Multi-physics modeling of induction-based additive manufacturing of metals
The shift towards 3D printing of functional products has provided a glimpse of the future in terms of manufacturing technologies and the creation of volumetrically complex structures made possible only through these technologies. 3D printing has emerged from the culmination of several technologies covering multiple industries and a myriad of materials. Unlike subtractive technologies such as mills, lathes and CNC machines, where material is removed from a bulk slab or billet to produce a desired part, 3D printing uses an additive layered approach to deposit material based on cross sections of the desired part. Both approaches produce parts based on 3D models created with Computer Aided Design (CAD) software such as SolidWorks®. The advantages of an additive approach are numerous and include part geometries which are impossible with subtractive technologies, less material waste, and often significantly less energy requirements. Disadvantages include low production rates, often less than functional materials, and poor precision compared to traditional technologies. Additive processes also tend to require more specialized raw materials than do subtractive technologies. Despite the disadvantages, the growth of 3D printing is driven by market demand from business sectors such as aerospace, medicine, automotive, and consumer electronics, and there is a strong industry effort to address the short-comings of the additive approach. Materials for the 3D printing of functional parts fall primarily in two categories: polymers and metals. For polymers, Selective Laser Sintering (SLS), Stereolithography (SL), and Fused Deposition Modeling (FDM) are the most common 3D printing technologies. For printed metals, Electron Beam Melting (EBM®), Laser Engineered Net Shaping (LENS® ), and Direct Metal Laser Sintering (DMLS) are the most common. 3D Metals machines tend to be extremely expensive and are typically found only in well-funded research centers, defense contractor R&D departments, and government laboratories. Since the strength of the U.S. economy has been shown to be largely dependent on the success of small businesses, there is clearly a need for a lower cost entry level technology that will enable competitive 3D metals processing by common machine shops and parts fabrication facilities. The work presented in this thesis is focused on basic modeling of a proposed induction-based technology for metals printing that shows promise for a lower cost system that could see widespread use in machine shops around the world. Induction heating involves the creation of intense resonant magnetic fields which induce alternating eddy currents within conductive materials found in close proximity. These induced eddy currents produce Joule heating within the conductive body proportional to the material’s temperature-dependent resistivity and the square of the frequency-dependent current density. The use of induction technology for heating and even melting metals has been around for nearly a century. The basic principle behind induction heating was discovered by Michael Faraday nearly two centuries ago. The concept proposed in this thesis involves adapting and controlling induction heating technology to heat metal alloy filaments to a point between the solidus and liquidus states (a semi-solid state) whereby the metal filament becomes soft and can be laid down in a predictable, well-behaved manner and then be brought to a low melting point for consolidation with previously deposited layers. The thesis covers an introduction to the basics of induction heating including historical contributions and a discussion of relevant theory from electromagnetics and thermodynamics. Relevant numerical methods are presented, along with some initial ideas about applying the technology to an additive deposition process.
Computer Engineering|Electrical engineering
Muse, Danny W, "Multi-physics modeling of induction-based additive manufacturing of metals" (2012). ETD Collection for University of Texas, El Paso. AAI10118143.