Sampling Plan Research Articles

Designing two mixed quick switching sampling plans for linear profiles

AbstractThis study compares two proposed mixed quick switching sampling (QSS) plans for linear profiles as the quality characteristic. For the QSS plans, we recommend a binomial attribute plan for normal inspection and then a variable sampling plan for tightened inspection based on capability index CpuA of linear profiles with one‐sided specifications. The difference between the two proposed QSS plans is in the tightened inspection. Tightened inspection of the first proposed plan is a single sampling using CpuA index, but tightened inspection of the second plan is a multiple dependent state repetitive (MDSR) plan based on CpuA index. The optimal parameters are obtained by nonlinear optimization. Simulation study for selecting parameters is conducted with various combinations of specified acceptable quality level (AQL), limited quality level (LQL), producer's risk, and consumer's risk. Simulation results confirm that the second proposed QSS plan which applies variable MDSR at tightened inspection performs better than another proposed plan. Hence, the approach of the second proposed plan is demonstrated in an illustrative example.

Modeling Preharvest Cyclospora cayetanensis Sampling and Testing for Various Water and Produce Sampling Plans

As of August 2023, the two U.S. Food and Drug Administration (FDA) official detection methods for C. cayetanensis are outlined in the FDA Bacteriological Analytical Manual (BAM) Chapters 19b (produce testing) and 19c (agricultural water testing). These newly developed detection methods have been shown to not always detect contamination when present at low levels. Yet, industry and regulators may choose to use these methods as part of their monitoring and verification activities while detection methods continue to be improved. This study uses simulation to better understand the performance of these methods for various produce and water sampling plans. To do so, we used published FDA test validation data to fit a logistic regression model that predicts the methods’ detection rate given the number of oocysts present in a 10-L agricultural water or 25 g produce sample. By doing so, we were able to determine contamination thresholds at which different numbers of samples (n = 1, 2, 4, 8, 16, and 32) would be adequate for detecting contamination. Furthermore, to evaluate sampling plans in use cases, a simulation was developed to represent C. cayetanensis contamination in agricultural water and on cilantro throughout a 45-day growth cycle. The model included uncertainty around the contamination sources, including scenarios of unintentionally contaminated irrigation water or in-field contamination. The results demonstrate that in cases where irrigation water was the contamination source, frequent water testing proved to be more powerful than produce testing. In scenarios where contamination occurred in-field, conducting frequent produce testing or testing produce toward the end of the season more reliably detected contamination. This study models the power of C. cayetanensis detection methods to understand the sampling plan performance and how these methods can be better used to monitor this emerging food safety hazard.

Cost optimization of acceptance sampling plan in a fuzzy supply chain environment

PurposeThe purpose of the paper is set to minimize the total cost of a manufacturing system when an acceptance sampling plan (ASP) is carried out in a fuzzy environment.Design/methodology/approachA fuzzy acceptance sampling plan (FASP) is employed for the inspection of the batch of products and a fuzzy cost optimization problem is formulated.FindingsThe extent of uncertainty determines an interval for the total cost function with upper and lower bounds. The effect of variation in the ambiguity of the proportion of defectives in the probability of acceptance is determined.Practical implicationsThe proposed model is specifically designed for production and supply units with ASP for attributes. Still, the proportion of defectives in the inspection process is fuzzy.Originality/valueFuzzy probability distribution is used to model an optimal inspection plan for a general supply chain. Economic design of supply chain under fuzzy proportion of defectives is discussed for the first time.

Data-driven multi-stage sampling strategy for a three-dimensional geological domain using weighted centroidal voronoi tessellation and IC-XGBoost3D

Conventional site investigation schemes typically use an empirical sampling strategy, which involves equal sampling spacing with regular grid patterns. However, this approach assigns equal importance to the entire site and does not account for subsurface stratigraphic variations and site constraints. In this study, a data-driven multi-stage sampling strategy is proposed to adaptively optimize the borehole locations for a three-dimensional (3D) geotechnical site, considering the subsurface stratigraphic uncertainties and irregular site geometries. The initial sampling plan is determined based on weighted centroidal Voronoi tessellation, which assigns various sampling densities to zones depending on their importance. Measurements obtained in the previous sampling stage are combined with prior geological knowledge to establish and update a 3D geological domain using a physics-informed geological modelling method. The next optimal location for sampling is adaptively determined with the objective of maximizing the reduction in the stratigraphic uncertainty. The proposed method represents the first data-driven 3D site planning method that explicitly considers 3D subsurface stratigraphic variations. The performance of the proposed multi-stage sampling strategy is illustrated using a simulation study. The results indicate that the proposed method efficiently identifies the optimal sampling locations while comprehensively considering the 3D subsurface geological uncertainties and irregular site geometries.

