1:40 p.m. - 2:20 p.m.
Paper No. 16: Investment Castings with Unique Levitation Melting Technology FastCast Dr. Sergejs Spitans, ALD Vacuum Technologies, Booth 202 Crucible-free Levitation Melting (LM) and single-batch casting of titanium alloys (e. g. for turbocharger impellers up to 500 g) has many advantages over multi-piece casting from ceramic- or Cold-Crucible (CC) induction furnaces.
First of all, electromagnetic (EM) levitation prevents contamination of the melt with the crucible material and results in a superior and reproducible quality of alloy. Heat losses from the liquid metal are reduced and limited to radiation and evaporation that permits fast melting and high overheating at much higher thermal efficiency. Additionally, contact-free single-shot casting of the levitated melt can be precisely controlled by the current in the inductor. Apart from that, the new method breaks down the statistical nature of a single product quality in case of a multi-piece casting and advances production to the “one-piece-flow” concept.
A novel method for the large-scale LM of metals is developed to transfer this technology from lab use into industrial sphere. Numerical simulation has been used to verify the new method and to design a pilot LM furnace capable for a contact-less melting of metallic samples with increased weights. The designed prototype has been successfully validated by experiments with Ti-6-4 and other alloys up to 500 g.
This presentation gives an update on recent achievements to the FastCast demonstrator which is in operation at ALD.
2:20 p.m. - 3:00 p.m. Paper No. 17: Analysis of Thermal Distortion Data to Detect Issues in Investment Shell Materials Dr. Sam Ramrattan, Western Michigan University This paper investigates the capability of monitoring investment shell materials using TDT data. TDT is considered for this purpose because it provides coupled thermal-mechanical investment shell behavior at head pressures and temperatures that can be adjusted to represent actual casting scenarios. TDT produces a high-dimensional dataset, as it produces multiple time-series profiles, referred to as thermal distortion curves (TDCs). In order to effectively use this dataset, this paper will incorporate multivariate statistical analysis for process monitoring. The proposed monitoring scheme will be demonstrated through a case-study. The ability of the proposed monitoring scheme to detect the shift from one investment shell system to another will be determined.
3:00 p.m. - 6:00 p.m. EXPOSITION 6:30 p.m. - 8:00 p.m. EVENING RECEPTION
October 2021 ❘ 25 ®
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