Abstract
Accurate and efficient identification of failure features of returned used mechanical components/parts is the prerequisite for adaptive remanufacturing. However, due to part-to-part variation, it is error-prone and ad-hoc to manual inspect each part with various defects. This paper proposes a failure feature identification method for adaptive remanufacturing. An innovative identification algorithm is developed to quickly identify the failure features which integrates point-clouds generation, fine-registration and Boolean calculation. For the identified features, hybrid tool path for adaptive remanufacturing can be generated automatically. A turbine blade is taken as an example to demonstrate the efficiency and reliability of the proposed method.
| Original language | English |
|---|---|
| Title of host publication | Procedia CIRP |
| Publisher | Elsevier |
| Pages | 552-556 |
| Number of pages | 5 |
| Volume | 90 |
| DOIs | |
| Publication status | Published - 6 Aug 2020 |
Publication series
| Name | Procedia CIRP |
|---|---|
| Publisher | Elsevier |
| Volume | 90 |
| ISSN (Print) | 2212-8271 |
Keywords
- Adaptive remanufacturing
- Failure feature
- Hybrid tool path
- Identification
- Point-clouds
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Yan Wang
- School of Arch, Tech and Eng - Professor of Circular Manufacturing
- Communication and Creative Ecologies Research Excellence Group
- Design for Circular Cities and Regions (DCCR) Research Excellence Group
- Advanced Engineering Centre
Person: Academic