Revolutionizing Mining Operations with Drones and AI

Table of Contents

1. Introduction
2. About Strayos
3. The Importance of Post Blast Analysis
4. Use Case 1: Fragmentation Analysis
   • What is Fragmentation Analysis?
   • Importance of Optimizing Fragmentation
   • Challenges in Traditional Methods
   • How Drones and AI have Improved Fragmentation Analysis
5. Use Case 2: Muck-Pile Shaping
   • Understanding Muck-Pile Shaping
   • The Benefits of Optimizing Muck-Pile Shape
   • Challenges in Manual Muck-Pile Shaping
   • How Drones and AI have Streamlined Muck-Pile Shaping
6. Use Case 3: Cost Optimization
   • The Role of Cost Optimization in Surface Mining
   • Key Metrics for Measuring Cost Optimization
   • The Challenges of Manual Cost Optimization
   • How Drones and AI have Enhanced Cost Optimization
7. Conclusion
8. FAQ
9. Resources

🚀 Introduction

Welcome to Strayos' webinar on "After the Blast: Measuring Blast Performance with AI". In this webinar, we will explore how new technologies like drones and artificial intelligence (AI) can be used to optimize blast performance in mining operations. Our team at Strayos, along with industry experts Brad Gyngell and Jon Lewis, will guide you through the process of post-blast analysis and showcase the benefits of implementing these technologies. We will cover key use cases such as fragmentation analysis, muck-pile shaping, and cost optimization. So let's dive in and discover how these innovative solutions can revolutionize the mining industry.

1️⃣ About Strayos

Before we delve into the specifics of post-blast analysis, let's take a moment to introduce Strayos. Strayos is a software company that specializes in visual AI software for mining optimization. Our suite of tools includes drilling and blasting optimization, AI-powered analysis, and photogrammetry engine. With a global presence in eight countries, Strayos has empowered over 550 mining sites worldwide, delivering significant savings and operational improvements for our customers. Our goal is to provide innovative solutions that optimize the entire mining value chain, from surveying to blasting to processing.

2️⃣ The Importance of Post Blast Analysis

Measuring and analyzing blast performance is crucial for mining operations to achieve optimal results. By conducting post-blast analysis, operators can identify areas for improvement, reduce costs, and increase overall efficiency. Traditionally, measuring blast performance has been challenging due to logistical and technical limitations. However, with advancements in technology, such as drones and AI, this process has become streamlined and more accessible. In the following sections, we will explore various use cases and demonstrate how these technologies can revolutionize post-blast analysis.

🎯 Use Case 1: Fragmentation Analysis

Fragmentation analysis plays a vital role in mining operations, as it directly impacts downstream processes such as crushing and milling. Achieving the right particle sizes can improve plant throughput, reduce equipment wear, and increase overall yield. Traditionally, fragmentation analysis required manual measurements and specialized expertise. However, with the advent of drones and AI, this process has become faster, safer, and more accurate.

What is Fragmentation Analysis? Fragmentation analysis refers to the measurement and characterization of rock fragments after a blast. It involves assessing the size distribution of the material, including the percentage of oversize and fines. By analyzing fragmentation, operators can optimize blast parameters, such as drilling patterns and explosive types, to achieve desired particle sizes for efficient downstream processing.

Importance of Optimizing Fragmentation Optimizing fragmentation is a balancing act. Coarse fragmentation can slow down the plant, increase wear, and require additional crushing. On the other hand, fine fragmentation can lead to increased energy consumption, equipment wear, and reduced overall yield. To find the optimal balance, operators need to match the requirements of the plant and continuously improve the fragmentation process.

Challenges in Traditional Methods Traditional fragmentation analysis methods were time-consuming, error-prone, and required specialized expertise. Manual measurements and analysis often led to inconsistencies and difficulties in correlating blast results with blast inputs. Moreover, the interruption of loading operations for manual measurements was not cost-effective.

How Drones and AI have Improved Fragmentation Analysis Drones and AI have revolutionized fragmentation analysis by streamlining the entire process. Drones equipped with cameras can capture high-resolution images of the blast area within minutes, without interrupting operations. These images are then processed using AI algorithms to automatically detect and analyze fragmentation parameters such as cast percentage and particle sizes. The result is a faster, more accurate, and cost-effective way of optimizing fragmentation in mining operations.

