt consists of the addition of nutritional…

447

Abstract

Purpose

People are increasingly concerned about food and health and are seeking enriched products. One way to add nutritional value to yogurt consists of the addition of nutritional flour. However, it is necessary to optimize formulations that meet the consumers’ expectations. Thus, the purpose of this paper is to aim at sensory optimization of a strawberry yogurt enriched with different flours.

Design/methodology/approach

The optimal concentrations of each flour were defined using the Just-about-right-scale test. Then, an acceptance test was used to assess the samples at optimal concentrations.

Findings

It was observed that the strawberry yogurt should include 1.275 percent golden flaxseed flour, 1.093 percent green banana flour, 1.075 percent eggplant flour and 3.420 percent oatmeal flour. All formulations had good acceptability and the yogurt added with the addition of golden flax flour and the traditional product received similar sensory acceptance. Thus, it is possible to add nutritional value to strawberry yogurt by maintaining its sensory quality.

Research limitations/implications

More detailed studies on the shelf-life of yogurt are necessary to enable the incorporation of flours into yogurt as heat, light and oxygen can reduce the beneficial effects of flours. Therefore, researchers should test the proposed propositions further.

Practical implications

Optimization of an enriched yogurt is a good alternative to provide a product that meets consumers’ expectations, besides adding value to the product. However, there are technological challenges when adding functional components in foods. Thus, this study aimed at sensory optimization of a strawberry yogurt enriched with different flours.

Social implications

The authors aimed to provide a healthy product to the market as well as contribute toward product variety in the market.

Originality/value

There are few studies in respect to the sensory aspects of enriched yogurts. Therefore, this work will aid future studies, supporting the optimization of functional products and contributing toward product variety in the market.

Details

British Food Journal, vol. 119 no. 2
Type: Research Article
ISSN: 0007-070X

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Article
Publication date: 1 March 2006

Nermin Ozgulbas and Ali Serhan Koyuncugil

The objective of this study is to describe financial profiles of firms via data mining method and obtain vital characteristics of performance level for the firms, which have the…

600

Abstract

The objective of this study is to describe financial profiles of firms via data mining method and obtain vital characteristics of performance level for the firms, which have the best financial profile of the health sector. In this study, public hospitals needed an urgent financial solution under the health sector reform steps were selected for implementation. The study covered 645 Ministry of Health hospitals, which have revolving fund in Turkey. Year of 2004 data was used in the study. As the methodology of this study, the Chi‐Square Automatic Interaction Detector or CHAID decision tree algorithm, one of the most efficient and up‐to‐date data mining method used for segmentation According to the results of the study, it was determined that financial performance of 9.15% (59 hospitals) of the covered hospitals was classified as “good” whereas 90.85% (586 hospitals) of them displayed as “bad” financial performance. Also hospitals were categorized in 12 different profiles in terms of level of financial performance by CHAID. These profiles show us what financial indicators of the hospitals should focus on for good financial performance as well as those profiles should take example to improve their financial performances. As a result of the findings, financial management policies, financial strategies and legal regulations were suggested to improve financial performance of the public hospitals and for the success of the Turkish health sector reform steps.

Details

Social Responsibility Journal, vol. 2 no. 3/4
Type: Research Article
ISSN: 1747-1117

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