MODEL-BASED MONITORING OF NOZZLE CLOGGING IN FUSED DEPOSITION MODELLING PROCESS

Abstract

3D printing and particularly fused deposition modelling (FDM) is widely used for prototyping low-cost customised parts. However, current FDM 3D printers have several process errors which tend to influence the quality of prototyped parts. One of such process errors that was not fully addressed yet is nozzle clogging in FDM 3D printing. Nozzle clogging is one of the significant process errors in FDM 3D printers, and it affects the quality of the prototyped parts. In addition, present FDM 3D printers have limited process monitoring techniques to track precise nozzle clogging conditions and minimise process failures. This thesis proposes a model-based monitoring of nozzle clogging in FDM process. The proposed model and method can be used efficiently for monitoring nozzle clogging conditions in FDM 3D printers as users can track nozzle clogging condition real-time and identify if it is within the acceptable region before any serious 3D printing failure will happen.