Selection of a tightened-normal-tightened system for given values of the acceptable quality level and limiting quality level

A table and a procedure are given to find the tightened-normal-tightened system involving the minimum sum of producer's and consumer's risks for a specified acceptable quality level and limiting quality level.     

Selection of ChSP-1 chain sampling plans for given acceptable quality level and limiting quality level

Procedures and tables are given for the selection of chain sampling plans of type ChSP-1 for given acceptable quality level, producer's risk, limiting quality level and consumer's risk. Selection of ChSP-1 plan is discussed for both proportion nonconforming and the number of nonconformities per unit.     

Modified tables for the selection of quick switching systems for values of the given acceptable quality level and limiting quality level

The paper presents modified tables derived from the work of Romboski and Soundararajan & Arumainayagam for the selection of quick switching systems of type QSS-2, QSS-3 and QSS-4 for given values of acceptable quality level, limiting quality level, producer's risk and consumer's risk. The plans selected from the tables will involve a smaller average sample number at the acceptable quality level.     

Minimum risks chain sampling plans (ChSP-4(c1, c2,)) indexed by acceptable quality level and limiting quality level

summary In this paper, an approach for designing ChSP-4 (c1,c2) plans while minimizing the sum of risks when the sample size is fixed is described. A set of quality level Also, an improved procedure for constructing plans with a given operation ratio is provided.     

Selection of modified quick switching systems for given acceptable and limiting quality levels

A set of tables and procedures are given for finding the modified quick switching systems for which the sum of producer's and consumer's risks is minimized for specified acceptable quality level and limiting quality level.     

Hierarchical bayes quality measurement plan

Quality Measurement Plan (QMP) as developed by Hoadley (1981) is a statistical method for analyzing discrete quality audit data which consist of the expected number of defects given the standard quality. The QMP is based on an empirical Bayes (EB) model of the audit sampling process. Despite its wide publicity, Hoadley's method has often been described as heuristic. In this paper we offer an hierarchical Bayes (HB) alternative to Hoadley's EB model, and overcome much of the criticism against this model. Gibbs sampling is used to implement the HB model proposed in this paper. Also, the convergence of the Gibbs sampler is monitored via the algorithm of Gelman and Rubin (1992).     

Selection of multiple deferred state MDS-1 sampling plans for given acceptable quality level and limiting quality level involving minimum risks

A table and a procedure are given for finding the multiple deferred state sampling plan of type MDS-1 involving minimum sum of risks for specified acceptable quality level and limiting quality level.     

The effectiveness of coach turnover and the effect on home team advantage,team quality and team ranking

The effectiveness of coach turnover on team performance is widely discussed in the literature due to the indirect impact of a team's performance on a club's revenues. This study examines the effect of coach turnover within a competition season by focusing on the change in team quality and the change in home team advantage under the new coach. The change in team quality or home team advantage can vary according to the team (team specific) or might be an independent quantity (non-team specific). We estimated nine possible regression models, given no change, team-specific change and non-team-specific change in quality or home team advantage. The data are the match results of Belgian male soccer teams playing in the highest national division during seven seasons. Results point to a team-specific effect of a new coach on a team's quality. This article further contributes by evaluating the new coach's success with regard to whether his ability to improve team quality also results in a better position of the team in the final ranking. A new coach will be able to improve the ranking of the team if the improved team quality under the new coach renders a positive team quality.     

A new sampling plan under the exponential distribution

This article considers a sampling plan when the quality characteristic follows the exponential distribution. We provide the exact approach and propose an approximated approach. In the proposed approximation, a new statistic combined with a Weibull transformation is used for the normal approximation. The plan parameters are obtained through the two-point approach at the acceptable quality level (AQL) and the limiting quality level (LQL). The tables for plan parameters are reported according to various values of the AQL and the LQL when the producer's and the consumer's risks are given. A real example is given to illustrate the proposed approximation approach.     

Selection of conditional sampling plans for given AQL and LQL

This paper presents procedures and tables for the selection of conditional sampling plans, viz. conditional double sampling plan, chain-deferred sampling plan, link sampling plan, and ChSP-4A chain sampling plan for given acceptable quality level (AQL), producer's risk, limiting quality level and consumer's risk giving minimum sample size at AQL under the conditions of the Poisson model for the operating characteristic curve.     

A Bayesian nonparametric model for Taguchi's on-line quality monitoring procedure for attributes

A Bayesian nonparametric model for Taguchi's on-line quality monitoring procedure for attributes is introduced. The proposed model may accommodate the original single shift setting to the more realistic situation of gradual quality deterioration and allows the incorporation of an expert's opinion on the production process. Based on the number of inspections to be carried out until a defective item is found, the Bayesian operation for the distribution function that represents the increasing sequence of defective fractions during a cycle considering a mixture of Dirichlet processes as prior distribution is performed. Bayes estimates for relevant quantities are also obtained.     

