Acceptance Sampling Research Articles

Correction: Modified acceptance sampling for statistical quality control

Correction: Modified acceptance sampling for statistical quality control

Integrating order statistics in reliability acceptance sampling plans for a compound distribution: a case study

Integrating order statistics in reliability acceptance sampling plans for a compound distribution: a case study

Optimizing Group Size using Percentile Based Group Acceptance Sampling Plans with Application

The present paper focuses on optimizing the sample size and the acceptance number which are commonly known as design parameters for the group acceptance sampling plan (GASP). Design parameters are analyzed under the assumption that the characteristic of interest for the product follows Another Generalized Transmuted-Exponential (AGTransmuted-Exponential) distribution. Using different values of the quality levels (median lifetime), the values of the Operating Characteristic function is determined. The proposed plan satisfies two types of risks based on producer's point of view and consumer’s point of view at varied stipulated quality levels. Optimization of the sample size, group size and acceptance numbers is obtained through Monte Carlo simulation, for which relevant R codes were developed. Specific R codes are appended for future usage by academia and practitioners from various fields of life. The simulated results of the study are exhibited in the form of tables and explained with relevant examples. Results of the proposed GASP are compared with plan parameters obtained using MLE estimates of AGTransmuted-Exponential distribution and also by design parameters obtained using mean as quality level. Results of the study exhibited that Median as a quality parameter resulted in the decrease of group size and acceptance number simultaneously at all quality levels. Easy to follow the methodology of the current paper will open new vistas for applying the proposed GASP to a family of transmuted probability distributions. For illustration purposes, a real data set for fatigue fracture stress is analyzed using MLE estimates of AGTransmuted-Exponential distribution to demonstrate the implementation of the proposed sampling plan.

NanoMIP beacons with a co-operative binding mechanism for the all-in-one detection of methamphetamine aptamer complexes

Methamphetamine is a highly addictive stimulant with significant public health implications, necessitating the development of rapid, sensitive, and reliable detection methods. Traditional analytical techniques, though accurate, often involve complex sample preparation, expensive equipment, and lengthy analysis times. This study presents the design, synthesis, and application of nanoMIP beacons with a unique co-operative binding mechanism for the detection of methamphetamine. NanoMIP beacons selective for methamphetamine/aptamer complexes were synthesized using a solid-phase synthesis method that involved the bio-conjugation of an aptamer on the stationary phase and the incubation of methamphetamine to form a methamphetamine-aptamer complex. The resultant nanoMIP beacons were eluted off the affinity column and characterised using transmission electron microscopy. The co-operative binding mechanism, which relies on the structure-switching capability of the aptamer upon analyte binding was demonstrated through comparison of the fluorescence quenching signal of a scrambled sequence and nanoNIP controls. The fluorescence quenching assay was established using a fixed optimal concentration of aptamer and varying amounts of methamphetamine. The nanoMIP beacons showed enhanced the sensitivity (LOD = 23 ± 3.5 nM) and excellent selectivity, with a 40-fold increase in quenching for methamphetamine compared to other illicit drugs. The nanoMIP beacons demonstrated acceptable sample recoveries in both urine diluent and 50% human serum. This work provides a new strategy for the development of hybrid nanoMIP/aptamer-based sensors and provides a robust analytical tool for combating methamphetamine abuse.

Performance evaluation study of reliability acceptance sampling plans based on compound exponential-geometric distribution

Performance evaluation study of reliability acceptance sampling plans based on compound exponential-geometric distribution

A-108 Re-evaluation of reference intervals for circulating albumin, total calcium, and magnesium levels among subjects in Dallas County

