/ machine learning

Using Machine Learning to Make Blasting Design Cheaper, Faster, and More Intelligent

In the USA, there are over 14,000 mines and quarries. The first step in this large supply chain is the drilling & blasting design. Every day, planning at least a week ahead, mines and quarries managers decide where to blast. The blasting engineer has the responsibility of setting the parameters for a safe and productive blast. Is there a way to make blasting design cheaper, faster, and more intelligent? The answer is YES!

This blog post is the first of a series of posts on how technologies can change blasting design for the better. The following is a depiction of the traditional blasting design workflow:

1_2

2_2

The traditional blasting design process is time-consuming and costly. It involves the blasting engineer going back-and-forth to manually input data and edit the design. Further, experience accumulated from each blast is difficult to quantify or transfer. With the help of drones, smart drills, and machine learning, mines and quarries can complete the process of blasting design within two hours, automatically prepare for blasts, and learn from the result of each blast to better predict the next one, all with around $20,000 of equipment and software investment.

3_1

Let us conclude with a comparison between the traditional, manual blasting design process and the cutting-edge, future blasting design process:

4_2

In the next three blog posts, we will dig deeper into the advantages of smarter technologies and discuss separately how mining and construction companies can save cost, speed up the blasting design process, and more effectively learn from prior blasts. Stay tuned!

Headline Photo by Shane McLendon / Unsplash