Mining Experience/Knowledge: Giant Miner

10/05/2026

One Workflow. Multiple Ways to Work.
With WipFrag 4, your fragmentation analysis fits your workflow.
Capture and analyze on-site using your mobile device, or
Capture and complete the analysis on your Windows PC.
Whether you’re in the field or back at your workstation, WipFrag 4 gives you the flexibility to work where and how you need.
Capture. Analyze. Collaborate. Anywhere.
Watch the video to see how the WipFrag 4 workflow works.
Download WipFrag 4 here, create an account and learn on the demo images for free: https://wipware.com/get-wipfrag/

09/30/2026

Getting Good WipFrag Results

Good results begin with good image acquisition. Images should be clear, properly scaled, and representative of the material being measured.

Before capturing an image, ask yourself:

1. Can I clearly see the particles I need to measure?
2. Does this image represent the material I am measuring?
3. Am I using the correct scaling method?
4. Have I captured enough images to represent the variability of the sample?

For large or variable samples, capture multiple representative images rather than relying on a single photograph. Good fragmentation analysis starts with good sampling and image acquisition.

Become an expert in fragmentation image acquisition. Learn from our knowledge base and discover best practices for capturing and sampling images for WipFrag:

Read WipFrag Image Capture and Sampling Guide https://wipware.com/kb/wipfrag-image-capture-and-sampling-guide/

09/27/2026

Bench Blasting

07/22/2026

Fragmentation Analysis Software | WipFrag by WipWare

Why WipFrag is the Industry Standard for Rock Fragmentation Measurement
In modern mining and quarrying operations, accurate rock fragmentation analysis is essential for improving blast performance, optimizing downstream comminution, and reducing operational costs. Selecting the right fragmentation analysis software enables engineers to make data-driven decisions that increase productivity while minimizing energy consumption.
WipFrag, developed by WipWare Inc., is one of the world's leading image-based fragmentation analysis software solutions. Trusted by mines, quarries, universities, and research institutions across the globe, WipFrag transforms photographs into accurate particle size distribution (PSD) data within minutes.
What is Fragmentation Analysis Software?
Fragmentation analysis software is used to measure the size distribution of blasted rock using digital images instead of traditional sieve analysis. The software automatically identifies individual rock fragments and calculates particle size distribution statistics such as:
• X20, X50, X80, and X95
• Maximum particle size (Xmax)
• Characteristic size (Xc)
• Uniformity Index (n)
• Percent passing curves
• Particle size histograms
These measurements help engineers evaluate blast performance and optimize drilling, explosive loading, and crusher feed.
Why Choose WipFrag?
WipFrag combines advanced image processing, artificial intelligence, and decades of mining expertise into a single platform.
Key capabilities include:
• Automatic rock edge detection using deep learning
• Image analysis from smartphones, tablets, and digital cameras
• Drone orthomosaic fragmentation analysis
• Real-time conveyor belt fragmentation analysis
• Vehicle bucket fragmentation measurement
• Automatic scale detection
• PSD curve generation
• Swebrec and Rosin–Rammler curve fitting
• Blast-to-crusher performance evaluation
• Heat map visualization for fragmentation variability
• Cloud processing with image credits
• Windows, Android, and iOS support
Applications
WipFrag is widely used throughout the mining value chain, including:
• Surface mining
• Underground mining
• Aggregate quarries
• Construction blasting
• Tunnel excavation
• Research laboratories
• University teaching
Beyond Fragmentation Analysis
Unlike many fragmentation software packages, WipFrag also provides tools for rock mass characterization, including:
• Joint mapping
• In-situ block size analysis
• Rock Quality Designation (RQD) estimation
• Bench face structural analysis
These capabilities help engineers better understand the relationship between geological structures and blast fragmentation.
Benefits of Using WipFrag
Organizations using WipFrag can achieve:
• Improved blast optimization
• Better crusher feed consistency
• Reduced secondary breaking
• Lower energy consumption during crushing and grinding
• Improved mill throughput
• Reduced operating costs
• Faster decision-making through automated analysis
• Consistent and repeatable fragmentation measurements
Supporting Mine-to-Mill Optimization
Fragmentation directly affects every stage of the mining process, from loading and hauling to crushing, grinding, and recovery. By providing accurate and repeatable fragmentation measurements, WipFrag enables engineers to optimize the entire mine-to-mill process rather than focusing solely on blasting.
Why Mining Professionals Choose WipFrag
For over three decades, WipFrag has been trusted by mining companies, consultants, researchers, and universities worldwide. Continuous innovation, including AI-powered edge detection, drone orthomosaic analysis, cloud processing, and advanced geological characterization, makes WipFrag one of the most comprehensive fragmentation analysis software solutions available today.
Whether you are evaluating blast performance, monitoring crusher feed, or optimizing your mine-to-mill strategy, WipFrag delivers the accurate fragmentation data needed to improve operational performance.

