Certain observations on lot sensitive sampling plan

This paper compares the sample size efficiency of the lot sensitive plan over the equivalent double and multiple sampling plans. It is shown that a fully curtailed lot sensitive plan will involve smaller average sample number than the equivalent double and multiple plans.     

Tightened single-level continuous sampling plan

In this paper, a new tightening concept has been incorporated into the single-level continuous sampling plan CSP-1, such that quality degradation will warrant sampling inspection to cease beyond a certain number of sampled items, until new evidence of good quality is established. The expressions of the performance measures for this new plan, such as the operating characteristic, average outgoing quality and average fraction inspected, are derived using a Markov chain model. The advantage of the tightened CSP-1 plan is that it is possible to lower the average outgoing quality limit.     

Repetitive variable acceptance sampling plan for one-sided specification

In this paper, a variable repetitive group sampling plans based on one-sided process capability indices is proposed to deal with lot sentencing for one-sided specifications. The parameters of the proposed plans are tabulated for some combinations of acceptance quality levels with commonly used producer's risk and consumer's risk. The efficiency of the proposed plan is compared with the Pearn and Wu [Critical acceptance values and sample sizes of a variables sampling plan for very low fraction of defectives. Omega – Int J Manag Sci. 2006;34(1):90–101] plan in terms of sample size and the power curve. One example is given to illustrate the proposed methodology.     

A continuous sampling plan using CUSUMs

A Continuous Sampling Plan, CSP-CUSUM, is proposed based on the use of Cumulative Sums (CUSUMs) for deciding when to switch between the phases of sampling inspection and 100% inspection. The Geometric CUSUM, also termed the Run-length CUSUM, is chosen for this purpose, and two separate CUSUMs are to be operated, one for each inspection phase. The conventional measures of performance for CSPs such as average outgoing quality, average fraction inspected, and average proportion passed under sampling inspection are evaluated for CSP-CUSUM, and comparisons with some standard CSPs are presented. An additional performance-measure, Average Cycle Length, is proposed. A table is provided to aid the choice of parameters for the operation of CSP-CUSUM. It is recommended that a Geometric CUSUM control chart be maintained in parallel with CSP-CUSUM to detect significant upward shifts in the incoming fraction defective.     

A bayesian life test acceptance sampling plan by variables with cost considerations

This paper presents an economic life test acceptance sampling plan using item-censored data in a Bayesian situation. It is assumed that failures in a life test are replaced immediately by new ones. A prior distribution is assigned to the mean lifetime θ for the calculation of the expected total cost. Then the optimum plan is chosen to be the one which minimizes the expected total cost. A direct search method and a dual programming method are introduced, with emphasis on the latter. A numerical example is presented to illustrate the procedure. A sensitivity study is included on the effect of a wrong choice of the prior distribution.     

Design of generalized CSP-C continuous sampling plan

In this paper, the concept acceptance number has been incorporated to the single level continuous sampling plan CSP-1. The advantage of the proposed plan, designated as the CSP-C plan, is to achieve a reduction in the average fraction inspected at good quality levels. Nomographs for the design of the proposed plan are presented. The expressions of the performance measures for this new plan such as OC, AOQ and AFI are also provided.     

Design of acceptance sampling plan using a modified EWMA statistic

In this paper, a modified exponentially weighted moving average (EWMA) statistic is proposed. The approximate distribution of the proposed modified EWMA statistic is derived. A variable acceptance sampling plan is designed using the proposed EWMA statistic. The plan parameters of the proposed sampling plan are determined such that the given producer's risk and consumer's risk are satisfied. The efficiency of the proposed plan based on the new EWMA statistic is compared with the existing EWMA plan in terms of the sample size required. The application of the proposed plan is given with the help of an example.     

An empirical bayes approach to a variables acceptance sampling plan problem

An empirical Bayes approach to a variables acceptance sampling plan problem is presented and an empirical Bayes rule is developed which is shown to be asymptotically optimal under general conditions. The problem considered is one in which the ratio of the costs of accepting defective items and rejecting non-defective items is specified. Sampling costs are not considered and the size of the sample taken from each lot is fixed and constant. The empirical Bayes estimation of the Bayes rule is shown to require the estimation of a conditional probability. An estimator for conditional probabilities of the form needed is derived and shown to have good asymptotic properties.     

On designing an acceptance sampling plan for the Pareto lifetime model

In this paper, the design of reliability sampling plans for the Pareto lifetime model under progressive Type-II right censoring is considered. Sampling plans are derived using the decision theoretic approach with a suitable loss or cost function that consists of sampling cost, rejection cost, and acceptance cost. The decision rule is based on the estimated reliability function. Plans are constructed within the Bayesian context using the natural conjugate prior. Simulations for evaluating the Bayes risk are carried out and the optimal sampling plans are reported for various sample sizes, observed number of failures and removal probabilities.     

A group acceptance sampling plan for truncated life test having Weibull distribution

In this paper, a group acceptance sampling plan for a truncated life test is proposed when a multiple number of items as a group can be tested simultaneously in a tester, assuming that the lifetime of a product follows the Weibull distribution with a known shape parameter. The design parameters such as the number of groups and the acceptance number will be determined by satisfying the producer's and the consumer's risks at the specified quality levels, while the termination time and the number of testers are specified. The results are explained with tables and examples.     

Inverse-gaussian acceptance sampling plans by variables

Variable sampling plans to control fraction defective are obtained using the Inverse-Gaussian (IG) distribution. OC curves are obtained and impact of sample size and specification limits on these curves are discussed. Simulation studies are used to investigate sensitivity of the sampling plans under the more commonly used normal distribution.     

