DOI: 10.3390/eng7110589 ISSN: 2673-4117

Integrated Statistical Process Control-Based System for Validating Sinter Quality in Pig Iron Production

Viorica Vasilica Toniță, Virgil Gabriel Teodor

In the modern context of industrial practice, optimizing primary metallurgical processes is no longer merely an option for increasing efficiency, but a necessity dictated by stringent sustainability indicators, energy consumption, and cost management. Pig iron production in the blast furnace is a complex, resource-intensive process where raw material quality directly determines the performance of the entire technological flow. Iron ore sinter constitutes the primary component of the blast furnace’s ferrous burden. From an industrial engineering perspective, sinter is not just a simple product with high iron content, but a complex macroscopic system, structurally and chemically optimized to ensure stable and economic blast furnace operation. Studying the actual composition through advanced mineralogical and textural analyses reveals not only the elements present within the sinter, but also the relationships between them. To validate whether the theoretical optimization model functions under real industrial conditions, the implementation of an Integrated Validation System based on Statistical Process Control (SPC) and trend comparison is proposed. The method consists of the following steps: monitoring sinter composition, implementing Statistical Control Charts, calculating control limits, and computing the capability index. Sampling from the sintering batch was carried out from three distinct zones: at the height of the stacks, at their middle, and at their base for sludges and dusts. In contrast, for the sinter, it was performed by selecting three lumps from different zones after cooling. By stabilizing the manner in which blast furnace sludge is reintroduced into the process, without modifying the base sinter recipe, the process capability (Cpk) could be increased from 1.4302 to 2.441, representing an improvement of over 41%. This demonstrates the feasibility of implementing an automated constrained-dosing system for secondary materials.

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