07/20/2026

The Importance of Analysing In-Situ Block Size of a Bench Face
Written by Blessing Taiwo

Understanding the in-situ block size of a bench face is essential for better rock mass characterization, blast design, and downstream processing optimization. The natural fracture network of a rock mass directly influences blast performance, fragmentation outcomes, and comminution efficiency.

In-situ block size analysis provides valuable information for several mining applications, including:

Rock Mass Rating (RMR) and Geotechnical Characterization:
Measuring joint spacing, block size, and fracture conditions helps engineers better understand rock mass behaviour and stability.

Blast Modelling and Fragmentation Prediction:
In-situ block size is a critical input for fragmentation models. For example, advanced models such as Swebrec use in-situ block size as a reference parameter to improve fragmentation prediction, including estimating maximum fragment size (Xmax), rather than relying only on traditional burden or spacing (B,S) relationships.

Comminution Optimization:
The natural block size of the rock influences crushing and grinding energy requirements. Understanding the pre-existing fracture structure helps optimize blasting optimization.

WipFrag has expanded its capability beyond traditional post-blast fragmentation analysis by introducing Joint and In-Situ Block Analysis. The technology enables users to analyze bench faces, measure joint characteristics, estimate block size, and calculate Rock Quality Designation (RQD).

The analysis can be performed using both mobile devices and Windows PC platforms. Users can simply capture an image of the rock face without scale using the WipFrag mobile application or utilize the new EDM scale integration for auto scaling.

By connecting geological characterization with blasting and processing performance, WipFrag provides a complete solution for understanding the rock mass, from the natural structure of the bench face to the final fragmentation result.

From Rock Mass to Fragmentation Performance, WipFrag helps bridge geology, blasting, and comminution.

07/13/2026

How Fragmentation affect mining production.

07/13/2026

06/27/2026

Reviewing the Journey of the First Online Automated Fragmentation Analysis Technology – Part 4

The Global Race for Automated Fragmentation Analysis in the 1980s

In this part of the review series, I will look back at the remarkable wave of innovation that emerged during the 1980s as researchers around the world pursued automated image-based rock fragmentation measurement. Drawing from the work of Dr. John Franklin and Dr. T. Kemeny & Girdner (1996), published in Measurement of Blast Fragmentation by John Franklin and Takis Katsabanis, this review highlights the pioneering technologies that shaped the industry.

Canada – The Birthplace of WipFrag

Before 1985, researchers at the University of Waterloo had developed the Waterloo Image Enhancement Program (WIEP). Following significant advances in edge detection algorithms for underground mining applications, supported by research funding from INCO, the WIEP system was commercialized as WipFrag by Maerz, Franklin, and Palangio of WipWare Inc.

Unlike many research prototypes, WipFrag became a commercial system that has continuously evolved. It was early shown to be versatile, applying not only to rock fragmentation but also to materials like ammonium nitrate prills, glass beads, and zinc concentrate.

Other Canadian organizations also advanced image-based fragmentation analysis. CANMET's Experimental Mine in Val-d'Or, Quebec, developed a video-based image analysis system using a 386 microcomputer and commercial image processing software. McGill University's method was based on an earlier version of the Waterloo Image Enhancement Program (WIEP), while ICI Canada developed a system to support its ICI SABREX blast design model.

Sweden

Researchers at Luleå University of Technology developed one of the earliest automated fragmentation analysis systems, combining a TV camera, microcomputer, and image analysis to measure rock fragment sizes. This work later evolved into the IPACS project.

France

France introduced the FRAGSCAN project in 1983, developed by the Laboratoire des Ponts et Chaussées. Unlike edge-detection methods, FRAGSCAN estimated particle size using repeated image erosion and dilation operations to simulate sieving.

Germany

Researchers Vogt and Assbrock at the Technical University of Clausthal developed TUCIPS, an automated image processing system for production blast fragmentation.