Abstract Background Reference intervals are either directly established from normal volunteers, adopted from assay manufactures and verified as transferable to the normal population, or indirectly derived using patients’ archived laboratory data. This study describes indirect derivation of reference intervals for albumin, total calcium, and magnesium appropriate to the patient population of Dallas County. The tests were selected due to their often combine measurement in the assessment of calcium and bone mineral metabolism Methods Retrospective reported laboratory results during May 2022 for albumin (n=1342), total calcium (n=1945), and magnesium (n=2148) were obtained. Values were subjected to statistical analysis for nature of distribution, mean, and standard deviation as well as stratified for patients’ characteristics (gender, race, and age). Statistical analysis applied were Hoffman regression analysis, one-way ANOVA, and Tukey-Kramer tests. Results Following removal of outliers, statistically suggested reference intervals for albumin, total calcium, and magnesium were 5.5 to 2.4 g/dL, 10.5 to 7.5 mg/dL, and 2.6 to 1.6 mg/dL respectively. Although there was race specific differences in albumin and calcium levels (p=0.032) and (p=0.002) respectively, differences for magnesium were slightly nonsignificant (p=0.06). Similarly, significant differences due to age were observed for albumin, total calcium, and magnesium (P <0.00 for all). The data suggests that albumin, magnesium, and calcium levels are unequivocally dependent on age and race for patients in Dallas County. The upper limits of population derived, and manufacturer verified reference intervals were 5.45 and 5.2 g/dL for albumin, 10.5 and 10.2 mg/dL for calcium, and 4.6, and 2.6 mg/dL for magnesium respectively, the lower limits were 2.4 and 3.5, 7.5 and 8.4, 1.4, and 1.6 mg/dL respectively. Conclusions Reference intervals for albumin, total calcium, and magnesium appropriate to the patient population of Dallas County were derived. Derived values were statistically different from the manufacturer verified values in use. The study although limited by the small number of acceptable samples, highlights the need for laboratories to derive their respective population-based reference intervals. The study will be expanded to other biochemical parameters utilizing much larger sample volume.

Enhancing infection control in dialysis at a resource limited public healthcare institute: A cross-sectional study on microbiological quality assessment of dialysis water and dialysate

PurposeTo evaluate the microbiological quality of dialysis water and dialysate samples from hemodialysis units at a tertiary care government hospital and to assess the use of culture, endotoxin and periodicity of testing these assays to guide the actions of monitoring the quality of hemodialysis fluids, implement preventive and corrective actions, and improve the safety and outcomes of the dialysis process. MethodsA cross-sectional study was conducted at a 250-bedded super-specialty government hospital with a 24/7 hemodialysis unit equipped with 40 dialysis machines. Dialysis water and dialysate samples were collected monthly and analysed for microbial contamination and endotoxin levels as per AAMI guidelines. Bacterial cultures were done using Reasoner's Agar plates, and endotoxin analysis was performed using gel clot assay. Interpretation of results was based on predefined thresholds. ResultsAmong the 740 samples processed for microbial culture 19.6 % and 80.4% were unacceptable and acceptable respectively.Among the acceptable samples 10.5 % were at action level. At the end of 2 days of incubation, 15.2%dialysis water samples and 5.1%dialysate samples had unacceptable levels of bacterial colonies and at 5days additional 10.6 % dialysis water samples and 7.7%dialysate samples were unacceptable. 21.5 % of the samples tested for endotoxin had unacceptable levels. ConclusionsRegular monitoring of water quality in government healthcare hemodialysis units is crucial for quality of care, timely preventive and corrective actions for mitigating adverse outcomes. Processing cultures for 5–7 days is essential for detecting all contaminated specimens. While there might be a link between endotoxin levels and bacterial contamination, both endotoxin testing and bacterial culture independently are vital for evaluating water quality in dialysis settings. A comprehensive approach integrating various testing methods is necessary to uphold patient safety and enable necessary improvements.

