How it works
Data Analysis using AI
SmartDIL collects and normalizes historical site data. Examples include dimensions, rock type, drilling-and-blasting, etc.
After planning your stope, you will simply input the parameters and SmartDIL will predict the dilution of the planned stope based on the extensive collected data.
Using an easy-to-use web interface, you can modify the parameters and SmartDIL will give you an instant analysis of the planned stope’s dilution.
You can now adjust the planned stope according to the new parameters and perform drill-and-blast.
Add to Secure Database
All the new results from the blasted stope will then be input in a secure database, which will be used for the next stope planning.
Interested in learning more about dilution from experts? Check out the latest episode on The Mining Experience where Mr. Yvan Dionne and Mr. Kilian Bao discuss the importance of underground mining dilution and how to effectivley manage it to reduce on costs.
Interseted in learning how to use SmartDIL? The SmartDIL Webinar Recording is now available! Click the video below to watch the full presentation.
How long does the process take?
Achieving a level of complete automation with minimal manual intervention can take up to 6 months, due to the learning curve of the AI based on stope data.
Once this level is achieved, AI will be completely integrated into the underground mine design and no longer considered as a separate technology.
This system is not static, giving you the value of improved processes that will allow you to improve dilution control continuously based on new insights.
What are the advantages of SmartDIL?
Web application – can be setup online and accessed from anywhere
No expensive equipment needed.
No need much experience in AI knowledge, the program takes care of that!
No need to assign others who work in other domains and are outside of this project’s domain. One key employee is needed to input the data and interpret the output.
More productivity. Eliminate time-consuming and repetitive tasks done by humans. New insights generated by the AI allows for better decision-making.
Environmental sustainability. Less dilution = Less hauled tonnage = Less equipment fuel and wear.
Continuous improvement. By continuously collecting stope data, the AI gets better over time.
The main parameters influencing the accuracy of the prediction:
The number of mined sites given to AI. This can be related to the number of stopes as well as the accuracy of the results of each mined stope.
The other parameters having an influence (not necessarily in this order):
Quality of the extracted data.
Site with similar properties.
Adjustment of the weight of certain parameters by the users.
Varieties of extracted data: blasting data, geological data, field support, etc.
The accuracy of the prediction will be greater with a greater number of mined sites.
The accuracy of the prediction can be represented with the following curves :