3D Printed Smart Molds for Sand Casting
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Additive manufacturing, also commonly referred to as 3D printing, stands to transform sand casting with binder jetting technology that can create sand molds with unmatched geometric complexity. With printed sand molds, castings can be optimized with regard to the strength-versus-weight trade-off and structures such as periodic lattices are now available within molds that are not possible with traditional casting technology. However, an increase in design complexity invites more challenges in terms of understanding and managing both the thermodynamics and physics of the casting process. Simulations of castings are more important than ever, and empirical in situ sensor data are required to validate high fidelity computer modeling (e.g., MAGMASOFT®). One novel solution is to leverage the design freedom of CAD-based solid modeling to introduce unique mold features specifically for housing sensors (Internet of Things) within the mold to enable the collection of a diversity of data at manifold locations: temperature, pressure, moisture, gas chemistries, motion of the molds and internal cores (shifting or rotation), and magnetic field. This report describes a proof of concept in which unprecedented levels of process monitoring were integrated—both wirelessly and wired—at strategic locations throughout a printed mold and inside of internal cores. The collected data were used to validate the quality of a casting in situ as well as to provide feedback for optimizing the casting process, mold design, and simulations. A trade-off was explored between sensor survivability and disposability.
Keywords3D printing additive manufacturing electronics sensing simulation
Sand casting is an economical metal forming process that has been employed to manufacture metal objects since the Shang Dynasty of China over 3000 years ago.1 Relative to other forms of casting, sand casting provides a wide range of sizes, complexity, and types of metal alloys. Consequently, the size of the worldwide casting market recently increased to over 100 million metric tons19 with sand casting as the predominant method of casting.24 The growth and importance of this age-old industry require the leveraging of the latest quality and process controls as well as advances in mold, core, and pattern production to meet global demand and to maintain technical vitality.
Additive manufacturing (AM) or 3D printing emerged as a new manufacturing method since the 1980s, but has generally been limited to production of prototypes. However, the benefits of 3D printing for the casting industry were identified early.5 The capability to fabricate complex part geometries using layer-by-layer deposition as opposed to traditional subtractive manufacturing now enables production of molds, cores, and patterns that would be otherwise impossible to create without 3D printing.2 One important use of AM in the casting industry is 3D printed sand molds which provide complex cavities, good dimensional accuracies, the ability to insert components within the casting and/or mold, and an increased freedom in the design of the metal delivery system (gating, sprue, risers, etc.). Sand printers use binder jetting technology to ink jet a binder resin into a catalyst-mixed sand. After printing a layer, a new layer of sand is re-coated over the previous layers and the process repeats until the mold and/or cores are completed. The furan binder chemistry typically used involves a condensation-type curing and cross-linking reaction which are both exothermic and chromophoric. The temperature increases in the mold as it cures are generally less than 20 °C3 which could allow for the survival of electronics or sensors inserted into the mold during printing.
More generally, substantial research has been focused on 3D printed sand molds including the material systems (e.g., binders and silica),7,18,21 properties such as surface finish and porosity,2,15,22 complex multi-material structures,16,17 modeling of the process12 and even sensing in smart sand molds8 in which temperature sensors were inserted into 3D printed sand molds, and the survival and utility of the sensors were evaluated. An entire community has researched ink jetting, the foundational process of binder jetting, and the process is well understood and modeled.6,9,13
Design of an Instrumented 3D Printed Sand Mold
This effort included leveraging an “Internet of Things” strategy for nontraditional sensing of AM-enabled castings (a) in molds and (b) in a core in order to collect data to fuel the analytics necessary to advance in situ evaluation, model validation, and casting qualification. In concert with advances in modeling, the comprehensive collection and integration of process measurements will enable improved simulations, in situ quality control, and possibly expedite the qualification of casting designs and mold printing processes (rather than resource-consuming physical trial-and-error tests). Wired thermocouples have only infrequently been published in research with examples including,4,8,10 but the use of these sensors is common knowledge in the foundry industry to optimize casting processes—albeit not documented in open literature. Alternatively, Bluetooth systems have been improving over the last two decades to the point now that a sensor system with an ARM processor (used in most smartphones as of 2017), a Bluetooth radio, and an arsenal of miniaturized sensors can be now be integrated onto a small printed circuit board that is smaller than a postage stamp. The inevitable marriage of this Internet of Things sensing capability with the ancient art of sand casting has not been reported to the best of the authors’ knowledge and is presented here with a sensor system including 12 degrees of sensing. Specific cavities were included in the molds to integrate sensors and collect high fidelity data including environmental metrics (temperature, pressure, humidity), acceleration, rotation, and magnetic flux.