Designing efficient Bayesian sampling plans for exponential distributions based on samples under a (n, t) simple step-stress test

This article studies a method about how to design an efficient Bayesian sampling plan based on samples collected through a (n, t)-sampling scheme with a simple step-stress accelerated life test (ALT). For brevity, such a step-stress accelerated life test is called (n, t)-SSALT. A Bayesian sampling plan (BSP) derived through the (n, t)-SSALT is called BSPA. First, we derive the BSPA with data collected through a (n, t)-SSALT for a general loss function. Given gamma and Jeffreys prior distributions, an explicit expression of the Bayes decision function under a certain loss function is derived. By applying a curtailment procedure to the preceding Bayes decision function, an on-line new Bayes decision function and Bayesian sampling plan, called an efficient Bayesian sampling plan (EBSPA), are constructed. It is shown that the Bayes risk of EBSPA is less than or equal to that of BSPA. This indicates that the EBSPA is more efficient than the BSPA. Comparisons among some BSPAs and the proposed EBSPA are given. The numerical results indicate that, in terms of Bayes risks, the EBSPA significantly outperforms the BSPA.

Designing of quality interval skip-lot sampling plan with multiple deferred state sampling plan

Designing of quality interval skip-lot sampling plan with multiple deferred state sampling plan

Listeria monocytogenes detection on food contact surfaces: suitability of different swab materials

The high binding capacity of Listeria monocytogenes to food contact surfaces increases the risk of cross-contamination in food. In addition to appropriate cleaning and disinfection procedures, a suitable sampling plan and technique for the earliest possible detection are necessary for prevention. This paper evaluates the sensitivity of 3 swab materials (cotton, viscose and nylon-flocked) for the qualitative and quantitative detection of L. monocytogenes on food contact surfaces (100 cm2). A L. monocytogenes cocktail of 3 serotypes (IIa, IIb and IVb) was applied to stainless steel, polyvinyl chloride, polytetrafluoroethylene and high-density polyethylene surfaces at a concentration of approx. 1.0 × 101-1.0 × 102 CFU/100 cm2 and approx. 4.0 × 104 CFU/100 cm2. The surfaces were sampled after 15 min of incubation by 3 different swabs using the double-swab technique, and then stored for 4 and 24 h until processing. The results of the qualitative and quantitative tests showed a few statistically significant differences in the detectability of L. monocytogenes by different swab materials, which implies that the detection rate of L. monocytogenes on a certain food contact surfaces can be increased by using the respective most suitable swab.

Repetitive sampling inspection plan for cancer patients using exponentiated half-logistic distribution under indeterminacy

This piece of work deals with a time truncated sampling scheme for cancer patients using exponentiated half-logistic distribution (EHLD) based on indeterminacy. We have studied time truncated schemes like repetitive acceptance sampling plan (RASP) under indeterminacy. We have estimated the projected scheme parameters such as sample size and acceptance and rejection sample numbers for known indeterminacy parameters. In addition to the projected sampling scheme quantities, the corresponding tables are generated for various values of indeterminacy parameters. The results of a sampling scheme show that the average sample number (ASN) decreases as indeterminacy values increase. It leads that the indeterminacy parameter is played a crucial portrayal in ASN. A comparative study is carried out with existing sampling schemes based on indeterminacy and classical sampling schemes. The evaluated sampling schemes are exemplified with the help of cancer data. From tables and exemplification, we wind up that the projected RSP scheme under indeterminacy desired a smaller sample size than the existing schemes.

Designing a variables two-plan sampling system with adjustable acceptance criteria for lot disposition

The variables acceptance sampling plan and variables acceptance sampling system (VASS) based on process capability indices (PCIs) have gotten greater attention recently because they can efficiently validate product quality in variables measurement scales. In the VASS, the variables quick-switch sampling system (VQSS) and variables tightened-normal-tightened sampling system (VTSS) are the basic two-plan sampling systems. Compared to the VQSS, the VTSS is more flexible and adaptive because it empowers practitioners to adjust the rule-switch mechanism. Recent studies on the PCI-based VTSS have only focused on the sample size type, denoted as VTSS-I. However, VTSS-I requires a large sample size in the tightened inspection, leading to increased inspection costs and delays in distribution. In this article, we proposed an acceptance criterion-type VTSS, denoted as VTSS-II, based on unilateral PCIs. By comparing the proposed VTSS-II with the existing VTSS-I, the VTSS-II can significantly reduce the inspected sample size and has superior discrimination power. Because the rule-switch mechanism of the VTSS-II is adjustable, we created a cloud-computing app to provide an easy way for practitioners to obtain the optimum system design.

Application of the multiple dependent state sampling strategy to late adolescent suicide rates

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.

