Risk preference,multiple attributes,and multiple criteria in bayesian acceptance sampling plans

Although there has been considerable research directed toward developing Bayesian acceptance sampling plans, little consideration has been given to incorporating a decision-maker's risk attitude or treating such problems in terms of multiple-type defects and multiple criteria. We review our own work which is focused on the above issues. A model incorporating risk preference is shown to yield substantial differences in the characteristics of an optimal sampling plan relative to a typical Bayesian linear cost (risk neutral) model. Bayesian models and optimization schemes for a variety of multiple-type defect plans are reviewed. A bicriterion acceptance model, employing average outgoing quality and average inspection cost is also formulated. Traditional versus interactive optimization procedures are compared empirically in terms of ease of use, satisfaction with solutions, and insight gained into the problem.     

Some experiences using MIL-STD-105 in the united states air force

The historical and, to some extent, the current role of attribute inspection sampling in the United States Air Force is described. Some insight into consideration culminating in revisions made to the original MIL-STD-105 sampling plans is provided. These revisions were motivated from a practitioner's perspective rather than that of a statistical expert. Some significant administrative applications within the Air Force are described, and a practical method, based on the total amount of inspection, is given for distinguishing between sampling plans that have a fixed risk level (i.e., common value on the OC curves).     

Stepwise inspection in Bayesian multiattribute acceptance sampling

Bayesian models for multiattribute acceptance sampling have been developed under the assumption that sampling inspection is carried to completion. A Bayesian multiattribute model for stepwise sampling inspection is proposed, whereby sampling inspection is terminated as soon as the disposition of the inspection lot is determined. An iterative solution procedure is developed for obtaining optimal or near-optimal multiattribute acceptance sampling plans under stepwise sampling inspection. The effect of stepwise sampling inspection on the characteristics of an optimal sampling plan is investigated. It is shown that stepwise sampling inspection achieves a sampling plan with lower total expected cost than complete sampling inspection. In addition, it is shown that the sequence of attributes in a stepwise sampling inspection substantially affects the sampling plan and resultant expected cost. The proposed methodology is used to evaluate various heuristics which may be used to determine the sequence of attributes in a stepwise inspection procedure.     

Design of sequential sampling inspection plans with screening based on minimal lattice paths

In this article we propose new sequential sampling inspection plans with screening indexed by LTPD and AOQL, in which the alternative of accepting or rejecting a lot is decided by the results of sequential sampling plans, based on the minimal lattice paths. It is illustrated that the average total inspection can be economized by using both of the proposed sequential sampling inspection plans, with screening indexed by LTPD and AOQL, respectively. © 1994 John Wiley & Sons, Inc.     

Sequential and systematic sampling plans for the Markov‐dependent production process

Acceptance sampling plans are used to assess the quality of an ongoing production process, in addition to the lot acceptance. In this paper, we consider sampling inspection plans for monitoring the Markov‐dependent production process. We construct sequential plans that satisfy the usual probability requirements at acceptable quality level and rejectable quality level and, in addition, possess the minimum average sample number under semicurtailed inspection. As these plans result in large sample sizes, especially when the serial correlation is high, we suggest new plans called “systematic sampling plans.” The minimum average sample number systematic plans that satisfy the probability requirements are constructed. Our algorithm uses some simple recurrence relations to compute the required acceptance probabilities. The optimal systematic plans require much smaller sample sizes and acceptance numbers, compared to the sequential plans. However, they need larger production runs to make a decision. Tables for choosing appropriate sequential and systematic plans are provided. The problem of selecting the best systematic sampling plan is also addressed. The operating characteristic curves of some of the sequential and the systematic plans are compared, and are observed to be almost identical. © 2001 John Wiley & Sons, Inc. Naval Research Logistics 48: 451–467, 2001     

Optimal Bayesian single-sampling attribute plans with modified beta prior distribution

In this article we study the properties of the optimal Bayesian single-sampling plans when the prior distribution of the lot fraction defective is modified Beta, which has been found useful in the analysis of inspection schemes for complex production systems. These properties are used to devise an improved and more efficient algorithm for the determination of the optimal sampling plans. Numerical examples are presented to illustrate the potential computational savings of the algorithm.     

Economic design of sampling plans with multi-decision alternatives

For situations where there are several markets with different profit-cost structures, economic attributes sampling plans are developed for determining the market to ship the lot to. Two sampling plans are considered; the fixed-size sampling plan with several levels of acceptance numbers, and the inverse sampling plan with several levels of sample sizes. Linear profit models are constructed which involve four profit/cost components; profit from a conforming item, inspection cost, replacement cost, and cost from an accepted nonconforming item. For fixed-size and inverse sampling plans, methods of finding optimal sampling plans are presented and examples with beta-binomial prior distributions are given.     