Group acceptance sampling plan based on truncated life tests for Type-I heavy-tailed Rayleigh distribution

This study on the Type-I heavy-tailed Rayleigh (TI-HTR) distribution is a special case of Type-I heavy-tailed (TI-HT) family of distributions was studied. The characteristics were derived, including the moment and its measures, quantile function, reliability measures, and other statistical properties as well as parameter estimation using the maximum likelihood method and penalized likelihood estimation. The behavior of its various functions were shown graphically. Analytically, we showed that model linearly grows near the origin and exhibits rapid exponential decay. However, the tail behavior cannot equal the traditional heavy-tail in the power law sense, hence it is called the type-I heavy-tail. Interestingly, we designed a group acceptance plan (GASP) and demonstrated usefulness with both assumed and maximum likelihood estimates. The GASP under the TI-HTR distribution is preferable when the parameter values are small. The distribution was used to model real-life data sets to justify its usefulness. The results of the application of the model to both COVID-19 and Cancer data showed that the model fits the two data better than the competing models and also suggest that inference from the model is better than those of the competitors. In estimating the parameters, the penalized likelihood procedure perform considerably better with minimum standard error of the estimates. From the Cramér-von Mises test results which guides against the heavy-tail sensitivity, the TI-HTR distribution offers a better model for fitting fast decaying exponential data since it has the least statistics in both datasets.

Enhancing quality in Lot reception: A comparative analysis of innovative attribute acceptance sampling plans

Purpose: This study aims to enhance production quality by applying Quality Control (QC) principles through acceptance sampling, specifically analyzing the efficacy of attribute acceptance sampling plans in final lot receptions.Design/methodology/approach: Through a comprehensive review and critical evaluation of various sampling methodologies found in literature, this paper assesses their efficiency under distinct administrative and operational conditions. It emphasizes the comparison of different attribute acceptance sampling plans by examining variations in parameters and key performance indicators, such as Average Outgoing Quality (AOQ) and inspection time allocation percentage. Furthermore, it proposes a model for Continuous Sampling Plans (CSP) to evaluate these plans' performance in response to operational characteristic variations.Findings: The analysis reveals that the selected methodologies significantly aid in decision-making processes for lot acceptance, utilizing non-conforming rates depicted by the Average Quality Level (AQL). This provides a robust framework for improving Quality Control strategies, demonstrating the potential of these methodologies to optimize production quality through strategic lot acceptance.Practical implications: This paper outlines a practical approach for industry practitioners to enhance decision-making in lot acceptance, offering a method to balance quality control with operational efficiency effectively.Originality/value: By comparing a wide range of attribute acceptance sampling plans and introducing a novel CSP model, this research contributes valuable insights into the optimization of QC strategies. It offers a unique perspective on enhancing production quality, marking a significant advancement in the field of Quality Control and management.

Optimal variable acceptance sampling plan for exponential distribution using Bayesian estimate under Type-I hybrid censoring

Acceptance sampling plans with censoring schemes are crucial for improving quality control by efficiently managing incomplete information. This approach improves cost and time effectiveness compared to traditional methods, providing a more accurate assessment of product quality. In this study, a variable acceptance sampling plan under Type-I hybrid censoring is designed for a lot of independent and identical units with exponential lifetimes using Bayesian estimation of the mean life. This novel approach diverges from conventional methods in acceptance sampling plans, which rely on maximum likelihood estimation and the minimization of Bayes risk. Bayesian estimation is obtained using both squared error loss and Linex loss functions. Under each method, a nonlinear optimization problem is solved to minimize the testing cost, and the optimal values of the plan parameters are determined. The proposed plans are illustrated using various numerical examples, with each plan presented in tables. The acceptance sampling plan using the squared error loss function proves to be more cost-effective than the plan using the Linex loss function. A comparative analysis of the proposed plans with existing work in the literature demonstrates that our cost is much lower than the cost of existing plans using maximum likelihood estimation. Additionally, a real-life case study is conducted to validate the approach.

A matrix-separation-based integral inequality for aperiodic sampled-data synchronization of delayed neural networks considering communication delay

This paper achieves the synchronization of delayed neural networks (DNNs) considering aperiodic sampled-data control and communication delay. First of all, based on the master-slave DNNs with aperiodic sampling synchronization controller, a synchronization error system is constructed. Then, an augmented functional containing both the error state and its derivative is constructed. Compared with the existing researches, the augmented functional introduces more cross information of error states to the criterion. Next, an integral inequality based on the separation of internal integral variable and matrix is developed. Compared to the inequalities that treat the internal variable and the matrix as unified ones, the developed inequality provides a tighter estimate of the derivative of the augmented functional. On this basis, a criterion with less conservative is developed for the aperiodic sampled-data synchronization of DNNs considering communication delay. Finally, to indicate the superiority of the developed method on improving the acceptable sampling upper bound of synchronization, three numerical examples are provided.

