Data-Driven Dynamic Simulations of Gold Extraction Which Incorporate Head Grade Distribution Statistics

Round 1

Reviewer 1 Report

This study applies data-driven simulation modeling, to represent standardized operational modes and their impact on gold extraction operational performance. This demonstrates the data-driven incorporation of gold head grades into the DES/DRS framework developed to represent the operations at Minera Florida. This research confirms that the critical variable Target Ore Stockpile Level is crucial in maximizing gold head grades and tonnage. The study topic is interesting and important. There are some revisions should be made as following:

1、P531, “High values may arise because of sampling errors or reflect distinct geological sub-environments or domains within a mineral deposit”, When eliminating outliers, whether the cause of high values is considered?

2、P597，How to reflect the accuracy of the discrete rate simulation and the consistency with the actual production results of the Minera Florida Cyanidation Process.

3、P692，Figure 11(a), the ore 2 Stockpile Level exceeds the total ore Stockpile Level. Please verify whether the data is correct and whether it has some impacts on results, and make necessary supplements.

4、The format of tables in the article is different, and should be unified according to the requirements of the journal.

The author cites references in the abstract and conclusion of the paper. This is not always necessary and the expression should be optimized.

Author Response

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Author Response File: Author Response.pdf

Reviewer 2 Report

The article illustrates a data-driven method for improving the process efficiency in a gold extraction operation. Based on the model analysis ore stockpile played a critical role in the performance of the operation. The probabilistic model is able to predict and take the right decisions based on the available data. 

The authors have included the necessary citations in the introduction section.

The materials and methods section needs improvement. The authors have explained a lot about the various statistical methods that have been employed in the article. However, they are well-known and do not add value to the overall readers. It would be useful if the authors can explain how these methods are suitable in the current scenario. What are alternative methods of evaluation available and how do the current methods give better analysis based on the available data?

Author Response

Please see the attachment.

Author Response File: Author Response.pdf

Round 2

Reviewer 2 Report

The authors have implemented the changes as advised by the reviewers. This article can be published in its current form.

Congratulations.