Analytical approach for determining the cost optimum raw material quality level

In this paper, the expected cost of a raw

material quality characteristic is determined and

the cost optimum quality level is found. A series

of piecewise linear functions is used torepresent a general cost function. Examples are given in

which the distributions of quality characteristics are treated as being either

uniform or normal. The relationship between a raw

material characteristic and manufacturing cost is

assumed to be known

Determining cost optimum quality level Manitoba     

Zero defects: a quality costs approach

Zero Defects has been advocated a s the ultimate target for quality control and assurance.Thispaper conducts an economic analysis of such a concept.The traditional frame work of quality

costs analysis is used to provide the bas is of analysis.A modified quality costs model is formulated to incorporate the revenue effects of quality and the dynamic nature of the manufacturing environment.It is shown that,for the quality cost model specified in this paper,the optimal dynamic strategy for the producer is to continuously improve product quality. Further more,the consumers'perspective and the existence of hidden or unidentifiable defects further reinforce the importance of quality improvement.In this way,a sound economic basis is provided for the Zero Defects concept.     

Algebraic statistics of level codings for fractional factorial designs

We discuss the applications of algebraic statistics to fractional factorial design with special emphasis on the choice of level coding. In particular, we deal with the theory of Bayley's level codings in that framework.     

Construction and selection of skip-lot sampling inspection plans of type SkSP-2 indexed by indifference quality level and maximum allowable per cent defective

This paper presents tables based on the Poisson model, for the selection of skip-lot sampling plans of type SKSP-2, with a single-sampling plan which has a zero acceptance number as a reference plan. The indifference quality level (IQL) and the maximum allowable per cent defective (MAPD) are the criteria used for fixing the plan. Procedures for the selection of plans for given conditions of (IQL, average outgoing quality limit) and (MAPD, average outgoing quality limit) are also discussed.     

Optimal designing of an SkSP-R double sampling plan

In this article, we propose a method of planning and determining the optimum parameters of a SkSP-R skip-lot sampling plan by using the attribute double sampling plan as the reference plan. The SkSP-R plan is a new type of skip-lot sampling plan which has a provision for re-inspecting the submitted lots. The optimal plan parameters of the suggested sampling plan are estimated with the target that the average sample number be minimized and satisfying both the specified producer's as well as the consumer's risks simultaneously. In order to obtain the optimum parameters, tables are also built for different combinations of the acceptable quality level and the limiting quality level in conjunctions with different producer's and consumer's risks. An illustrative example is provided for the implementation of the suggested plan. The advantages of the suggested plan over the existing conventional sampling plans and other existing skip-lot sampling plans are also described.     

Tables of cumulative distribution functions and percentiles of the standardized stable random variables

It is shown that Zolotarev's (1964) integral representation of the cumulative distribution function (c.d.f.) of stable random variables and the IMSL subroutine DCADRE (for numerical integration ) provide a natural and practically simple method for finding the values of c.d.f., the percentiles and the density function of such random variables. For symmetric stable random variables (r.v.'s ) Z_∝, values of P_∝(z) … P(0<Z_∝<z) for z … 0(.02)4.08 and ∝=.1(.2)1.9, as well as percentiles of these r.v.'s for ∝=.5(.1)2 and the percentage points .6, .7(.05).85(.025).9(.01).96(.005).995, are presented. For asymmetric stable r.v.'s we present values of their c.d.f.'s for z … 0(.1)4, ß= ?1(.25)1 and ∝=.1(.2)1.9. These result sare compared with related results of others which were obtained by using different procedure and standardization.     

Some exact results on the sample autocovariances of a seasonal ARIMA model

A seasonal random walk is an ARIMA process such that the first difference of order s (s ≥ 1) is a white noise. Given a series of observations from a particular linear transformation of a seasonal random walk, we study the autocovariances c'(k) based on uncentered data and the autocovariances c(k) based on centered data. In both cases, we provide exact, explicit formulae for the mean, variance, and covariance of the sample autocovariances. It is seen that the moments of the c(k)'s are different from those of the c'(k)'s, even asymptotically. Several analytical results presented in the paper were derived by using a symbolic manipulation program.     

Adaptive bootstrap tests and their competitors in the c -sample location problem

This paper deals with a power comparison of different types of tests, parametric, nonparametric, robustified and adaptive ones for the two-sided c -sample location problem. A robustness study on level f in the case of heteroscedasticity and non-normal distributions is included in our study, too. First of all, we consider an adaptive test based on Hogg's concept and two adaptive Bootstrap tests using Hogg's principle. It turns out that the adaptive Hogg-test is the best one in the case of homoscedasticity but for heteroscedasticity, an adaptive Bootstrap test using Hogg's principle is preferable.     

Acceptance sampling plan based on an exponentially weighted moving average statistic with the yield index for autocorrelation between polynomial profiles

Acceptance sampling plans based on process yield indices provide a proven resource for the lot-sentencing problem when the required fraction defective is very low. In this study, a new sampling plan based on the exponentially weighted moving average (EWMA) model with yield index for lot sentencing for autocorrelation between polynomial profiles is proposed. The advantage of the EWMA statistic is the accumulation of quality history from previous lots. In addition, the number of profiles required for lot sentencing is more economical than in the traditional single sampling plan. Considering the acceptable quality level (AQL) at the producer's risk and the lot tolerance percent defective (LTPD) at the consumer's risk, we proposed a new search algorithm to determine the optimal plan parameters. The plan parameters are tabulated for various combinations of the smoothing constant of the EWMA statistic, AQL, LTPD, and two risks. A comparison study and two numerical examples are provided to show the applicability of the proposed sampling plan.