计数序贯抽样检验方案的OC函数和ASN

根据序贯概率比检验的理论,给出计数序贯抽样检验方案的设计原理,得到国家标准GB／T8051—2008中计数序贯抽样检验方案的OC函数和ASN的计算方法。     

The effect of nonnormality on variables sampling plans

Acceptance sampling plans based on variables have been in use for many years. Recently, there has been a renewal of interest in these plans, because of the relative efficiencies that they offer with respect to attributes sampling regarding sample size. Furthermore, in situations where acceptable quality levels are very small, and a high level of protection is desired, variables sampling is often much more efficient than attributes sampling. An important disadvantage of variables sampling is that the distribution of the parameter being inspected must be known. Most standard variables sampling plans assume that the distribution of this parameter is normal. This article examines the effect of the normality assumption in variables sampling. Methods to detect departures from normality are reviewed.     

Application of dirichlet integrals for curtailment problems in sampling inspection

The standard problem in sampling inspection is to consider plans with and without curtailment. Curtailment causes difficulty and authors rarely give exact results (i.e., exact OC and ASN functions) for curtailed procedures. In this article we regard curtailment as an inverse sampling procedure and use Dirichlet integrals to obtain exact formulas for the OC, the ASN, and also the variance of the number of observations required under three types of plans: no curtailment, semicurtailment (for rejection only) and two-sided curtailment. Different sections of the article deal with the single sample, the two-stage, and the multiple-stage sampling problems. New tables for carrying out the single-sample procedure are included in the article. The authors feel that this article presents new directions and new ways of dealing with problems associated with quality control.     

On the use of standard tables to obtain Dodge-Romig LTPD sampling inspection plans

Procedures are described which yield single and double sample Dodge-Romig [1] lot tolerance percent defective (LTPD) rectifying inspection plans. For the determination of such plans only a desk calculator and standard tables of the discrete probability distributions are required. Some advantages gained by using these procedures rather than the Dodge-Romig table include: (a) The Consumer's Risk is not limited to 0.10. (b) More choices of LTPD are available. (c) Smaller average total inspection is achieved by using a plan designed for specific “process average” and lot size rather than a compromise plan designed to cover intervals on these two parameters.     

Qmp/USP: A modern alternative to MIL-STD-105D

The Quality Measurement Plan (QMP) and the Universal Sampling Plan (USP) are the data analysis and sampling plans for the AT&T Technologies quality audit. This article describes QMP/USP, an acceptance sampling plan based on QMP and USP principles. QMPIUSP is a complete acceptance sampling system. It combines the elements of classical rectification inspection plans with those of MIL-STD-IOSD. There is no switching between plans, no tables of numbers to look through, and no discontinue state. QMP/USP is a computerized, self-contained system that features:

• Acceptance decisions based on the QMP Bayes empirical Bayes analysis of current and past sampling result
• Sample size selection based on USP, i.e., lot size, AQL, a cost ratio, the QMP analysis, and a budget constraint
• Guaranteed AOQ
• A complete statistical analysis of the quality process.

In this article, we describe the operation of QMP/USP and compare its performance with that of MIL-STD-IOSD. The comparison is made under many different quality environments with many metrics. Our results show that QMP/USP and MIL/STD/IOSD perform similarly for the environments where quality could be described as “in control”; and that QMPlUSP is superior in the environments where quality is “out of control”.     

A backward recursive technique for optimal sequential sampling plans

This paper presents a procedure akin to dynamic programming for designing optimal acceptance sampling plans for item-by-item inspection. Using a Bayesian procedure, a prior distribution is specified, and a suitable cost model is employed depicting the cost of sampling, accepting or rejecting the lot. An algorithm is supplied which is digital computer oriented.     

Joint determination of optimum variable and attribute target means

This article considers the problem of joint control of attribute and variable quality characteristics of a given product. Items are acceptable if they meet the specifications for both types of quality characteristics at the same time. Otherwise, the items are sold as scrap at reduced prices. The objective is to determine simultaneously the target values for each characteristic so as to maximize the expected profit per item. Several item-by-item quality-inspection plans are formulated on the basis of various inspection strategies. These strategies are defined in terms of whether the inspection is to be carried out simultaneously for both characteristics, or sequentially, or whether inspection for one of the characteristics is to be ignored. All these plans are shown to differ in terms of their profitability. However, they all yield equivalent quality standards. A numerical example is provided to illustrate the application of these models.     

