Optimization of Sandblasting Process of Complex 3D Surface Polishing Using Variable Viscoelastic Diamond Abrasive Particles
- Junghua Tung, Chengshun Chen, Wenyu Zhao, Cher-Ming Tan
- Corresponding Author
- Junghua Tung
Available Online May 2018.
- https://doi.org/10.2991/amcce-18.2018.65How to use a DOI?
- Sandblasting Process, Polishing, Abrasive Particles, Workpiece Surface, Taguchi Method
- This paper reports a type of abrasive polish method. Controlling the environmental aqueous rust inhibitor content can change its viscoelasticity to adhere diamond particles on polymer materials. Using the sandblasting mechanism, the elastic abrasive with fine diamond particles adhered to them collides with the workpiece. The abrasive particles deform and slide on the workpiece surface, so that the diamond particles on the abrasive surface can cut onto the surface peak of the workpiece. Thus, the surface of the material with complicated morphology can be rapidly and precisely polished. The friction generated by the abrasive on the surface of the workpiece will cause the rust inhibitor solution to evaporate, resulting in reduced viscosity, leaving the diamond particles to gradually fall off from the abrasive. Applying the Taguchi method, the robust parameters for viscosity and injection angle were identified. The surface roughness of the tooling steel by using the identified parameters was found to decrease from Ra=1.47μm to Ra=0.2μm in 3 minutes. Its polishing application for inner angle and inside curved face of the two different die materials has 40 times higher efficiency as compared to the traditional polishing process.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
TY - CONF AU - Junghua Tung AU - Chengshun Chen AU - Wenyu Zhao AU - Cher-Ming Tan PY - 2018/05 DA - 2018/05 TI - Optimization of Sandblasting Process of Complex 3D Surface Polishing Using Variable Viscoelastic Diamond Abrasive Particles BT - 2018 3rd International Conference on Automation, Mechanical Control and Computational Engineering (AMCCE 2018) PB - Atlantis Press SN - 2352-5401 UR - https://doi.org/10.2991/amcce-18.2018.65 DO - https://doi.org/10.2991/amcce-18.2018.65 ID - Tung2018/05 ER -