This paper presents Borne case studies of quality control practices based on the authors' visits to Borne manufacturing industries. The statistical methods applied in each quality control programme are emphasized.
IntroductionThe term quality control in its broad sense means the total activities of the staff of a company in carrying out its quality objectives. These objectives need not aim at producing the best quality that the manufacturer can possibly make, but the quality that can meet the consumer's satisfaetion at an agreed price on the product. Generally speaking, a manufacturer's primary aim in running an industry is to achieve the maximum possible profit by rational means. It is a characteristic of modern mass production techniques that statistical methods are particularly useful in the control of quality, and should have the effect of improving quality at reduced costs.Over the last forty years, there has grown up a vast literature on statistical techniques for quality surveillance, including acceptance sampling schemes, control charts, continuous sampling plans, cusum charts, and many other modified methods. Two recent surveys of the situation are provided by Dodge (1969) and Chiu and Wetherill (1973). The majority of these techniques are either purely theoretical work or are proposed and studied under simplified assumptions on the production model or with hypothetical data. These idealized conditions mayor may not be realistic. Although it is known that some of these statistical methods have been successfully applied in practice, there has been little written on the practical aspect of how they are actually applied. A study of some quality control practices is hence desirable. Such a study may provide some practical information for the practising quality control managers and industrial statisticians.In 1971 and 1972, the authors visited a number of factories in Britain and in Hong Kong to study their quality control and quality assurance practices, with special attention to the statistical methods employed. A selection of