There have been a number of studies on process control methods, although these theories are too complicated to be applied to manual control production processes. In these processes, an operator measures an important quality characteristic, and then changes a control variable to adjust the observed deviation in the characteristic. This simple paper proposes an approximate method of calculating a reduction factor for this adjustment using only two parameters of process errors and measurement errors. The degree of approximation in this method is evaluated for three typical types of process errors. The reduction factor calculated by this method has a constant value, while the reduction factors that vary according to the deviation are often used in actual production processes. This paper compares these two types of reduction factors in their control effectiveness. The method of estimating the reduction factors using operation data is also discussed.

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A theory of a probability paper for inverse Gaussian distribution is derived, and a utility of the probability paper is shown by using real data.

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Though the increasing importance of the service sector has focused attention on the quality of services as well as products, few empirical studies have been made on service quality and its evaluation. In this study, to determine factors by which consumers evaluate services, a multi-stage survey is made of four representative mass-market services. First, attributes constituting quality are determined for each service, and then consumer expectations for their improvement are surveyed. Factor analysis is applied to obtain latent evaluation factors which are compared between service categories. Evaluation factors representing function, completeness, ease of use, and emotion/environment are found to be quite universal. An additional factor representing assurance was also found for services considered to have a high degree of function-related variability or risk. It is shown that individual consumer's factor scores for these evaluation factors have significant correlation across service categories. Examination is also made of the relationship between respondent attributes and usage patterns and the derived evaluation factors.

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