In-Mold Sensing for Casting Process Simulation Studies (Wired Thermocouples)
in a location where the temperature never exceeds the maximum operating temperature of the circuit (85 °C) and data collection would be continuous,
in a location where the temperature would exceed the operating temperature but not the maximum storage temperature (150 °C) allowing for a short duration of data collection and guaranteeing the survival and recyclability of the circuits, or
in a location where both the maximum operating and storage temperatures would be exceeded but in closer proximity to the cavity providing more direct data acquisition but for only a short period—until the sensor is sacrificed.
The final case would require immediate wireless communication as recovery of the circuits at shakeout would not be possible. However, the data collected could be in difficult-to-reach locations in a mold such as an internal core. The aim of the thermocouple study was to provide the appropriate distances from the cavity to determine the positioning of the wireless sensors.
In-Core Wireless Sensing
three axes of magnetic field,
an inertial measurement unit providing three axes each of rotation and acceleration, and
an environmental sensor with relative humidity, pressure, and temperature.
Among the different types sensors that can be provided in a miniaturized format, linear acceleration and rotation can be used to measure relative motion of mold components including identifying potential core shifts. In situ temperature sensing (or lack thereof) can verify that nearby cavities have been filled with metal as anticipated or identify cold shut defects formed due to excessive heat losses during filling. Electrically conductive fluids, such as molten metal, generate magnetic fields when in motion that can be measured with a magnetometer. Previous studies have focused on the use of static or dynamic magnetic fields to stir molten metal in order to improve metal purity, reduce solidification defects, control grain size, and control crystal orientation.11,20,24 However, another previous study examined the use of a magnetic probe to measure melt velocity and mass transfer.14 As molten metal was passed around a permanent magnetic cylinder, a changing voltage was read and translated into velocity and mass transfer. One potential application of measuring magnetic fields in castings is to provide an immediate and indirect detection of metal in runners—two sensors of which at a known separation could provide an indication of melt velocity.
Results and Discussion
The results of this effort can be separated into two sections:1 the thermocouple comparison with MAGMASOFT® which shows that both physical instrumentation and simulation are necessary to gain a strong understanding of the process physics and2 a demonstration of the diversity of sensor data which can be collected in an internal core with wireless sensors—providing data acquisition, to the best of the authors’ knowledge, never previously available.
Embedded Wired Thermocouples
Bluetooth Sensors Within Difficult-to-Access Cores
Magnetic Field Measurements
This unexpected magnetometer result demonstrates a potential method to instantaneously and indirectly monitor the fill of internal cavities or runners without the delay associated with temperature sensing. Measurements taken as metal passes nearby at two sensor locations of known separation along a mold runner could allow for the calculation of the velocity of the molten metal. By measuring and subsequently optimizing the speed of the metal entering the mold cavity, the quality of the casting could potentially be improved by reducing sand erosion or gas entrapment, the subject of future collaborative work with Guha Manogharan at Pennsylvania State University who identified the concept. Further research is needed to determine if this is related to the motion of the metal front and could be used as an in situ tool for immediately detecting metal in different chambers in the mold. Furthermore, the magnetic field changes that occur over 60 s after the pour completes could possibly provide insights into the solidification process, and this hypothesis is also the subject of future work.
Both pressure sensors registered changes as the metal flowed during the pour and possibly during the immersion of the core itself—after the start of the pour but prior to the complete filling of the risers. As the bottom sensor was surrounded laterally but also from below with molten metal, the pressure reading arrived slightly earlier and reached a higher value of 101 kPa versus 100.5 kPa in the top sensor. The value of pressure sensing in molds or in the core could allow for indirect measurement of the permeability of the bonded sand and the optimization of the process and materials (binder, sand, venting, etc.) by reducing localized high pressures in the sand.
Due to recent technological advancements that are dramatically reducing the size and cost of sensors, integration of high fidelity sensing is inevitable in modern industrial practices and metal casting is no exception. This age-old process stands to benefit from both 3D printing as well as advanced sensing, and in many cases from the introduction of both transformative technologies simultaneously. With today’s wireless sensors, data from deep within molds and difficult-to-access regions are readily obtainable, particularly when paired with the design and manufacturing freedom afforded by 3D printing. This study has demonstrated the utility of leveraging 3D printing to enable the use of sensors which can provide primary data as well as validate complex computer models. This is an early look at how coherent use of advanced manufacturing, simulation, and sensing can revolutionize a steadfast practice.
This research was supported by several institutions. We thank our colleagues from America Makes for partial resourcing from the ongoing Additive Manufacturing for Metal Casting (AM4MC) project. We would like to thank the Friedman Endowment for Manufacturing at Youngstown State University. The Department of Art at Youngstown State University provided the building that houses the foundry that completed all work and we appreciate their involvement. Finally, we thank MAGMA Inc. for the donation of an educational software license and expert advice. All statements of fact, opinion, or analysis expressed are those of the authors and do not reflect the official positions or views of any U.S. Government agency. Nothing in the contents should be construed as asserting or implying U.S. Government authentication of information or endorsement of the author’s views.
Funding was provided by Air Force Research Laboratory (4063.001).
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