In industrial realities, management systems have a categoriesed structure that studies the scope of application discriminating between the different production phases, the type of resources and the dedicated operating departments. The implementation of a quality management system integrates the Quality principle into manufacturing activities is an opportunity to guarantee the quality of research results and to improve and gain recognition for the work done in a research laboratory. In the context of a clean room of R&D production, we want analysing some process flows, which have been identified for this purpose, having as its ultimate goal the CR's already active quality system management model optimisation. This thesis work involves the use of various evidence-based and statistical tools for the definition and visualisation of processes, the identification of possible failures or criticalities and the definition of consequent corrective actions. This approach will define a new model for assessing and managing non-conformities, which are already dealt with the current quality system. The novelty introduced is the development of a management system starting from the knowledge of industrial realities certified and the codification of know-how developed in the MNF CR itself. A practical system declination is the proposal of preventive and corrective actions as tools for non-conformities and criticalities handling as highlighted in the monitoring of process activities. The thesis is organised in two phases. The first phase analyses Dry Etching process as the case study chosen for the definition of the model described above. This choice turns out to be sufficiently complex to represent a self-consistent system that we expect to capture the variability of operational parameters like a general model. For this reason, the second phase involves the study of the generalisation of the validity of the elaborated model to a second domain, relating to the field of deposition processes.