Economic design of continuous sampling plan under linear inspection cost

The article explores the problem of an economically based type I continuous sampling plan (CSP-1 plan) under linear inspection cost. By assuming that the per unit inspection cost is linearly proportional to the average number of inspections per inspection cycle, and by solving the modified Cassady et al.'s model, we not only have the required level of product quality but also obtain the minimum total expected cost per unit produced.     

A double acceptance sampling plan for generalized log-logistic distributions with known shape parameters

A double acceptance sampling plan for the truncated life test is developed assuming that the lifetime of a product follows a generalized log-logistic distribution with known shape parameters. The zero and one failure scheme is mainly considered, where the lot is accepted if no failures are observed from the first sample and it is rejected if two or more failures occur. When there is one failure from the first sample, the second sample is drawn and tested for the same duration as the first sample. The minimum sample sizes of the first and second samples are determined to ensure that the true median life is longer than the given life at the specified consumer’s confidence level. The operating characteristics are analyzed according to various ratios of the true median life to the specified life. The minimum such ratios are also obtained so as to lower the producer’s risk at the specified level. The results are explained with examples.     

Autoregressive processes applied to acceptance sampling by varlables

The effect of serial correlation on acceptance sampling plans by variables has been examined in this paper assuming the quality measurements follow an AR(p) process. The effect of serial correlation can be examined by comparing OC curves, sample size and producer's risks, ∝, with that of the independent case when the process standard deviation, σ, is known. When σ is unknown and for large n, sampling plans can be constructed using the central limit theorem. However, for σ unknown and for small n, there is no satisfactory method of obtaining sampling plans.     

Estimating general variable acceptance sampling plans by bootstrap methods

We consider variable acceptance sampling plans that control the lot or process fraction defective, where a specification limit defines acceptable quality. The problem is to find a sampling plan that fulfils some conditions, usually on the operation characteristic. Its calculation heavily depends on distributional properties that, in practice, might be doubtful. If prior data are already available, we propose to estimate the sampling plan by means of bootstrap methods. The bias and standard error of the estimated plan can be assessed easily by Monte Carlo approximation to the respective bootstrap moments. This resampling approach does not require strong assumptions and, furthermore, is a flexible method that can be extended to any statistic that might be informative for the fraction defective in a lot.     

Average outgoing quality of CSP-C continuous sampling plan under short run production processes

A CSP-C continuous sampling plan is a new single-level continuous sampling procedure developed by Govindaraju & Kandasamy (2000) by incorporating the concept of acceptance number to the CSP-1 plan for the application of continuous production processes. In this new plan, the sampling inspection phase is characterized by a maximum allowable number of non-conforming units, c, and a constant sampling rate, f. Govindaraju & Kandasamy (2000) derived the performance measures such as average outgoing quality (AOQ), average fraction inspected (AFI) etc, of the CSP-C plan using a Markov chain model for long run production processes. Yang (1983) has observed that the AOQ and AFI, being long run average measures, are not satisfactory measures of performance for short run production processes. Hence, formulas are derived in this paper, using the renewal theory approach enabling one to compute AOQ and AFI for both long run and short run production processes. Numerical illustrations are also given. By simulation, the accuracy of the short run measures is studied.     

Minimum average fraction inspected for continuous sampling plan CSP-1 under inspection error

SUMMARY In this paper, we present a further modification of Endres's method to construct the problem of minimizing the average fraction inspected (AFI) for the continuous sampling plan CSP-1 under inspection error. The measures of average outgoing quality under perfect and imperfect replacement conditions are considered. The formulae for searching the smallest clearance number i for minimizing the AFI for a CSP-1 plan are also provided. The solution procedure of the proposed method is more reliable, clearer and easier than that of Endres.     

Endorsement of acceptance sampling techniques by implementing neural networks

Acceptance sampling, a category of statistical quality control, deals with the confidence of the product's quality. In certain times, it is necessary to deal with the error in the demanding distribution counting on the sample size and the pertained population size, in determining the necessitated sample size for the acute exactitude. Further this sample size with minimized error is utilized in deriving the most beneficial OC curve. Neural networks have been used to train the data with the resulting error and their matching toleration level for the sample sizes of different population sizes. This trained network can be used to foster automated acceptance or rejection of the sample size to be used for a better OC curve based on the minimized error, ensuing time reduction of the burdened work. It is better explained in this paper with the geo-statistics data, using SAS program.     

Quick specification of acceptance sampling plans for dependent attribute sampling

Traditionally, fraction-nonconforming is treated as a Bernouilli variable with the attendant assumption of independence in constructing the acceptance sampling plans. This study relaxes the independence assumption in attribute sampling and provides a convenient nomogram to incorporate the effects of dependence into the sampling plans. The nomogram provides convenient answers for a number of questions about sampling with attributes. The study simplifies the procedural details, virtually eliminates the computation and facilitates the rapid scanning and evaluation of alternative solutions.     

Procedure for the selection of CSP-M one level skip-lot sampling inspection plans that have a single-sampling plan with acceptance number zero as the reference plan

This paper presents a procedure for the selection of CSP-M one-level skip-lot sampling plans, designated as CSP-MSkSP, that have a single-sampling plan with acceptance number zero as the reference plan. The parameters of the plan are determined when two points on the operating characteristic curve are specified, the two points being (p1,) and (p2,), where p1 is the acceptable quality level, is the producer's risk, p2 is the limiting quality level and is the consumer's risk.