Distribution and fixed-precision sampling plans for diamondback moth (Lepidoptera: Plutellidae), on winter-spring cabbage.

The diamondback moth (Plutella xylostella L.) is the most destructive insect pest on cabbage (Brassica oleracea var. capitata L.). Infestation by this pest usually results in the indiscriminate use of insecticides by farmers due to a lack of sampling plans for this pest. Sampling plans for P. xylostella management decisions on winter-spring cabbage in the Eastern Cape Province of South Africa were developed, through population monitoring that comprised weekly counts of immature stages of P. xylostella on 60 plants for 11 wk each during the winter and spring seasons. The mean density-variance relationship was used to describe the distribution of the pest, and number of infested plants was used to develop a fixed-precision sampling plan. All plant growth stages preceding maturation were vulnerable to P. xylostella damage resulting in yield losses. A high aggregation of P. xylostella on cabbage was observed in spring than in winter. The average sample number to estimate P. xylostella density within a 15% standard error of the mean was 35 plants. Furthermore, the estimated plant proportion action threshold (AT) was 51% with density action thresholds of 0.50 and 0.80 for spring and winter, respectively. Fitting P. xylostella cumulative counts in the winter and spring sampling plans resulted in 100% and 45% reduction in insecticide treatments. The similarity of sample size and ATs between both seasons provides evidence that a single sampling plan is practical for all cabbage growing seasons. The similarity of the estimated ATs to those acceptable in established integrated pest management programs indicates reliability.

Design of acceptance sampling plans based on interval valued neutrosophic sets

Design of acceptance sampling plans based on interval valued neutrosophic sets

An extended exponential model: Estimation using ranked set sampling with applications

In this paper, we emphasize a new three-parameter lifetime distribution. It can be presented as a tractable complementary exponentiated Bell exponential distribution defined as a paragon of the complementary exponentiated Bell-generated family of distributions. In the first part, some essential properties of the proposed distribution, such as the quantile function, the linear representation of the probability density function, and the moment measures, are presented. The second part is focused on the model's applications in diverse statistical scenarios. In the first scenario, two sampling schemes, namely ranked set sampling and simple random sampling, are used to estimate the unknown parameters. A simulation study is provided to assess the performance of the estimates using the two sampling schemes, and their relative efficiencies are computed. In the second scenario, a group acceptance sampling plan for truncated life tests is elaborated. Finally, real data sets are considered to illustrate the practical interest of the findings.

The Sustainable Benefits of Construction and the Perception of Cement Workers

Objective: The challenge of this work was to diagnose the sustainable benefits of civil construction and the perception of employees in a cement factory based on a new production methodology.
 
 Method: The study was carried out through quantitative and cross-sectional research, with the application of a questionnaire via Google forms for employees and customers of the factory under study.
 
 Results and conclusions: The sampling plan was 62.79% male, 58.14% married, 28.93% aged between 28 and 32 years old, 32% technical level, 11.63% post graduates and 22% of participants demonstrated understanding about sustainability. 77% of employees are unaware that the industry used a less aggressive production method for the environment, unique in Maranhão. We conclude that the industry under analysis has sought to implement good socio-environmental practices, but to achieve more expressive results, it needs to qualify and involve the entire production and consumption chain of the civil construction market with qualification programs, to guarantee the horizontalization of information with effective socio-environmental actions and thus preserving future generations.
 
 Research implications: The research highlights the perception of workers/collaborators in the cement industry on the consumption and sale of products that minimize the negative effects on the environment.
 
 Value of originality: This is original research that contributes to the understanding of the impact of the cement industry, during the production process, from the extraction of raw material. Since it degrades the environment by contaminating water and soil, it also interferes with human health, in addition to proposing the search to balance the negative socio-environmental impacts through cement production.

Eustrongylides spp. parasite risk management in Atherina boyeri from Lake Trasimeno.

Atherina boyeri is the primary source of fishing profit in Lake Trasimeno and a common host for Eustrongylides spp. larvae. The presence of Eustrongylides in fish is a public health concern, and effective risk management procedures are necessary to guarantee that infected products do not reach the market. Currently, in the European Union, there is no official sampling plan for fresh fish that defines sample size, inspection methods, and criteria for accepting or rejecting the product. An approach to Eustrongylides risk management is proposed in this study. A total of 270 batches of A. boyeri, each consisting of 29 specimens, were collected and examined visually in 3 years (2020-2023). The prevalence of the parasite was 20% in 2020, and in the first months of 2021, it grew up to ⁓40%, then dropped to 12.50% in December 2021 and settled at 16% in February 2022. In January and February 2023, the prevalence fell below 1%. The mean abundance was calculated and used to establish a threshold value to determine fish marketability. In 2020 and 2021, several batches were judged not marketable, and in some batches, a freezing treatment was implemented to ensure the inactivation of the parasite. In the last months of 2022 and in January and February of 2023, the presence of parasites in captured fish was negligible, and this allowed the marketability of fish as fresh. The proposed sampling plan was effective in preventing the commercialization of potentially hazardous products.

