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Provides an automatic spreadsheet approach to developing acceptance sampling plans. The technique described allows the user to develop the plan using any needed values for alpha and beta, rather than being limited to those values included in commonly used tables. This allows for more negotiation flexibility and acceptance sampling plans that better fit the needs of customers and producers.

A procedure for designing chain sampling plans, ChSP‐1, is described for situations where one of the parameters, the sample size, is fixed. The procedure involves minimisation of the sum of the producer′s risk and consumer′s risk with due weights. Expressions have been derived under binomial and Poisson models, for the parameter i , using which one can obtain the plan for desired values of AQL/LQL weights and sample size. Examples are also given.

Inspection error has been and continues to be an important area of research particularly in statistical quality control. While considerable work has been reported on the effect of inspection error on different sampling plans and the implications thereof, very little seems to have been done to assess the effects of such errors on MIL STD 105D plans. In this article some aspects related to inspection errors and operation of MIL STD 105D plans have been studied. Based on this study some observations have been made which have led to the development of a few subtle practical guidelines that may prove helpful to the operating manager in administering such plans effectively.

This article presents a new chain sampling plan for three atttibute classes where items are classified into three categories namely good, marginal and bad. Various performance characteristics of interest to quality control engineers and plan designers are derived through GERT approach. In order to facilitate the operation and construction of the plan, Poisson unity values have been tabulated for a useful subset of the proposed plan.

In order to reduce avoidably lengthy duration required to test highly reliable products under usage stress, accelerated life test sampling plans (ALTSPs) are employed. This paper aims to build a decision model for obtaining optimal sampling plan under accelerated life test setting using Type-I hybrid censoring scheme for products covered under warranty.

The primary decision model proposed in this paper determines ALTSP by minimizing the relevant costs involved. To arrive at the decision model, the Fisher information matrix for Type-I hybrid censoring scheme under accelerated life test setting is derived. The optimal solution is attained by utilizing appropriate techniques following a nonlinear constrained optimization approach. As a special case, ALTSP for Type-I censoring is obtained using the same approach. ALTSP under Type-I hybrid censoring using the variance minimization approach is also derived.

On comparing the optimal results obtained using the above mentioned approaches, it is found that the cost minimization approach does better in reducing the total cost incurred. Results also show that the proposed ALTSP model under cost function setting has considerably lower expected testing time. Interesting findings from the sensitivity analysis conducted using a newly introduced failure dataset pertaining to locomotive controls are highlighted.

The research introduces a model to design optimum ALTSP for Type-I hybrid censoring scheme. The practical viability of the model makes it valuable for real-life situations. The practical application of the proposed model is exemplified using a real-life case.

A brief review of the historical development of quality control is provided, followed by a discussion of some of its fundamental concepts. Two statistical techniques widely used in the traditional quality control programmes are then described and compared with the Japanese Taguchi Methods, an increasingly popular new approach to quality control.

The traditional practice for maintenance, quality control and production scheduling is to plan independently irrespective of an interrelationship exist between them. The purpose of this paper is to develop an approach for integrating maintenance, quality control and production scheduling. The objective is to investigate the benefits of the integrated effect in terms of the expected total cost of system operation of the three functions.

The proposed approach is based on the conditional reliability of the components. Cost model for integrating selective maintenance, quality control using sampling-based procedure and production scheduling is developed using the conditional reliability. An integrated approach is such that, first an optimal schedule for the batches to be processed is obtained independently while the maintenance and quality control decisions are optimized considering the optimal schedule on the machine. The expected total cost of conventional approach, i.e. “No integration” is calculated to compare the effectiveness of integrated approach.

The integrated approach have shown a higher cost saving as compared to the independent planning approach. The approach is practical to implement as the results are obtained in a reasonable computational time.

The approach presented in this paper is generic and can be applied at planned as well as unplanned opportunities. The proposed integrated approach is dynamic in nature, as during maintenance opportunities, it is possible to optimize the decision on maintenance, quality control and production scheduling considering the current age of components and production requirement.

The originality of the paper is in the approach for integration of the three elements of shop floor operations that are usually treated separately and rarely touched upon by researchers in the literature.

The purpose of this paper is to develop an exponentially weighted moving average (EWMA) control chart based on the Wilcoxon rank-sum (WRS) statistic using repetitive sampling to improve the sensitivity of the EWMA control chart to process mean shifts regardless of the prior knowledge of the underlying process distribution.

The proposed chart is developed without any distributional assumption of the underlying quality process for monitoring the location parameter. The authors developed formulae as well as algorithms to facilitate the design and implementation of the proposed chart. The performance of the proposed chart is investigated in terms of the average run-length, standard deviation of the run-length (RL), average sample size and percentiles of the RL distribution. Numerical examples are given as illustration of the design and implementation of the proposed chart.

The proposed control chart presents very attractive RL properties and outperforms the existing nonparametric EWMA control chart based on the WRS in the detection of the mean process shifts in many situations. However, the performance of the proposed chart relatively deteriorates for small phase I sample sizes.

This study develops a new control chart for monitoring the process mean using a two-sample test regardless of the nature of the underlying process distribution. The proposed control chart does not require any assumption on the type (or nature) of the process distribution. It requires a small number of subgroups in order to reach stability in the phase II performance.

Control charts for statistical quality control have been the subject of academic study for many years. Various analytical approaches to economic control chart design have been advanced, although none has found wide use in practice. Describes a simulation approach to the investigation of control chart economics. Simulation can provide guidance on chart design issues such as sample size, sampling interval and the use of alternative chart alarm rules. Applies the method to the economic comparison between variables control charting and other inspection strategies such as 100 per cent inspection. Presents some generalized results, allowing comparison to be made for various scenarios. Emphasizes the importance of process capability in the choice of quality control strategy and demonstrates the economic advantages of control charting where special or assignable causes exist.

In this first of a two‐part series, the methodology for the research is described. This took the form of a postal questionnaire carried out in conjunction with the Institute of Industrial Managers to establish the current situation. The results were compared with a similar study carried out in 1980. Work on the questionnaire was supplemented by a series of interviews and in‐company work. This included measurement of the movement of materials through the system and machine utilisation, the results and conclusions from which are presented. Part II of the series proposes a methodology for sustained improvement of production management systems.