This paper concerns the application of Process Control Techniques (PCTs) for the improvement of the technical performance of discrete production processes. Successful applications of these techniques, such as Statistical Process Control Techniques (SPC), can be found in the literature. However, some companies do not manage to apply PCTs successfully. In some cases applying PCTs does not lead to an improvement of the technical performance, or it leads to a reduced financial performance. Lack of management commitment and training are often said to be the reason for a failing implementation. However, it is probable that also situational factors, related to the type of process and production organisation, are influencing the degree of success. Besides the success of implementation activities, the potential success or applicability of PCTs is also determining the total success. In the literature however, one often starts from the point of a ‘best practice’ for the application of PCTs. Considering the assumption of applicability this ‘best practice’ has to be differentiated to prevent companies from trying to implement unsuitable PCTs. In this paper, besides the concept of applicability, a framework for the application of PCTs is presented. By using this framework, the functions of PCTs and their relationships are illustrated. The framework has been developed as a tool for a research on the applicability of PCTs. The aim of this research is to differentiate the best practice concept. This has to result in a decision support system, that helps to determine the most suitable set of techniques, based on situational characteristics.