Two-stage group reliability acceptance sampling plan for Lindley distribution

Two-stage group reliability acceptance sampling plan for Lindley distribution

Acceptance sampling plans based on percentiles for extended generalized exponential distribution with real data application

In this paper, when the life test is truncated at a pre-determined time, new acceptance sampling plans (ASP) are developed based on percentile lifetime as a quality parameter for the extended generalized exponential distribution (EGED). An inspection of a representative sample of goods or materials from a big lot or batch is used in quality control testing under acceptance sampling plans to assess whether the lot satisfies predetermined quality requirements. For the suggested new acceptance sampling plans, the minimum sample sizes needed to emphasize the determined lifetime percentile are obtained for a given customer's risk. The sample plans' operating characteristic function values and the producer's risk are built at various quality levels for some distribution parameters. Some numerical examples are presented to show how the suggested ASP can be used. A genuine industrial data set from a top Korean automobile is fitted to the EGED relative to other competitors and the applicability of the suggested ASP is illustrated. It is found that the suggested ASP for the EGED can be applied by the researchers in production engineering fields.

A Bayesian approach with double group sampling plan to estimate quality regions for proportion of nonconforming products in industry based on beta prior

To succeed in the global market, firms must prioritize quality over individual goals and preferences. One of the two primary approaches for ensuring quality is acceptance sampling, which is employed in statistical process control to inspect attributes of the product for acceptance. In acceptance sampling, the lot is either accepted or not-accepted based on predetermined acceptance criteria for inspection. This paper presents a proposed Bayesian double group sampling plan (BDGSP) for estimating quality regions. The binomial distribution is used to construct the likelihood function for both nonconforming and conforming products based on acceptance criteria. To calculate the average probability of acceptance, the beta distribution is used as a suitable prior distribution of the binomial distribution. Four distinct quality regions are predicted for various indicated producer’s and consumer’s risk levels. Based on various combinations of values for design parameters, the suggested plan generates variation point values. Risks for producers and consumers are related to acceptable quality level and limiting quality level. To track the effects of changes in the values of the specified parameters, operating characteristic curves are utilized. The applicability of the proposed plan for current industrial strategies is demonstrated using a real dataset.

Developing variables two-plan sampling scheme with consideration of process loss for lot sentencing

This paper considers a well-known two-plan sampling system, Tightened-Normal-Tightened (TNT) sampling scheme, which includes two single sampling plans (SSPs) with regulations for transitioning between tightened and normal inspections. Tightened inspection is conducted when there is a noticeable decline in quality, and normal inspection is employed when the quality is satisfactory. Most acceptance sampling plans evaluate product quality in terms of process yield, which does not differentiate between products that fall within specification limits. To address this issue, a new performance measure called the process loss index Le was developed, which accounts for the quality loss function. This index is determined by dividing the “expected quadratic loss” by the “square of half the specification width.” Using this index, two primary types of variables TNT sampling scheme were constructed and evaluated in this study. Their efficacy and features were investigated, discussed, and compared. The findings reveal that the TNT sampling strategy delivers the required quality assurance with a reduced sample size compared to the conventional SSP.

Development of whey protein beverage incorporating encapsulated probiotic strain Lactiplantibacillus rhamnosus NCDC 347 and its physico-chemical characteristics.

