Lightweight Mesh File Format Using Repetition Pattern Encoding for Additive Manufacturing. (December 2020) - Vaissier, Benjamin; Pernot, Jean-Philippe; Chougrani, Laurent; Véron, Philippe
Abstract: To facilitate the transfer, storage and manipulation of intricate parts' geometry whose fabrication has been made possible thanks to the rise of Additive Manufacturing (AM) technologies, an encoding framework reducing the resulting file size has been developed. This approach leverages the fact that many AM parts are presenting repetition patterns, by encoding the repetition of similar geometry chunks. The decomposition of the part into chunks is a complex optimization problem, whose identification as a Weighted Exact Cover (WEC) problem allowed to develop a new heuristic algorithm dedicated to its fast resolution in linear time O ( n ) . The encoding strategy is implemented through a variation of the AMF file standard (for quick adoption of the format by existing software), and also through a new ad-hoc hybrid file format. To demonstrate the efficiency of the approach, the encryption of lattice and support structures through these two encoding strategies are compared to the results of several state-of-the-art encoding approaches. The way this data weight lightening strategy preserves the overall accuracy is discussed while considering different floating points encoding precisions with respect to the AM process requirements. This comparison exhibits file size reductions up to -84% in comparison with file sizes generated by state-of-the-art approaches. Not only the proposed repetition pattern encoding framework allows file size reductions, but it could also be exploited to optimize and speed-up some steps of the Product Development Process (PDP), including process planning phases. Graphical abstract: Highlights: A framework for the compressed encoding of AM mesh files is proposed. This framework exploits the repetition patterns present in many AM geometries. The Weighted Exact Cover problem behind this optimization is formalized. An efficient heuristic algorithm is developed and detailed for its resolution. mpression performances are compared to state-of-the-art approaches.