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Presents a compact table yielding the parameters of a single sampling scheme. The table is compatible with the structure of MIL‐STD‐105D and the switching procedure incorporated in this scheme is relatively simpler than that of MIL‐STD‐105D. The basis for the construction of the table is given. Methods are given for the selection of a scheme having either acceptable quality level, limiting quality level, indifference quality level or average outgoing quality limit as a function of lot size.

This purpose of this paper is to present an optimization‐based approach to support the design of attribute sampling plans for lot acceptance purposes, with the fraction of non‐conforming items being modeled by a Poisson probability distribution function.

The paper approach stands upon the minimization of the error of the probability of acceptance equalities in the controlled points of the operating curve (OC) with respect to sample size and acceptance number. It was applied to simple and double sampling plans, including several combinations of quality levels required by the producer and the consumer. Formulation of the design of acceptance sampling plans as an optimization problem, having as a goal the minimization of the squared error at the controlled points of the OC curve, and its subsequent solution employing GAMS.

The results are in strong agreement with acceptance sampling plans available in the open literature. The papers approach in some scenarios outperforms classical sampling plans and allows one to identify the lack of feasible solutions.

An optimization‐based approach to support the design of acceptance sampling plans for attributes was conceived and tested. It allows for a general treatment of these problems, including the identification of a lack of feasible solutions, as well as making possible the determination of feasible alternatives by relaxing some model constraints.

Describes a study to measure the quality of service provided by food‐poisoning surveillance agencies in England and Wales in terms of the requirements of a representative consumer ‐ the egg producing industry ‐ adopting “egg associated” outbreak investigation reports as the reference output. Defines and makes use of four primary performance indicators: accessibility of information; completeness of evidence supplied in food‐poisoning outbreak investigation reports as to the sources of infection in “egg‐associated” outbreaks; timeliness of information published; and utility of information and advice aimed at preventing or controlling food poisoning. Finds that quality expectations in each parameter measured are not met. Examines reasons why surveillance agencies have not delivered the quality demanded. Makes use of detailed case studies to illustrate inadequacies of current practice. Attributes failure to deliver “accessibility” to a lack of recognition on the status or nature of “consumers”, combined with a self‐maintenance motivation of the part of the surveillance agencies. Finds that failures to deliver “completeness” and “utility” may result from the same defects which give rise to the lack of “accessibility” in that, failing to recognize the consumers of a public service for what they are, the agencies feel no need to provide them with the data they require. The research indicates that self‐maintenance by scientific epidemiologists may introduce biases which when combined with a politically inspired need to transfer responsibility for food‐poisoning outbreaks, skew the conduct of investigations and their conclusions. Contends that this is compounded by serious and multiple inadequacies in the conduct of investigations, arising at least in part from the lack of training and relative inexperience of investigators, the whole conditioned by interdisciplinary rivalry between the professional groups staffing the different agencies. Finds that in addition failures to exploit or develop epidemiological technologies has affected the ability of investigators to resolve the uncertainties identified. Makes recommendations directed at improving the performance of the surveillance agencies which, if adopted will substantially enhance food poisoning control efforts.

Sediment measurement is usually accessible on a periodic or distinct basis. The measurement of sediment (suspended and bedload), especially in the field, is vital in keeping essential data of sediment transport and deposition. Various techniques for measuring sediment have been used over time each with its merits and demerits. The techniques discussed in this paper for suspended sediment include bottle, acoustic, pump, laser diffraction, nuclear and optical. Other techniques for bedload measurement are; River bedload trap (RBT), CSU/FU bedload trap, Helley–Smith, Polish Hydrological Services (PIHM) device, pit and trough, vortex tube, radioactive traces and bedload–surrogate technologies. However, the choice of technique depends on multiple factors ranging from budget constraint, availability of equipment, manpower and data requirement. The purpose of this paper is to present valuable information on selected techniques used in sediment measurement, to aid researchers/practitioners in the choice of sediment measurement technique.

This paper presents a general review of selected field techniques used in sediment measurement (suspended and bedload). Each techniques mode of operation, merits and demerits are discussed.

This paper highlights that each technique has its peculiar merits and demerits. However, two techniques are generally preferred over others; the bottle sampling and the Helley–Smith sampler for measuring suspended and bedload sediment. This is because the applicability of these techniques is quite widespread and time-tested.

