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Acceptance sampling plans by variables are a basic quality control technique. These plans provide economical procedures to determine the acceptability of batches of product. Most of these plans are based on a single quality characteristic and are of the classical type. This work concentrates on Bayesian variable acceptance sampling plans for fraction defective. Both destructive and non-destructive sampling procedures are considered. A set of decision points are estimated and employed to make decisions about the inspected lots. Techniques to dispose of the rejected lots are provided. Components of the expected total cost relative to various decisions are estimated. The sample size required to obtain the expected optimum cost is found. An untrue assumption implicit in the measurement of the quality characteristic of items sampled is that the observed dimensions are error free. The distributions, means, and variances of a set of parameters for error free and error prone sampling is listed. Computer programs written in FORTRAN 77 are developed to compute the decision points and the costs for both destructive and nondestructive testing. Precise Bays estimate of the costs and other economic parameters involve the moments of the fraction defective p raised to the kᵗʰ power. Mathematical expressions for the conditional expectations of p|x and p|ẋ are derived and a computer program to estimate these moments is provided. Producing quality items with minimum cost requires keeping a production process under control. The quality characteristic X of each item produced is determined and the sample means are plotted on an Ẋ-control chart. A production process is assumed to start in control at time t = 0 with specific values of the mean and standard deviation. The occurrence of a single or multiple cause-failures shift the process mean outside the control limits. During the search for the causes of failure, the process is either allowed to continue in operation or shut down until the assignable cause or causes are discovered. The expected duration of time during which the process is shut down and the additional time to be taken to repair the process are considered. Computer programs are provided to estimate the optimal sample size, the interval between successive samples, the control limits, the probability of type I error, the power of the chart, and the average time the process operates in the presence of an assignable cause. The parameters estimated are employed to estimate the optimal loss-cost. The economic design of Ẋ -charts assumes one quality characteristic of interest. However a product quality in most industrial products and processes is characterized by more than one quality characteristic where the application of a Ẋ -control chart for each variable is inappropriate. In this work a Hotellings T² control chart is employed to handle cases of where products are tested relative to several quality characteristics.

The problem of utilizing blending techniques to control coal quality at the production-consumption phase is considered. Three blending models were developed to provide coal of high thermal content and low pollutants. With the aid of operational mine planning, coal is blended at the coal producing mines such that the best quality of coal is mined during a planning period, while meeting the management production objectives. The first model developed uses 0-1 programming formulation to select potential working areas of a mine on the basis of predicted grade values obtainable from geostatistics. A second model developed combines economically coals produced by different suppliers to meet the specification of a power plant. The second model uses a linear programming formulation to develop coal purchasing strategy. Finally, a multiobjective programming technique is used to determine the tonnages of coal which must be cleaned from various sources (e.g. stockpiles) in order to result in clean coal of high thermal content and low sulfur content. The two objectives used are minimization of total sulfur and maximization of total Btu. Both the operational mine planning and coal purchasing models were tested on actual mine data. The study demonstrated the capability of controlling coal quality by blending technique with the aid of the three models. This can be translated into dollar savings to both the coal producer and the coal consumer.

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This study uses Monte Carlo simulation to examine the performance of a variable frequency sampling cumulative sum control chart scheme for controlling the mean of a normal process. The study compares the performance of the method with that of a standard fixed interval sampling cumulative sum control chart scheme. The results indicate that the variable frequency sampling cumulative sum control chart scheme is superior to the standard cumulative sum control chart scheme in detecting a small to moderate shift in the process mean.

The objectives of this study were to investigate the hypotheses that: (1) Job satisfaction is related to medical specialty, the physician's nationality, and length of tenure. (2) The physician's attitude toward the Drug Utilization Review (DUR) program is related to medical specialty, the place of residency training, length of tenure, and job satisfaction. (3) The quality of drug prescribing is related to medical specialty, the place of residency training, length of tenure, job satisfaction, and the physician's attitude toward the DUR program. The results indicated a significant relationship between the physician's nationality and job satisfaction (P = 0.001), and between job satisfaction and the physician's attitude toward the DUR program (P 0.001). Medical specialty was a strong independent predictor of the quality of drug prescribing (P = 0.002). However, the other independent variables of the locale of residency training, length of tenure, job satisfaction, and the physician's attitude toward the DUR program were not related to drug prescribing.

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