Additive Manufacturing proposes innovative directions for high value components and has benefitted from large research efforts for almost all existing industrial sectors. This paper introduces some opportunities and the associated challenges attached to Additive Manufacturing, to produce large metallic components for naval aeronautics and train industries. Two innovative approaches are discussed. Hybrid manufacturing consists in integrating AM together with other processes with the objective to benefit from the interests of each process while avoiding its drawbacks. Finding the optimal manufacturing work plan can be challenging. Twin manufacturing uses models and multiphysics simulation to create a digital clone of the process implementation within its environment. Various configurations and choices can be tested before being selected. The digital twin can also be fed by monitoring data captured during the process. The paper is illustrated with several proof-of-concept parts.
RIVETTE M., HASCOET J.-Y., MOGNOL P., 2007, A Graph-Based Methodology for Hybrid Rapid Design, Proc. Inst. Mech. Eng. Part B J. Eng. Manuf., 221/4, 685–697.
MOGNOL P., RIVETTE M., JEGOU L., LESPRIER T., 2007, A First Approach to Choose Between HSM, EDM and DMLS Processes in Hybrid Rapid Tooling, Rapid Prototyp. J., 13/1, 7–16, doi: 10.1108/13552540710719163.
ISO 14649-1, 2003, Industrial Automation Systems and Integration – Physical Device Control – Data Model for Computerized Numerical Controllers – Part 1: Overview and Fundamental Principles.
ISO 6983-1, 2009, Automation Systems and Integration – Numerical Control of Machines – Program Format and Definitions of Address Words – Part 1, Data Format for Positioning, Line Motion and Contouring Control Systems, http://www.iso.org/cms/render/..., (accessed Feb. 15, 2022).
HASCOET J.-Y., TOUZE S., RAUCH M., 2018, Automated Identification of Defect Geometry for Metallic Part Repair by an Additive Manufacturing Process, Weld. World, 62/2, 229–241, doi: 10.1007/s40194-017-0523-0.
TABERNERO I., CALLEJA A., LAMIKIZ A., LOPEZ De LACALLE L.N., 2013, Optimal Parameters for 5-axis Laser Cladding, Procedia Eng., 63, 45–52, doi: 10.1016/j.proeng.2013.08.229.
ALCACER V., CRUZ-MACHADO V., 2019, Scanning the Industry 4.0: A Literature Review on Technologies for Manufacturing Systems, Eng. Sci. Technol. Int. J., Jan., doi: 10.1016/j.jestch.2019.01.006.
MULLER P., RÜCKERT G., VINOT P., 2019, On the Benefits of Metallic Additive Manufacturing for Propellers, Sixth International Symposium on Marine Propulsors smp’19, Rome (Italy), p. 8.
RYCKELYNCK D., CHINESTA F., CUETO E., AMMAR A., 2006, On the a Priori Model Reduction: Overview and Recent Developments, Arch. Comput. Methods Eng., 13/1, 91–128, doi: 10.1007/BF02905932.
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