Continuous casting is a crucial step in the production of a variety of steel products. Its performance is measured in terms of conflicting objectives including productivity, yield, quality and production costs. These are conflicting in the sense that, if the productivity is increased, there is a reduction in other performance parameters. These performance parameters are greatly influenced by operating conditions such as casting speed, superheat, mold oscillation frequency, and secondary cooling conditions. An optimized solution for continuous casting process can be obtained. However uncertainty in operating parameters which affects the performance of caster is rarely considered. Moreover, the solution obtained is optimal with respect to a particular performance measure and does not provide a balance between all. In this paper an integrated design framework has been developed based on metamodels and the compromise Decision Support Problem (cDSP). The framework developed deals with uncertainty and yields robust solutions for performance measures. Further, the design space for continuous casting has been explored for different scenarios to determine satisficing solutions. The utility of the framework has been illustrated for providing decision support when an existing configuration for continuous casting is unable to meet the requirements. This approach can be instantiated for other unit operations involved in steel manufacturing and then may be integrated to simulate the entire production cycle of steel manufacturing. This in turn will enable development of materials with specific properties and reduce the time and cost incurred in the development of new materials and their manufacturing.

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