Data-Driven Mine Production Control Based on Measurement-While-Drilling

Drilling and blasting are critical within the mining industry and affect subsequent operations including milling, and can therefore limit the competitivity of a mine. Ideally, upon blasting, the valuable rock (a.k.a. the ore) should land
in piles that are distinct from the piles of waste rock. However, some waste rock is inevitably mixed with the ore due to suboptimal blasthole drilling and explosive charging, suffering from uncertainty of the target rock composition. The energy that is expended on processing waste rock, due to ore dilution, is significant. This project is to decrease the uncertainty in the target rock composition, by extending the capabilities of Measurement-While- Drilling (MWD) technology, which consists of sensors that are attached to the drills, and data processing algorithms that interpret the data. The MWD information is used to avoid ore dilution, and more generally to better inform the downstream processes, in what is known as drill-to-mill integration.

Faculty Supervisor:

Alessandro Navarra

Student:

Partner:

Peck Tech

Discipline:

Engineering

Sector:

Professional, scientific and technical services

University:

McGill University

Program: