An attribute control chart is designed for the time truncated life test when the quality characteristic follows the new Lomax Rayleigh Distribution (NLRD). Control chart coefficients and performance of the proposed control chart are determined for different shift constants. Average run lengths for different shift constants and control chart limits are tabulated for reference. Time truncated attribute control charts performance in monitoring non-conforming units following NLRD distribution is validated in this study. Simulated data results and real data example reveals that the new proposed attribute control chart for NLRD shows better results in identifying even small shifts.

Objectives: To prepare the percentile-based acceptance sampling plans for the Exponentiated Inverse Kumaraswamy Distribution (EIKD) at a specific truncation time to inspect the defective lots corresponding to the desired acceptance level. Methods: The failure probability value is estimated using the cumulative probability function F(.) at time ‘t’ which is converted in terms of the scale parameter σ as 100th percentile using quantile function. The minimum size of the sample, Operating Characteristic (OC) and the minimum ratios are calculated for a required levels of consumer’s as well as producer’s risk. Findings: The percentile-based sampling plans are obtained through the minimal size of the sample ‘n’ under a truncated life test with a target acceptance number c in a manner that the proportion of accepting a lot which is not good (consumer’s risk) would not be more than . These values are calculated at The function of probability of acceptance for variations in the quality of a lot (OC function) L(p) of the sample plan are evaluated for the acceptance values of c=1 and c=5. The minimum ratio values are calculated for the acceptability of the lot with producers’ risk of using the sampling plan. Novelty: The modernity of this study is the designing of the acceptance sampling plans to a non-normal data using an asymmetrical distribution that has all three shape parameters. Also, the monitor of the implementation and suitability of statistical quality control and process control aspects using Exponentiated Inverse Kumaraswamy Distribution when compared to other asymmetrical distributions which has at least one scale parameter. Keywords: Sampling plans, Consumer's risk, Operating characteristics function, Truncated life tests, Producer's risk

In the textile and packing industries, the lifetime of the items is exhibited by some statistical distribution. This paper aims to develop a multiple dependent state repetitive (MDSR) sampling plan by assuming that the lifetime of an item comes from an exponentiated half logistic distribution (EHLD). The MDSR sampling plan will be more economical than the other sampling plans on hand such as the multiple dependent state sampling schemes, the repetitive sampling plan, the single sampling plan, and the resubmitted sampling plan concerning the size of the sample required to test the lot. The design parameters for the developed sampling plans are obtained by minimizing the average sample number when both the consumer's and producer's risks are satisfied at corresponding quality levels. Tables are given for practical use. The proposed MDSR sampling plan is compared with the single sampling plan and some examples are also provided.

A multiple dependent state sampling plan (MDSSP) is designed when the lifetimes of the variables follow New Lomax Rayleigh Distribution (NLRD). The decision to accept or reject a lot in the proposed methodology is based on the quality of the given present or previous lots. A binomial model-based operating characteristic curve (OC curve) for continuous lots of variables under similar settings in healthcare is used in finding the probability of acceptance, acceptance number, rejection number, and the number of preceding (succeeding) lots to consider. Time truncated life test based on the specified median of the NLRD is used in designing the current acceptance sampling plan. For specified values of the parameters of NLRD, quantile ratios, consumer’s risk and producer’s risk, average sampling number (ASN) and probability of acceptance of a lot are reported in tables. Real data on worldwide suicide rates of 15–19 years in the year 2019 from the World Health Organization (WHO) website is considered to illustrate this methodology. The minimum sample size required from the selected data to comment on worldwide suicide rates in late adolescents is explained with MDSSP. The results of the proposed acceptance sampling method are compared with the single-stage sampling plan.

A new Lomax Rayleigh distribution (NLRD) is proposed and generated using Transformed Transformer (T-X) family generator. Various structural properties like generating functions, moments, limiting form, quantile function median and mode of NLRD are studied. Maximum likelihood estimators (MLEs) of the parameters are obtained and the model fitting is tested with simulated data. Model adequacy with live data is explained with two real-time cancer data sets. The NLRD shows a better fit in the estimation of survival in bile duct cancer and head and neck cancer data than other existing distributions.

In this manuscript, we developed resubmitted lots with group acceptance sampling plan for the lifetime of the product follows the odd generalized exponential log logistic distribution introduced by Rosaiah et al. (2016c). The values of the design parameters of the proposed plan are obtained which are satisfying the both producer’s as well consumer’s risk by fixing the experiment termination time. An application of the proposed plan to the industry is presented and the Kolmogorov-Smirnov test was conducted. However, this plan provides reasonable fit for lifetime of items of ball bearings data. Finally, the advantage of the proposed plan reduces the sample size as compared with the ordinary group sampling scheme. An example is given to illustrate the methodology.

According to the results of industrial research, product failure time is correlated with fatigue weakness, which is typically produced by repeated stress variations. A double acceptance sampling strategy was presented for shortened life tests where the lifespan of test products follows an odd generalized exponential log-logistic distribution (OGELLD), according to the findings of this study. The minimum sample sizes for the first and second samples are calculated using a producer’s risk of 0.05 to ensure that the actual median life is greater than the specified life at the chosen consumer confidence level. Based on various ratios of genuine median life to stipulated life, we analyzed operational features; we observed that reduced producer risk at the defined level was associated with the lowest median ratios to the specified level. Finally, an illustration is offered to help in the grasp of the suggested framework.

In this article, a lifetime distribution named as Type-II generalized log-logistic distribution (TGLLD) is considered and its failure rate of products with different shape parameters used to find out ageing criteria. An attempt has been made to derive the statistical and reliability properties of TGLLD. Parameters are evaluated using maximum likelihood estimation and obtained the reliability of the distribution. A simulation study also conducted to know the performance of the estimators. The estimates obtained are validated with the use of live data.

In this paper, an attribute control chart is aimed when the lifetime of the item follows Type-II generalized log-logistic distribution (TGLLD) under a time truncated life test assuming that the common scale parameter is known. Average run length (ARL) is used to assess the performance of the aimed control chart. Simulation technique is developed to present the performance of the control charts at a specified average run length (ARL), shift constant and for different parametric values of shape and scale parameters, sample size. The results are illustrated with live data example.

We suppose that a product’s lifetime follow the exponentiated Fréchet distribution of defined shape parameters. Based on this assumption, a double-acceptance sampling plan is constructed. The zero and one failure framework is essentially thought of: if no errors are found from the first sample, then the lot is approved; also, if at least two failures occur, it is rejected. In the first sample, if one failure is observed, then the second sample is taken and decided for the same length as the first one. The cumulative sample sizes of the first and second samples are determined on the basis of the stated confidence level of the consumer to ensure that the actual median is longer than the given life. As indicated by the various ratios of the actual median life to specified median lifetime, the operating characteristics are calculated and placed in presented tables. To decrease the risk of the producer at the predefined level, the minimum ratios of this sort are additionally obtained. Lastly, examples are provided for representation reasons for the proposed model.

In this paper, we consider the New Rayleigh-Pareto distribution as a life time model. Based on the evaluated percentiles of sample estimates like sample mean, median, midrange, range and standard deviation, the control limits for the respective control charts are developed. The admissibility and power of the control limits are assessed in comparison with those on the popular Shewhart control limits.

