Wire arc additive manufacturing of an aeronautic fitting with different metal alloys: From the design to the part. (April 2021) - Suárez, Alfredo; Aldalur, Eider; Veiga, Fernando; Artaza, Teresa; Tabernero, Iván; Lamikiz, Aitzol
Graphical abstract: Highlights: WAAM manufacturing steps from a CAD model to the final geometry of the part. Optimal deposition parameters and mechanical properties for four metallic alloys. The WAAM process reduces the component buy-to-fly ratio, rationalizing resource use. A monitoring method is developed to obtain a unique fingerprint of each part. A matrix manufacturing strategy is used to increase the productivity of the process. Abstract: WAAM (Wire Arc Additive Manufacturing), an additive manufacturing technology with high deposition rates, can produce metallic components, layer by layer, from different alloys, yielding high mechanical performance. Customized AM machines with monitoring and control systems are necessary to facilitate automated manufacture of different types of components through WAAM technology. In this paper, a methodology for the validation of additive manufacturing is presented as an alternative to industrial machining, for the manufacture of medium-sized aeronautical parts. To begin with, the most appropriate welding technology and adequate parameters for four different metal alloys are selected. Successively, a characterization wall is manufactured with each of the four metal alloys, for metallographic and mechanical characterization, concluding that the material deposited utilizing the WAAM process is adequate for the fabrication of medium-sized aeronautical parts. Consecutively, machine paths are defined under conditions that consume the least possible amount of material for the manufacturing of the aeronautical part. Several aspects -manufacturing times, deposition rate, material efficiency ratio- of each component are then analyzed, relating them to the properties obtained in each alloy. The manufacturing process is supervised and controlled by online monitoring. The novelty of this paper consists in establishing unique dataset for each component that is defined as a unique additive manufacturing Fingerprint as baseline for in process defect detection. Finally, the unique contribution of stablishing a matrix-strategy for the manufacture of multiple parts with the same tooling to optimize the use of resources is presented.