This review paper provides an in-depth description and comparison of selected existing field sediment measurement techniques. The objective is to ease decision-making about the choice of technique, as well as to identify the suitability and applicability of the chosen technique.

The purpose of this paper is to construct innovative exact and approximative sampling plans for acceptance sampling in statistical quality control. These sampling plans are determined for crisp and fuzzy formulation of quality limits, various lot sizes and common α- and β-levels.

The authors use generalized fuzzy hypothesis testing to determine sampling plans with fuzzified quality limits. This test method allows a consideration of the indifference zone related to expert opinion or user priorities. In addition to the exact sampling plans calculated with the hypergeometric operating characteristic function, the authors consider approximative sampling plans using a little known, but excellent operating characteristic function. Further, a comprehensive sensitivity analysis of calculated sampling plans is performed, in order to examine how the inspection effort depends on crisp and fuzzy formulation of quality limits, the lot size and specifications of the producer’s and consumer’s risks.

The results related the parametric sensitivity analysis of the calculated sampling plans and the conclusions regarding the approximation quality provide the user a comprehensive basis for a direct implementation of the sampling plans in practice.

The constructed sampling plans ensure the simultaneous control of producer’s and consumer’s risks with the smallest possible inspection effort on the one hand and a consideration of expert opinion or user priorities on the other hand.

The purpose of this paper is to propose a double exponentially weighted moving average control chart using repetitive sampling (RS-DEWMA) for a normally distributed process variable to improve the efficiency of detecting small process mean shift.

The algorithm for the implementation of the proposed chart is developed and the formulae for the in-control and out-of-control average run lengths (ARLs) are derived. Tables of ARLs are presented for various process mean shift. The performance of the proposed chart is investigated in terms of the average run-length for small process mean shift and compared with the existing DEWMA control chart. Numerical examples are given as illustration of the design and implementation of the proposed chart.

The proposed control chart is more efficient than the existing DEWMA control chart in the detection of small process mean shifts as it consistently gives smaller ARL values and quickly detects the process shift. However, the performance of the proposed chart relatively deteriorates for large smoothing constants.

The application of repetitive sampling in the control chart literature is gaining wide acceptability. The design and implementation of the RS-DEWMA control chart offers a new approach in the detection of small process mean shift by process control personnel.

This paper fills a gap in the literature by examining the performance of the repetitive sampling DEWMA control chart. The use of repetitive sampling technique in the control chart is discussed in the literature, however, its use based on the DEWMA statistic has not been considered in this context.

The purpose of this paper is to develop a group acceptance sampling plan (GASP) for a resubmitted lot when the lifetime of a product follows odds exponential log logistic distribution introduced by Rao and Rao (2014). The parameters of the proposed plan such as minimum group size and acceptance number are determined for a pre-specified consumer’s risk, number of testers and the test termination time. The authors compare the proposed plan with the ordinary GASP, and the results are illustrated with live data example.

The parameters of the proposed plan such as minimum group size and acceptance number are determined for a pre-specified consumer’s risk, number of testers and the test termination time.

The authors determined the group size and acceptance number.

No specific limitations.

This methodology can be applicable in industry to study quality control.

This methodology can be applicable in health study.

The parameters of the proposed plan such as minimum group size and acceptance number are determined for a pre-specified consumer’s risk, number of testers and the test termination time.

The purpose of this paper is to develop an economic model, which could determine the acceptance sampling plan that minimizes the quality cost for batch manufacturing.

The authors propose a variable sampling plan based on one-sided capability indices for dealing with the quality cost requirement.

The total quality cost is much more sensitive to process capability indices and inspected cost than internal and external failure costs.

The experimental data were randomly generated instead of real world ones.

The proposed model is specifically designed for manufacturing industries with high sampling cost.

The one-sided capability indices were utilized for the first time to be suitable for the purpose.

The most frequently used attribute sampling plan in MIL‐STD 105 D. In cases, however, when the quality level of incoming lots is generally sufficiently good, MIL‐STD 105 D often leads to unnecessarily high sampling cost. This can be avoided by using α‐optimal sampling plans. The authors outline the α‐optimal sampling scheme along with a simple procedure to determine α‐optimal sampling plans at workshop level. These plans depend on three parameters which have to be estimated from recorded data. In this article the effects of estimation errors in these parameters are investigated.