Applying probabilistic material flow analysis for quality control and management of waste recycling in steelmaking.

In modern steelmaking, multiple processes comprise a continuous manufacturing system, but not all phosphorus content data are connected or integrated into a holistic and systematic database. Disconnected data hinder the improvement of material management and resource efficiency in the industry. The objective of this study was to establish a method to evaluate material flows, reduce uncertainty, and perform quality control for waste recycling in the steelmaking industry. The results indicate that 10% of the phosphorus input is present in the final products, 30% accumulates in the slags, and more than 60% of the total mass remains in the processes. Comparing the material flow analysis results obtained using static and probabilistic approaches, the partition ratio of the phosphorus content in slags changes from 24.07% to 40.78%, but that in processes changes from 49.10% to 68.05%. This indicates that the variations in phosphorus content in slags and processes might affect the effectiveness of slag recycling and might increase the resource consumption required to maintain the quality of final products. The probability of forming substandard products in the baseline scenario is 0.43. Adopting a 50% removal rate, the probabilities of forming substandard products are reduced to 0.36 (waste removal scenario), 0.38 (slag reduction scenario), and 0.31 (raw material treatment scenario). The performance of raw material treatment and waste removal is more efficient for quality control. The method used in this study can be applied to evaluate the possible outcomes of waste recycling and reduce the probability of forming substandard products.