Technical paper: SAG Mill Design and Benchmarking Using Trends in the JKTech Database

28 Sep 2023

Senior Process Specialist Tim Vizcarra examines the structure of JKTech's autogenous and semi-autogenous (AG/SAG) mill specific energy model in a new paper produced for the SAG23 Conference


JKTech maintains a large database of comminution circuit data acquired from detailed surveys of grinding circuits in operations all over the world. Traditionally, this database has been used for internal benchmarking of projects against similar reference sites, as well as for validating the simulation outputs of the population-balance comminution models in JKSimMet. This has been undertaken with the use of power-based models regressed against the data, the forms of which have evolved over the years as the database has grown in size, and which delineate the underlying patterns otherwise camouflaged in the noise and variability of the dataset.

This paper presents the structure of the latest version of the JKTech autogenous and semi-autogenous (AG/SAG) mill specific energy model, which is an adaptation of that previously proposed by Morrell. While Morrell’s model is well-known, historical publications have not provided insight into its behaviour or the trends that it predicts. These are described in this paper, where complex interactions between key feed, design, and operational variables that may not necessarily be evident in datasets of full-scale mills in production duty, are illustrated. The model's application in greenfield design scenarios and benchmarking of existing mills is demonstrated with a number of case studies.


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