This paper is motivated by a need identified by steel makers, namely, the need to produce steel products with new and often more stringent set of specifications and enhanced performances (such as fatigue life and corrosion behavior) using existing equipment cost-effectively.
Manufacturing a steel product involves series of unit operations, each having a significant bearing on the properties of the end product. This paper focuses on studying the effect of one such unit operation, namely, ladle refining. The performance like corrosion behavior and fatigue life and properties of advanced high strength steel are greatly influenced by its cleanliness and by maintaining composition within specified bounds. Cleanliness of steel is assessed in terms of the count and nature of inclusions present and the levels of tramp elements such as sulfur, phosphorus and total oxygen present in the liquid steel. The desired composition is maintained with respect to alloying elements (Ni, Cr, Mn, etc.) that are added to impart certain properties to the steel. The ladle furnace is one of the key unit operations for carrying out deoxidation and desulfurization to maintain the levels of oxygen and sulfur within a tolerable limit. Deoxidation reaction during refining lead to formation of a number of which are deleterious in nature and should be removed. The effectiveness of the ladle operation is thus influenced by conflicting goals such as inclusion removal efficiency, desulfurization and the cost of refining.
George Box is reputed to have observed that all models are wrong and some are useful. In keeping with George Box’s observation we suggest that our challenge is to determine the set points for the ladle unit operation using computational models that at best capture the essence of reality but not reality itself. Therefore, the need is to find solutions that are relatively insensitive to the inherent uncertainties embodied in the computational model while satisficing the conflicting goals.
In this paper we present a method for visualizing and exploring the solution space using the compromise Decision Support Problem (cDSP) as a decision model. We illustrate the efficacy of our method, for use by steel producers, by determining the set points for a ladle, in an industrial setting.