In situ measurement of granular pressure and velocity on component surfaces in stream finishing

In situ measurement of granular pressure and velocity on component surfaces in stream finishing
Title:
In situ measurement of granular pressure and velocity on component surfaces in stream finishing
Other Titles:
Advanced Surface Enhancement
Publication Date:
31 August 2019
Citation:
Itoh S., Ho J., Turangan C., Wan S. (2020) In Situ Measurement of Granular Pressure and Velocity on Component Surfaces in Stream Finishing. In: Itoh S., Shukla S. (eds) Advanced Surface Enhancement. INCASE 2019. Lecture Notes in Mechanical Engineering. Springer, Singapore
Abstract:
Stream finishing, one of the fast mass finishing processes that enables a ma-terial removal rate up to 500 μm/h, is a candidate for the post processing method for external surfaces of additively manufactured (AM) components. The problem here is non-uniform material removal (MR), which is probably caused by a conventional method of rotating target components 360o in a stream finishing bowl. Our plan is to control the component orientations and toolpath depending on each geometry. In order to consider the optimized toolpath, MR simulation is a promising tool. This study focuses on in situ measurement of process values around the target components, which are es-sential for modelling the granular flow. We measured the pressure and veloc-ity on components surfaces using prototyped tools submerged in the stream finishing media. As a result, the measured pressure increased with the sub-mersion depth, and reached 0.05 MPa at a depth of 250 mm. Regarding the contact angle, the pressure reached maximum in the normal direction toward media flow. The media motion on the surface was successfully tracked using a transparent container. The measured velocity reached maximum when the surface is parallel to media flow. Using these acquired pressure and velocity, a simple estimation of MR was conducted using Preston’s law, and agreed with the experimental result. The measured values will enable the calibration and validation of the simulation model, which can be used for the future toolpath prediction.
License type:
PublisherCopyrights
Funding Info:
This research is supported by core funding from Advanced Remanufacturing and Technology Centre (ARTC) and Institute of High Performance Computing (IHPC).
Description:
This is a post-peer-review, pre-copyedit version of an article published in Advanced Surface Enhancement. The final authenticated version is available online at: https://doi.org/10.1007/978-981-15-0054-1_23
ISSN:
978-981-15-0053-4
978-981-15-0054-1
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