United States

The University of Arizona developed the Split software, built on the public-domain NIH Image platform using high-resolution digital imaging. Other U.S. research included the Computer Image Analysis System (CIAS), investigated by the U.S. Bureau of Mines and NORAMCO Minnesota during the late 1980s and early 1990s.

What set WipWare apart was its successful transition from university research into a commercial technology that has continued to innovate for nearly 40 years.

Video showing WipWare system deployment at the early stage.

06/25/2026

Reviewing the Journey of the First Online Automated Fragmentation Analysis Technology – Part 3

What Could the 1986-2000 Version of the WipWare Inc. Online Fragmentation System Do?
Considering the available technology of the late 1990s, the system successfully met the mining industry's operational requirements by providing continuous, objective fragmentation data that improved process control and production efficiency.
The mining industry has always maintained a high threshold for adopting new technologies. Before deployment at operating mines, technologies must demonstrate both academic credibility and proven industrial performance. By 1999, WipWare's online fragmentation analysis system had successfully passed these requirements through extensive research and real-world validation.
Some Early Industrial Applications
1. Material Service Quarry – Chicago, USA
In one o Dr Norbert's investigation, a minus 5/8-inch crusher run product was measured in three different locations (stockpile, moving conveyor belt and material discharged from the end of the conveyor).
The resulting size distributions from each measurement location closely matched one another and agreed with the product specification, demonstrating that the online system could deliver consistent and reliable measurements under varying operating conditions.
2. INCO Underground Operations – Copper Cliff, Ontario, Canada
INCO deployed online time-lapse video photography at underground drawpoints to continuously characterize ore fragmentation.
Images were transmitted to the surface using broadband coaxial cable, fibre-optic communication, or wireless transmission, allowing operators to monitor fragmentation remotely and support production decisions without interrupting mining operations.
3. Highland Valley Copper – Logan Lake, British Columbia, Canada
One of the most significant early implementations was at Highland Valley Copper, where online fragmentation monitoring was integrated with ore hardness tracking to predict the performance of Semi-Autogenous Grinding (SAG) mills.
Even with the capabilities available in 1998, the operation reported more than10% increase in mill productivity by controlling mill feed based on both ore size and hardness.
Brunswick Mining, Bathurst, New Brunswick, Canada, where it was used to optimize feed size for a new autogenous grinding mill and maximize productivity.
Brunswick Smelting Division, Belledune, New Brunswick, Canada, where the system monitored and optimized return sinter size and uniformity to improve blast furnace performance.
These early deployments demonstrated that online fragmentation analysis was not limited to crushing operations but could also improve efficiency throughout the mining and mineral processing value chain.
Part 4 will cover some academic review of the first Fragmentation online system as at 1990s.

06/24/2026

Reviewing the Journey of the First Online Automated Fragmentation Analysis Technology – Part 2

In his presentation at FragBlast 6 in Johannesburg, South Africa, Dr. Norbert Maerz highlighted that the greatest advantage of an online fragmentation analysis system is its ability to generate measurement results in real time. At the time (1999), achieving real-time measurement, continuous output strip charts, and external communication represented major technological milestones.
This was long before the era of artificial intelligence and modern industrial connectivity. Delivering reliable, real-time analysis that met the demanding standards of the mining industry required significant innovation. Dr. Norbert Maerz, together with Dr. John Franklin and Dr. Tom Palangio, recognized that the true value of real-time measurement was not simply in producing data, but in enabling process control systems to act immediately on that information.
With timely fragmentation data, mining operations could adjust conveyor belt feed rates, optimize material blending, modify crusher settings, or even shut down equipment before large quantities of out-of-specification material were produced. This concept laid the foundation for today's closed-loop process optimization.
The 1999 generation of the WipWare online system supported several methods of external communication:
TTL I/O signals for triggering alarms when material fell outside specification.
4–20 mA current loop outputs to generate signals proportional to specified size passing values.
RS232 communication for transmitting digital data to process control computers.
RS422 and digital current loop communication for reliable long-distance data transmission.
These communication methods were successfully implemented across System 1, System 2, and subsequent generations of the technology.
Today, the latest generation, Solo 6, builds upon these pioneering developments by integrating real-time fragmentation analysis directly with plant control systems through Modbus TCP and OPC UA, enabling true closed-loop process control and automated optimization.
Video shows one of the old generation system deployment