In the present study, encapsulated strain Lactiplantibacillus rhamnosus NCDC 347 was used to prepare a novel whey protein-based beverage. The encapsulation process utilized skimmed milk powder matrix and evaluated strain viability, physico-chemical properties, sensory assessment, and shelf-life stability. Encapsulated L.rhamnosus NCDC 347 within skim milk powder maintained viability at 8.0 log CFU/g, forming spherical microcapsules with 1-12 µm concavities. Probiotic addition to whey protein beverages maintained pH and acidity within desired ranges. Physico-chemical analysis showed protein content of 8.71±0.21 % to 10.05±0.42 %, fat content of 0.56±0.24 % to 0.67±0.13 %, viscosity of 5.14 pa/s, and total soluble solids (TSS) of 14.42±0.31 to 16.16±0.23° Brix. The shelf-life study revealed that the beverage remained stable for up to 90days with no significant changes (p>0.05) in sensory analysis. The sensory analysis scored the test sample's acceptability at 7.3±0.41. The protein-rich probiotic drink exhibited favorable sensory qualities. Overall, incorporating encapsulated probiotic strain L.rhamnosus NCDC 347 into whey protein beverages could address daily protein requirements and enhance health.

Statistical Inferences about Parameters of the Pseudo Lindley Distribution with Acceptance Sampling Plans

Different non-Bayesian and Bayesian techniques were used to estimate the pseudo-Lindley (PsL) distribution’s parameters in this study. To derive Bayesian estimators, one must assume appropriate priors on the parameters and use loss functions such as squared error (SE), general entropy (GE), and linear-exponential (LINEX). Since no closed-form solutions are accessible for Bayes estimates under these loss functions, the Markov Chain Monte Carlo (MCMC) approach was used. Simulation studies were conducted to evaluate the estimators’ performance under the given loss functions. Furthermore, we exhibited the adaptability and practicality of the PsL distribution through real-world data applications, which is essential for evaluating the various estimation techniques. Also, the acceptance sampling plans were developed in this work for items whose lifespans approximate the PsL distribution.

Time Truncated Attribute Median Control Charts for Logistic-Exponential Process Distribution

Abstract In this article, time truncated attribute control chart is proposed for logistic-exponential distribution based on four acceptance sampling plans. The performance of the proposed control chart is evaluated in terms of average run length. Furthermore, the efficiency of the proposed attribute control chart is compared for all given acceptance sampling plans, viz., single sampling plan, repetitive sampling plan, multiple dependent state sampling plan and multiple dependent state repetitive sampling plan. Also, the application of the proposed control chart is illustrated by using real life example.

Audit Delay Phenomenon in Companies Listed on the Indonesia Stock Exchange

This study was conducted to examine the effect of financial distress, company size and audit committee on audit delay. This study uses companies that are delayed in submitting audited financial statements listed on the Indonesia Stock Exchange for the 2019-2021 period using the purposive sampling method. The selection of samples from 205 companies listed on the Indonesia Stock Exchange in 2019-2021 resulted in 116 acceptable samples. The data analysis method used in the study was Multiple Linear Regression Analysis with Eviews 12 with a significance level of 5%. The results of this study show that: (1) Financial distress does not affect audit delay, (2) Company size has a significant and positive effect on audit delay, (3) Audit committee does not affect audit delay.

Designing acceptance sampling plans for polynomial profiles using EWMA statistics based on process yield index

Inspection of raw materials, semi-finished products or final products is an important part of a quality assurance system. Acceptance sampling is a procedure used to decide either to accept or reject suppliers’ submitted lots in accordance with a specific standard. In this manuscript, designing acceptance sampling plans for lots with polynomial profile as quality characteristic is considered. To use previous lot information on deciding for accept or reject the available lot, exponentially weighted moving average (EWMA) statistic based on process yield index (Spk ) of polynomial profiles with two-sided specification limits is applied. For this purpose, three acceptance sampling plans of repetitive group sampling (RGS), resubmitted and also combined RGS-resubmitted plans are developed in this paper. The Parameters of the proposed plans are determined using non-linear optimization model. Performance of the proposed acceptance sampling plans are compared using numerical methods and Monte-Carlo simulations. Simulation results emphasize that the proposed combined sampling plan mostly requires less average sampling number (ASN) and consequently leads to decreasing inspection time and costs. The application of the proposed combined plan is also demonstrated using a real case.