Making Industrial Processes More Cost Efficient
Most steel plants are interested in ways to influence the sinter quality. Sinter quality consists of several variables, the measurements of many of which are time consuming. Mathematical models can provide an alternative to frequent measurements of such variables, as well as provide a means of influencing those quality variables. In some plants, sulphur dioxide emissions are also an issue, and they too can be taken into account.
Proportioning of iron ore is the key to getting desired sinter properties, but sintering process variables also matter. The amounts of iron ores, coke, limestone, dolomite and returned sinter, besides particle sizes, temperatures, residence times and bed height determine the sinter quality. If the iron ore composition varies a lot, the composition may also be taken into account. Sinter properties like tumbler strength, reducibility index, reduction degradation index, etc. can be predicted in advance by the advanced mathematical models. The models take into account production data as well as the knowledge of the sintering process. The production unit needs to provide us some amount of production data in terms of the variables that they want us to include in the models.