By leveraging these advanced technologies, mining operators can achieve significant cost savings, improve production rates, and enhance overall efficiency.

🏗️ Use Case 2: Muck-Pile Shaping

Muck-pile shaping is another critical aspect of mining operations that can benefit from the integration of drones and AI technologies. Optimizing the shape and Height of muck-piles can have a significant impact on equipment productivity, fuel consumption, and overall production capacity. Traditionally, manual measurements and calculations were required to assess muck-pile shape, resulting in time-consuming processes and potential safety hazards. However, with the introduction of drones and AI, muck-pile shaping has become more streamlined and efficient.

Understanding Muck-Pile Shaping Muck-pile shaping refers to adjusting the shape and height of the blasted material after a blast to optimize equipment productivity. Different types of loading equipment, such as loaders and excavators, have specific optimal muck-pile shapes that minimize movement and maximize digging efficiency.

The Benefits of Optimizing Muck-Pile Shape Optimizing muck-pile shape can lead to increased production rates, reduced re-handling, and improved equipment efficiency. By aligning the muck-pile shape with the requirements of each specific loading equipment, operators can minimize movement, reduce energy consumption, and enhance overall productivity at the loading stage of the value chain.

Challenges in Manual Muck-Pile Shaping Manual muck-pile shaping involved time-consuming measurements, potential safety risks, and expert knowledge in CAD software for analysis. This process was not only labor-intensive but also restricted the ability to quickly adjust muck-pile parameters and predict the outcomes of design changes.

How Drones and AI have Streamlined Muck-Pile Shaping Drones equipped with cameras and geo-referencing capabilities have revolutionized muck-pile shaping. After a blast, drones can capture images of the muck-pile from a safe location, without interrupting loading operations. These images, along with AI-powered algorithms, can automatically detect muck-pile boundaries, calculate volumes, and generate 3D models. Operators can then make data-driven decisions to adjust blast parameters, predict muck-pile shapes, and optimize loading equipment productivity.

The integration of drones and AI technologies has made muck-pile shaping more accurate, efficient, and cost-effective, enabling mining operators to achieve significant improvements in their production processes.

💰 Use Case 3: Cost Optimization

Cost optimization is a key objective for mining operations, and blast performance plays a critical role in achieving this goal. By focusing on optimization strategies, such as reducing re-handle and maximizing cast to final position, mining operators can reduce costs, increase production capacity, and improve overall efficiency. Traditionally, manual calculations and analysis were required to assess cost optimization metrics, resulting in time-consuming processes and potential errors. However, the combination of drones and AI has transformed cost optimization in mining.

The Role of Cost Optimization in Surface Mining Surface mining operations rely heavily on cost optimization to achieve profitability. Maximizing cast to final position and reducing re-handle can significantly reduce fuel consumption, equipment wear, and production downtime. Therefore, accurately measuring and analyzing these metrics is crucial for identifying areas of improvement and achieving cost savings.

Key Metrics for Measuring Cost Optimization Two key metrics for measuring cost optimization in surface mining are cast percentage and center of mass movement. Cast percentage represents the proportion of material thrown to its final position, reducing the need for re-handle. Center of mass movement indicates how far the centroid of the shot has moved, providing insights into the effectiveness of blast design and material displacement.

The Challenges of Manual Cost Optimization Manual cost optimization processes involved time-consuming measurements, complex calculations, and analysis using tools like AutoCAD. These processes were labor-intensive, prone to human error, and required specialized expertise to generate accurate results. Additionally, the lack of automated systems made it challenging to correlate blast results with blast inputs and identify the key variables influencing cost optimization.

How Drones and AI Have Enhanced Cost Optimization Drones equipped with cameras and AI-powered analysis tools have revolutionized cost optimization in surface mining. By flying drones before and after blasts, operators can quickly capture images of the mining area and generate accurate 3D models. AI algorithms can automatically analyze these models, calculate key metrics like cast percentage and center of mass movement, and provide real-time insights for decision-making. The automation of these processes reduces human error, saves time, and allows for continuous improvement in blast design and cost optimization.

By leveraging the power of drones and AI, mining operators can achieve significant cost savings, improve production rates, and optimize their overall operations.