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A Markov model is considered to calculate the steady state availability of a system which may adopt several stages of degradation and is subject to random failures at each stage of degradation. Minimal maintenance and partial repairs restore the system to the previous degraded stage and to the operational stage just before failure, respectively. Overhaul repair returns the system to “as good as new” after degradation failure. Finally, the mean time to minimal maintenance minimizing the unavailability is determined.

The paper presents a combined model of reliability and performance (performability model) of two modules in series, each has C components in parallel. The objective of the paper is to illustrate the effect of the reliability on the performance. The paper emphasizes homogeneous continuous-time Markov process and queueing approach for reliability and performance models respectively. A numerical example when C=2 is provided to illustrate the results.

A performance capability measure is proposed that is useful in a wide class of production processes. Traditional quality improvement methodologies concentrate on getting the process right in order to meet the capability requirements of the product immediately after production, as measured for a key quality characteristic by one of the popular capability indexes. This is not the best strategy when the characteristic degrades over time in use. The implications of this type of degradation on targeting the production process are investigated and illustrated for five typical degradation models. A method is given which enables the optimum settings for the target values of the process mean and standard deviation to be chosen, given a particular model for product degradation. Commonly used philosophies which advocate targeting at the centre of the specification range are shown to be sub-optimal. A useful consequence of better targeting practice is that warranty periods can be extended without increasing the costs associated with supporting warranty claims.

Many researches have shown that the adaptive control charts are more effective than the traditional static ones in detecting process shifts. This paper develops an algorithm for the optimization designs of the Variable Sample Size ( VSS ) np chart and the Variable Sampling Intervals ( VSI ) np chart for monitoring process fraction nonconforming p . The properties of the VSI and VSS np charts are measured by the steady-state Average Time to Signal ( ATS ). The performance of these adaptive np charts are studied and compared with the static np charts. It is found that the adaptive np charts do improve the effectiveness significantly, especially for detecting small or moderate process shifts.

This paper presents a correction plan for maintaining high quality level of production processes. The Graphical Evaluation and Review Technique (GERT) is applied to model and analyze the dynamic characteristic of the plan. Unity values are tabulated to facilitate operation and construction of plans.

To run a production processes an appropriate target for the process mean has to be fixed, for presenting process capability a suitable target for a process capability index has to be selected. Generally, the two targets are fixed independently. This paper presents a method which combines both targets with respect to process mean and process capability under a fuzzy environment. By defining linear membership functions for relaxing the strict conditions on the above given two targets, a minimax approach is used for obtaining a solution of the problem.

Industrial quality control is necessary at least for two reasons: Monitoring product or process quality in order to perform interventions for assuring a desired quality level. Monitoring product or process quality in order to meet certain requirements (imposed by law or customers) for documentation. Especially in the second case legal requirements or consumers demand that “professional” methods are used. Therefore, industry relies on the methods offered by “professional” bodies like the International Organization for Standardization (ISO) or its national counterparts for example the German DIN Deutsches Institut für Normung, because they are widely acknowledged as professional. One of the standards which are in use in German industries is DIN 55303 (Teil 5): “Statistische Auswertung von Daten - Bestimmung eines statistischen Anteilsbereichs” of February 1987 which corresponds to ISO 3207-1975 “Statistical interpretation of data: determination of a statistical tolerance interval.” This paper introduces in detail statistical tolerance intervals and subsequently examines the standard critical. This first part is devoted to the case that the normal approximation is used and results in the recommendation not to use the methods offered in the standard. A second part will investigate the case that the normal approximation is not made.

This paper compares semi-economic -control charts and -R control charts assuming two different discrete distributions for the length of the in-control period of a production process with regeneration points given by the alarms signals. Sample sizes and control limits for a set of parameters are calculated for both models. For comparison purposes, values of average cost and of probabilities of Type I and II errors are also computed and displayed.

Considerable work has been done to investigate the sensitivity of explosive materials. Various methods are developed for determining statistically the “explosion characteristics”. Any statistical method is based on a stochastic model and, clearly, an inappropriate model yields generally meaningless results, independently of the applied method. The most commonly applied method in the field of explosive material is known as Bruceton method. In this paper the Bruceton method and the underlying model are analyzed critically and the conclusion is drawn that the Bruceton method cannot be recommended for determining the sensitivity of explosive material. In a subsequent paper a different approach to solve the problem will be suggested.