Key Takeaways

  • Blast sequencing and timing design live inside broader blast-design suites: Orica BlastIQ and Deswik.Blast.
  • BlastIQ is a cloud platform for storing, managing and sharing blast-related information. It gives quality-control visibility over blast design and execution rules.
  • Marked “Emerging”: sequencing modules exist inside mature commercial suites. However, AI-driven optimization of sequence and timing (versus digitizing existing manual practice) is still a developing capability.
  • BlastIQ has documented API integration with Deswik.Ops, so these tools are not necessarily either/or. They are increasingly interoperable.

TL;DR

Blast sequencing with AI starts by moving your timing designs and execution records into a cloud platform like Orica BlastIQ or Deswik.Blast. Next, link each design to its measured fragmentation and movement. Only then can a model learn which delay timings work best for your rock.

What Is Blast Sequencing?

Blast sequencing is the order and timing in which individual blast holes detonate. Holes in a production blast do not fire at once. Instead, delays of a few milliseconds separate them, so each hole breaks rock toward a free face created by the holes before it.

The sequence shapes almost every blast outcome. It controls the direction rock moves and how the muckpile forms. Fragmentation depends on it too, because well-timed holes give rock room to break. Timing also limits ground vibration, since spreading detonations over time reduces the charge firing in any single instant. Electronic detonators made precise, programmable timing practical, which opened the door to data-driven sequence design.

How Do I Optimize Blast Sequencing With AI?

The path runs in three steps: digitize the workflow, connect it to your planning stack, then add the optimization layer.

Digitizing blast sequencing data

Traditionally, experienced blast engineers designed sequences using rules of thumb. They then had limited visibility into whether the plan was actually followed on the bench. Digitizing this workflow is what is happening now. It is also the necessary foundation for any future AI-driven sequence optimization.

Orica BlastIQ is the clearest example. It stores, manages and shares all blast-related information. As a result, engineers get systemized control over design and loading rules, plus better visibility of execution on the bench.

Connecting sequencing to your planning stack

BlastIQ exposes API endpoints. Mining teams have used these to connect it to their own planning and reporting systems, including Deswik.Ops. Therefore, it is designed to sit inside a broader digital mine-planning stack rather than as an isolated silo. Deswik.Blast offers a comparable sequencing capability within the wider Deswik suite. Sequencing also works best when it is set alongside the pattern itself during blast design optimization.

Adding AI to blast sequencing decisions

AI enters in the optimization layer on top of the captured data. It uses historical fragmentation and movement outcomes to learn which sequences and delay timings produce the desired fragmentation and dig-ability for a given rock mass. Those outcomes come from blasting evaluation after each shot. This loop is real but still maturing across the industry.

Why Blast Sequencing Is Still Emerging

We flag this area “Emerging” rather than “Yes” for a clear reason. The data infrastructure is mature. However, closed-loop AI optimization on top of it is not yet standard practice everywhere.

In practice, most sites need several steps before AI adds value. First, they must record the timing actually fired for every blast. Next, they must measure fragmentation and movement consistently. Finally, they need enough blasts in similar rock to separate the effect of timing from geology. Until then, expect digital sequencing tools to improve control and visibility more than they optimize outcomes.

FAQs

What does blast sequencing control?

Blast sequencing controls the order and delay timing of hole detonations. That affects rock movement direction, muckpile shape, fragmentation and ground vibration. Small timing changes can noticeably alter the result.

Can AI design blast sequencing today?

Partly. Commercial suites such as Orica BlastIQ and Deswik.Blast digitize sequence design and execution. AI optimization of timing from historical outcomes exists but is still emerging rather than standard practice.

What data does AI need for blast sequencing?

It needs the timing actually fired for each blast, linked to measured fragmentation and ore movement. Rock mass information adds context, because the best timing depends on the rock. Consistent records across many blasts are essential.

Do Orica BlastIQ and Deswik work together?

Yes. BlastIQ has documented API integration with Deswik.Ops. Teams can connect blast data into their wider planning and reporting systems rather than choosing one tool only.

Try It With Geocluster

Closing the optimization loop means connecting sequencing data to downstream fragmentation and dig-rate outcomes. That is a genuine applied-AI research project, not an out-of-the-box feature. The Geocluster Research Harness is built to help teams work through that kind of workflow. You can also read how the Geocluster Research Harness works.