Title
Applications of a Hybrid Manufacturing Process for Fabrication and Repair of Metallic Structures
Abstract
Since its appearance, rapid prototyping technology has been of interest to various industries that are looking for a process to produce/build a part directly from a CAD model in a short time. Among them, the direct metal deposition process is the only process which directly manufactures a fully dense metal part without intermediate steps. However, challenges of the direct metal deposition process include building overhang structures, producing precision surfaces, and making parts with complex structures. Coupled between the additive and the subtractive processes into a single workstation, the integrated process, or hybrid process, can produce a metal part with machining accuracy and surface finish. Therefore, the hybrid process is potentially a very competitive process to fabricate and repair metallic structures. This paper summarizes the current development of the hybrid process to process high temperature metallic materials, including tool steel and Ti64. Research in simulation and modeling, process development, and actual part building and repair are discussed.
Recommended Citation
F. W. Liou et al., "Applications of a Hybrid Manufacturing Process for Fabrication and Repair of Metallic Structures," Proceedings of the 17th Annual Solid Freeform Fabrication Symposium (2006, Austin, TX), pp. 1-11, University of Texas at Austin, Aug 2006.
Meeting Name
17th Annual Solid Freeform Fabrication Symposium, SFF 2006 (2006: Aug. 14-16, Austin, TX)
Department(s)
Mechanical and Aerospace Engineering
Second Department
Materials Science and Engineering
Research Center/Lab(s)
Intelligent Systems Center
Keywords and Phrases
Hybrid Process; Metal Deposition Processes; Multi-Axis Capability; Rapid prototyping
Document Type
Article - Conference proceedings
Document Version
Final Version
File Type
text
Language(s)
English
Publication Date
16 Aug 2006
Comments
This research was supported by the National Science Foundation Grant Number DMI-9871185, the grant from the U.S. Air Force Research Laboratory contract # FA8650-04-C-5704, and UMR Intelligent Systems Center. Their support is greatly appreciated.