Background: The millennium development goals encourage governments to address and reduce various developmental issues, two of the important ones being maternal and child health. The one of the important causes of maternal mortality in India is pregnancy induced hypertension (PIH) and present study is to identify the relationship between disturbed lipid profile and preeclampsia its effect on fetal and maternal outcome.Methods: This was a descriptive cross-sectional study done on data of maternal care and outcomes from the NRI General Hospital, Guntur district in the year 2013. Multiple logistic regression analysis is applied and results are adjusted to covariates maternal age and gravida.Results: Systolic blood pressure, diastolic blood pressure of normal group (n=50) and PIH group (n=60) are 116.08±7.77, 76.08±4.93, and 165.66±16.8 105.5±14.07 respectively. Birth weights of infants in normotensives and PIH group are 2.85±0.33 and 1.93±0.659 respectively. Percentages of fetal and maternal complications in PIH group are 88.33% and 25%. Still births are present in 31.66% of PIH cases. Mean and SD of gestational age in weeks in normal and PIH groups are 37.92±1.94 and 34.36±3.44 respectively.Conclusions: The model showed significant association between the selected independent variable, covariates and outcomes. The study demonstrates that multiple logistic regression may be applied to medical data in developing predictor models which are useful in clinical settings.

Odd generalized exponential log-logistic distribution introduced and studied quite extensively by Rosaiah et al. (2016) is considered as a probability model for the lifetime of products. In this article, the sampling plans are developed for percentile lifetimes using two approaches. In approach–I, minimum sample size necessary to ensure a specified percentile lifetime is determined based on the termination time and acceptance number along with operating characteristic values and producer’s risk. In approach-II, by fixing the number of failures, we determine the life test termination time along with operating characteristic values. The sampling plans constructed using two approaches are compared with respect to life test termination time.

The exponentiated half logistic distribution introduced by Cordeiro et al. (2014) is a probability model for the life time of an item. A submitted lot will be accepted or rejected based on the sampling plans where items are to be tested and for collecting the life of items, these plans are called reliability test plans. The present reliability test plan is more desirable than similar plans exists in literature is entrenched with respect to termination time of the experiment. For a range of stated acceptance number we determine the minimum life test termination time, sample size, and producer’s risk.

This paper aims to develop a multiple deferred state sampling plan for a time-truncated life test if the lifetime of the item follows exponentiated half logistic distribution. The optimal parameters of the proposed plan, such as the number of successive lots required for making the decision whether to accept or reject the current lot, sample size, the rejection and acceptance numbers are obtained using two points approach. The implementation of the proposed plan is illustrated with examples. Tables are constructed for various combinations of consumer’s and producer’s risks. Comparison is also made with existing sampling plans under exponentiated half logistic distribution.

This paper deals with construction of confidence intervals for process capability index using bootstrap method (proposed by Chen and Pearn in Qual Reliab Eng Int 13(6):355–360, 1997) by applying simulation technique. It is assumed that the quality characteristic follows type-II generalized log-logistic distribution introduced by Rosaiah et al. in Int J Agric Stat Sci 4(2):283–292, (2008). Discussed different bootstrap confidence intervals for process capability index. Maximum likelihood method is considered for obtaining the estimators of the parameter. Monte Carlo simulation technique is applied to find out the coverage probabilities and average widths of the bootstrap confidence intervals. The results are illustrated with real data sets.

This article describes the development of an acceptance sampling plan based on percentiles for Type-II generalized log-logistic distribution (TGLLD) introduced by Rosaiah et. al. [1]. The plan is developed by considering the lifetime percentiles as a variable and the life test will be terminated at a pre-specified time. The objective of the test is to determine the minimum sample size required to achieve a specific lifetime percentile at an acceptable level of consumer and producer risks. Determined the OC values and are presented along with producer risks. The sustainability of the plan is illustrated with real data set.

In quality control, we used to develop different types of sampling plans to ensure the quality of product lifetime. In this paper, we develop a group acceptance sampling plan (GASP) for lot resubmitting, to ensure the quality of product lifetime assuming that the product lifetime follows the exponentiated Fréchet distribution. The GASP parameters are determined by satisfying the specified producer's and consumer's risks according to the experiment termination time and the number of testers. We compare the proposed plan with the ordinary group sampling plan and found that the proposed plan requires less sample size. Two examples are used for illustration.