Melt turbulence during mold filling is detrimental to the quality of sand castings. In this research study, the authors present a novel method of embedding Internet of Things (IoT) sensors to monitor real-time melt flow velocity in sand molds during metal casting. Cavities are incorporated in sand molds to position the sensors with precise registration. Capacitive and magnetic sensors are embedded in the cavities where melt flow velocity is calculated by using an oscillator, the frequency of which is sensitive to changes in the close field permittivity, and change in magnetic flux, respectively. Their efficiency is investigated by integrating the sensors into 3D sand-printing (3DSP) molds for conical-helix and straight sprue configurations to measure flow velocities for aluminum alloy 319. Experimental melt flow velocities are within 5% of estimations from computational simulations. A major benefit of 3DSP is the geometrical freedom for complex gating systems necessary to reduce turbulence and access to mold volume for sensor integration during 3DSP processing. Findings from this study establish the opportunity of embedding IoT sensors in sand molds to monitor metal velocity in order to validate simulation results (2–5% error), compare gating systems performance, and improve foundry practice of manual pouring as a quality control system.
All Science Journal Classification (ASJC) codes
- Materials Science(all)