Document Type dissertation Author Name Karabelchtchikova, Olga URN etd-121807-234414 Title Fundamentals of Mass Transfer in Gas Carburizing Degree PhD Department Materials Science & Engineering Advisors Richard D. Sisson, Jr., Advisor Diran Apelian, Committee Member Makhlouf M. Makhlouf, Committee Member Satya Shivkumar, Committee Member Yiming Rong, Committee Member Scott A. Johnston, Committee Member Keywords Carburizing Modeling Multi-objective optimization Mass transfer Kinetics Thermodynamics Carbon diffusivity Date of Presentation/Defense 2007-12-18 Availability unrestricted Abstract
Gas carburizing is an important heat treatment process used for steel surface hardening of automotive and aerospace components. The quality of the carburized parts is determined by the hardness and the case depth required for a particular application. Despite its worldwide application, the current carburizing process performance faces some challenges in process control and variability. Case depth variability if often encountered in the carburized parts and may present problems with i) manufacturing quality rejections when tight tolerances are imposed or ii) insufficient mechanical properties and increased failure rate in service. The industrial approach to these problems often involves trial and error methods and empirical analysis, both of which are expensive, time consuming and, most importantly, rarely yield optimal solutions.
The objective for this work was to develop a fundamental understanding of the mass transfer during gas carburizing process and to develop a strategy for the process control and optimization. The research methodology was based on both experimental work and theoretical developments, and included modeling the thermodynamics of the carburizing atmosphere with various enriching gasses, kinetics of mass transfer at the gas-steel interface and carbon diffusion in steel. The models accurately predict: 1) the atmosphere gas composition during the enriching stage of carburizing, 2) the kinetics of carbon transfer at the gas-steel surfaces, and 3) the carbon diffusion coefficient in steel for various process conditions and steel alloying. The above models and investigations were further combined to accurately predict the surface carbon concentration and the carbon concentration profile in the steel during the heat treatment process. Finally, these models were used to develop a methodology for the process optimization to minimize case depth variation, carburizing cycle time and total cycle cost. Application of this optimization technique provides a tradeoff between minimizing the case depth variation and total cycle cost and results in significant energy reduction by shortening cycle time and thereby enhancing carburizing furnace capacity.
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