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This paper presents some possibilities of statistical process control that can be used when the basic requirements for the application of standard Shewhart control charts are not fulfilled. These basic assumptions that must be met include mainly a requirement on the normality of the data, the requirement for constant mean and variance, and last but not least the requirement for mutual independence of data. In practice, such as the metallurgical industry, those assumptions about the data are not necessarily always met. The stress in the article is put on the importance of the statistical process control as a part of the production management necessary for achieving a high product quality. Just the quality of the product decides on customer satisfaction and thus the success of the whole organization. The aim of this article is to describe some non-parametric control charts and concretely introduce one of the non-parametric control charts, namely Shewhart sign control chart, including a practical example from a metallurgical process. During preparation of this article accessible pieces of knowledge on the issue were compared. During this comparison of parametric and nonparametric methods it was found that nonparametric methods have many advantages and for cases where some of the basic assumptions about the data are not met they are appropriate. This article is the basis for further investigation of the problem, including a more detailed treatment of the particular non-parametric control charts.

Keywords: Statistical process control, nonparametric methods, production management, Shewhart sign control chart

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