A cost analysis of sampling inspection under Military Standard 105D

Military Standard 105D has been almost universally adopted by government and private consumers for the lot-by-lot sampling inspection of product which may be inspected on a dichotomoun basis The plan specifies, for each lot size, a random sample size and set of acceptance numbers (maximum allowable number of defectives in each sample). The acceptance numbers are based upon the binomial distribution and depend upon the quality required by the purchaser. Where several consecutive lots are submitted, a shift to less severe (“reduced”) inspection or more severe (“tightened”) inspection is specified when the ongoing quality is very high or low. Further experience permits a return to normal sampling from either of these states This paper examines the long range costs of such a sampling scheme. The three inspection types are considered as three distinct Markov chains, with periodic transitions from chain to chain. The expected sample size and the expected proportion of rejected product are determined as a function of the two parameters under control of the manufacturer, lot size and product quality. Some numerical examples are given which illustrate how to compute the overall cost of sampling inspection. Suggestions are made concerning the choice of parameters to minimize this cost.     

计数抽样检查标准ISO2859、JISZ9015、GB2828放宽检查抽样方案优良性分析

文对ISO2859、JISZ9015和GB2828三个标准的放宽检查抽样方案的OC和ASN曲线进行了全面的计算和分析,重点讨论了上述标准的二次和多次抽样方案的等效性和有效性,并对各标准优良性进行了分析和评价。     

Continuous sampling plans for markov-dependent production processes

This article discusses the behavior of three continuous sampling plans: continuous sampling plan 1 (CSP 1) and continuous sampling plan 2 (CSP 2) developed by Dodge [5] and Dodge and Torrey [7], and multilevel continuous sampling plan 2 (MLP 2) developed by Lieberman and Solomon [11], when the quality of successive units in a continuous production process follows a two-state time-homogeneous Markov chain. We first derive the average outgoing quality (AOQ) expressions of these plans. Exact procedures for determining the average outgoing quality limit (AOQL) can be obtained only for CSP 1. For CSP 2 and MLP 2 plans, iterative procedures have been used to obtain the AOQL contours. For these plans, it is assumed that the serial correlation coefficient between the two consecutive random variables of the Markov chain is known. In addition, estimation procedures for the coefficient are given. We show that if the serial correlation coefficient of the Markov chain is positive (negative), the AOQL is increased (decreased) as compared to the case when the successive units in the production process follows a Bernoulli pattern. Let r denote the number of production units examined in succession which are found to be of good quality and k denote the inverse of the sampling fraction employed when quality is good. Then if r and k are sufficiently small, it is observed from the graph that, for small departures of the serial correlation coefficient from zero, the AOQL values do not differ significantly for each of the three plans; whereas for sufficiently large values of r and k, the AOQL values differ significantly. Various aspects of these plans, such as their operating characteristics 2 (OC 2) and the serial correlation coefficient, are discussed.     

统计抽样方法在外语单词测验中的应用

本文通过分析一般工业产品计数抽样检验方法与外语单词专项测验的特点,发现二者本质相同。利用统计抽样方法不仅可以获得随机样本(试卷),排除某些主观干扰,同时还可以对受试方和考核方风险率进行评价和选择(按四个分级标准,给出了风险率不同的六组测验方案)。此法已为《大学英语词汇系统软件》采用.     

Systems approach to the multistage manufacturing connected-unit situation

This paper investigates the relationships among incoming quality limit (AIQL), manufacturing quality level in each stage of production, and outgoing quality limit (AOQL), for a multistage manufacturing connected-unit situation from the systems cost-effectiveness point of view. An objective function is developed and the formulated problem is solved using discrete optimization technique. The study is restricted to the development of single sampling plans where inspection is by attribute. Lot size and sample size are fixed for incoming and outgoing inspection for each stage of manufacturing.     

Variable sampling plans for normal distribution indexed by Taguchi's loss function

Taguchi has presented an approach to quality improvement in which reduction of deviation from the target value is the guiding principle. In this approach any measured value x of a product characteristic X brings a loss to consumer in general, where the loss is expressed as a quadratic form with respect to the difference between the measured value x and the target value T of a product characteristic. Then, it is natural to reject the lot which may bring a large loss to consumer. This concept induces us to construct new variable sampling plans based on the Taguchi's loss criterion. In this article, a design procedure of the sampling plans for assuring the loss in the Taguchi's method is proposed. Some numerical results based on the proposed design procedures are illustrated. © 1997 John Wiley & Sons, Inc. Naval Research Logistics 44: 591–603 (1997)