Applying the Bayesian Technique in Designing a Single Sampling Plan

The Bayesian sampling plans for production inspection are considered a technique of sampling inspection techniques for determining the characteristics of the sampling plan based on the assumption that the rate of defectives is a random variable that varies from one production batch to the next, resulting in a probability distribution f(p) that could be determined based on experience and the available quality information available. As part of this study, the parameters of a single Bayesian sampling plan (n,c) were derived by using the Beta-Binomial distribution and compared with those of other single sampling plans. Researchers have identified (ALA company for soft drinks), which handles product quality control. 120 production batches were selected, and the size of the batch and the number of defective items were used to determine the proportion of defective items, given that the variable varies randomly from one production batch to the next. Bayesian and decision-making models can be implemented to create a single sampling inspection process that is close to the actual quality level. The researchers discovered that when the decision-making model was used, the sample size was minimal compared to other inspection plans, leading to a low inspection cost.

Optimal design of a glider array for the observation of tropical cyclones

Underwater gliders have advantages for typhoon observation. In recent years, the typhoon-resistant operation mode and cluster networking capabilities of such platforms have improved greatly; therefore, underwater gliders have received increasing attention for typhoon observation, no matter observing the salinity, density, or temperature of the seawater during the typhoon. However, there is a lack of scientific evaluation of the sampling layout and planning of underwater gliders during tropical cyclones (TCs). Based on the simulation results of the three-dimensional Price–Weller–Pinkel numerical model (3DPWP) for Typhoon Hato, this study considers the working characteristics of underwater gliders to model the sampling results and for the first time proposes a method of evaluate the simulated typhoon observation effect of underwater gliders. Subsequently, four kinds of heading schemes for an underwater glider array are designed and evaluated, and the optimal design of a glider array for typhoon observation, that is, the “along-typhoon parallel” mode, is identified through comparison. Finally, the optimal design employing a genetic algorithm is applied to Typhoon Hato to verify its universality and effectiveness. Underwater gliders with the best typhoon observation scheme are helpful to more completely observing and reconstructing the 3D structure of the tropical-cyclone-induced ocean response with greater precision.

Pedagogy of learning: a praxis of industrial safety

This research analyzes the teaching-learning process of the industrial safety training of the Basic Platform Safety Course, developed by the training company Sampling Planning and Industrial Safety Advisory. The course is compulsory for offshore activities in the oil and gas industry in Brazil. When dealing with safety at sea, it is important to start from the premise that navigation imposes an associated danger, derived from the fact that it develops in an environment not conducive to human life, therefore, this theme is of extreme importance. The objective of the research is to evaluate how the learning pedagogy is related to the safety praxis in the offshore work environment. The type of research was based on a case study developed through observation and on-site interview questionnaires. As a data collection instrument, we used document analysis from theoretical tests, practical exercise sheets, grade maps, frequency controls and evaluation questionnaire, provided from the institution. Consolidated data demonstrate that the selected target audience knows and applies industrial safety standards and that the concepts acquired during the course are important in preventing accident risks. It is concluded that education is characterized by being an instrument of theoretical-practical association through information that can intervene in the reality and promote changes in everyday attitudes, leading to new practices for the construction of citizenship.

An Intersectional Examination of Economic Hardship and Individualized Education Program Meeting Participation

In this preregistered study, we confirmed a transition-planning construct and determined its relationship with an established economic-hardship construct using parent- and youth-reported data from the National Longitudinal Transition Study 2012 and following established quality indicators of preregistered secondary data analyses studies. Transition planning was made up of seven items relevant to individualized education program (IEP) meeting participation. We examined measurement invariance on the basis of disability category and race/ethnicity as well as the intersection of these student characteristics in order to make unbiased group comparisons on key latent parameters. Contrary to our hypotheses, there was no meaningful correlation between transition planning and economic hardship. Moreover, we were unable to establish measurement invariance of transition planning because the item “youth's role in IEP meeting” functioned differently on the basis of disability category. Implications for practice are discussed regarding how decisions about IEP meeting participation are made, by whom and why, and whether evidence-based practices are effectively disseminated. Future research should ensure adequate sampling plans for national survey attempts in order to conduct an in-depth examination based on intersectional student characteristics.

The design of the mixed repetitive sampling plans based on the Cpk index

PurposeThis 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.Design/methodology/approachThe 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.FindingsThe 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.Originality/valueIn 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.