Abstract
Metallic components can gain defects such as dents, cracks, wear, heat checks, deformation, etc., that need to be repaired before reinserting into service for extending the lifespan of these parts. In this study, a hybrid process was developed to integrate reverse engineering, pre-repair processing, additive manufacturing, and material testing for the purpose of part remanufacturing. Worn components with varied defects were scanned using a 3D scanner to recreate the three-dimensional models. Pre-repair processing methods which include pre-repair machining and heat-treatment were introduced. Strategies for pre-repair machining of defects including surface impact damage, surface superficial damage and cracking were presented. Pre-repair heat-treatment procedure for H13 tool steel which was widely used in die/mold application was introduced. Repair volume reconstruction methodology was developed to regain the missing geometry on worn parts. The repair volume provides a geometry that should be restored in the additive manufacturing process. A damaged component was repaired using the directed energy deposition process to rebuild the worn geometry. The repaired part was inspected in microstructure and mechanical aspects to evaluate the repair. The hybrid process solved key issues associated with repair, providing a solution for automated metallic component remanufacturing.
Recommended Citation
X. Zhang et al., "A Hybrid Process Integrating Reverse Engineering, Pre-Repair Processing, Additive Manufacturing, and Material Testing for Component Remanufacturing," Materials, vol. 12, no. 12, MDPI AG, Jun 2019.
The definitive version is available at https://doi.org/10.3390/ma12121961
Department(s)
Mechanical and Aerospace Engineering
Research Center/Lab(s)
Intelligent Systems Center
Keywords and Phrases
Additive manufacturing; Component remanufacturing; Hybrid process; Material testing; Reverse engineering
International Standard Serial Number (ISSN)
1996-1944; 1996-1944
Document Type
Article - Journal
Document Version
Final Version
File Type
text
Language(s)
English
Rights
© 2019 The Author(s), All rights reserved.
Creative Commons Licensing
This work is licensed under a Creative Commons Attribution 4.0 License.
Publication Date
01 Jun 2019
Comments
This research was funded by National Science Foundation, grant number CMMI-1547042 and CMMI-1625736.