Process planning for multi-axis additive manufacturing
Due to the COVID-19 crisis the PhD defence of Yavuz Murtezaoglu will take place (partly) online.
The PhD defence can be followed by a live stream.
Yavuz Murtezaoglu is a PhD student in the research group Design Engineering (DE). His supervisor is prof.dr. I. Gibson from the Faculty of Engineering Technology (ET).
In recent decades additive manufacturing has transformed from a set of prototyping methods to a mature set of industrial level manufacturing processes. To achieve predictable and high-quality end-use products, these processes require the application of high-quality process planning solutions.
This research questions the common perception that the nature of additive manufacturing processes has led to making process planning for additive manufacturing a trivial step. It is shown that duplicating process planning strategies from subtractive process planning algorithms leads to suboptimal results for their additive counterparts. The main focus of the research is thus the development of multi-axis process planning strategies that take the specific requirements of direct material deposition techniques (FDM, DED) into account.
The research presented in this thesis starts with the state of art on multi-axis additive manufacturing. CNC based subtractive manufacturing strategies and established subtractive process planning steps and terminology are used as a starting point to address the specific challenge of process planning for additive manufacturing. The next chapters describe the development of two novel algorithms for multi-axis additive manufacturing path planning. The first algorithm is based on geometry decomposition that partitions the main geometry into sections with similar functional requirements. Within a partition, material is deposited using constant printing settings, while between the partitions the main deposition direction is optimized. The second algorithm is focused on calculating continuous multi-axis tool paths following the part surface geometry, thus preserving smooth motion of nozzle orientation and collision freeness of the additive manufacturing process. Simulations and physical experiments have been executed to validate the strategies proposed. The developed algorithm for multi-axis additive manufacturing reduced the surface roughness due to stair-case effect by 57% compared to 2.5D AM for the test part used.