O. K. Rowan, Caterpillar, Inc., Mossville, IL; R. D. Sisson, Worcester Polytechnic Institute, Worcester, MA
A methodology for optimization of the gas carburizing heat treatment in terms of cost, cycle time and quality of the carburized parts has been developed. The optimization strategy is based on 1) modeling the effect of process parameters (carbon potential, temperature and time) on the mass transfer coefficient and carbon diffusivity in austenite; 2) correlating the observed variations in the process parameters on the kinetics of carburizing; and 3) developing a robust multi-objective optimization technique to achieve the desired case depth with minimum cost and minimum case depth variation. The index of performance for the process optimization involves both the surface carbon concentration and the case depth. While the first parameter depends on accurate control of the atmosphere and the carbon potential in the furnace, the case depth is primarily influenced by the furnace temperature and the duration of the carburizing process. The application of this optimization technique provides a tradeoff between minimizing the case depth variation and the total cycle cost and results in significant energy reduction by shortening cycle time and thereby enhancing furnace capacity.
Summary: A methodology for optimization of the gas carburizing heat treatment in terms of cost, cycle time and quality of the carburized parts has been developed. The optimization strategy is based on 1) modeling the effect of process parameters (carbon potential, temperature and time) on the mass transfer coefficient and carbon diffusivity in austenite; 2) correlating the observed variations in the process parameters on the kinetics of carburizing; and 3) developing a robust multi-objective optimization technique to achieve the desired case depth with minimum cost and minimum case depth variation. The index of performance for the process optimization involves both the surface carbon concentration and the case depth. While the first parameter depends on accurate control of the atmosphere and the carbon potential in the furnace, the case depth is primarily influenced by the furnace temperature and the duration of the carburizing process. The application of this optimization technique provides a tradeoff between minimizing the case depth variation and the total cycle cost and results in significant energy reduction by shortening cycle time and thereby enhancing furnace capacity.
