Every operation has a specification they need their material size to be within: Whether it’s ASTM specifications for aggregate operations, key performance indicators for crushers and SAGs, or blast metrics for explosives selection, these standards are crucial in streamlining an operation’s process.

For example: an operation in northern Quebec, Canada (if you are looking at a map of Quebec, chances are you are still not looking north enough… keep going… there you go) needed to ensure material size did not exceed 6 inches in size coming out of the primary crusher, for a variety of reasons:

• A energia necessária a jusante para quebrar essas partículas grandes era significativa
• Problemas de manutenção em termos de danos causados por essas partículas de tamanho grande
• Getting maintenance personnel on-site to deal with the points was extremely costly

With the assistance of Xstrata Process Support (XPS) and a hydraulic toggle supplier, WipWare was able to not only identify when material was larger than 6″ but send signals to through a PLC that would automatically adjust the crusher mantle to bring the material size back in line. Just by reducing maintenance shutdowns to manually adjust the crusher setting, this operation was able to recoup the cost of the system within a year.

Even if your operation opts to manually adjust its process using WipWare’s systems as a guide, the benefits are widespread and significant. We’ve seen the timeline between liner replacements expanded drastically, and SAG feed optimized on-the-fly by utilizing online data as a standard.

…And for the folks who have dealt with paving specifications, all it takes is for a half mile of out-of-spec pavement to be pulled up to identify the importance of keeping material in between the goal posts.

Speaking more on the ground level of photoanalysis technology, envelopes can be created inside of WipFrag e Só, so operators can identify out-of-spec material briefly. Perhaps it’s a matter of notifying mining personnel, or shutting down a belt until liner maintenance is completed; regardless, having a tool that can help significantly in adhering to your operation’s standards can mean cost-savings, reduced downtime, and a more proactive approach to mining and milling.

Feliz esmagamento!

Estimated reading time: 4 minutos

WipWare has been in the image analysis business for over 30 years commercially. We’ve seen a wide range of mining and aggregate sites, all with their unique challenges. One thing that stays consistent with every operation is the need to reduce particle sizes to ideal sizes for either the extraction of minerals, or for more practical uses (road building, etc.)

Blasting, crushing and grinding material down to an optimal size is difficult to do. When you tie in trying to be efficient at the same time, production rates can fluctuate quite easily. It’s very hard to track how well the ‘rock breaking’ is going.

Peneiramento da fila!

A peneiração manual existe há milhares de anos. Hoje em dia, a precisão desses métodos de análise de peneira é bastante impressionante: pare a correia, faça um corte, leve o material para o laboratório, coloque no agitador de peneira e voila! Em poucas horas você tem seu resultado. O que poderia ser melhor?

Well, let’s back it up a little and investigate. Manual sieve samples are very accurate for the sample itself. However, if you use manual sampling to track, say, relative changes, you are putting a lot of faith in that one belt cut of material representing hundreds/thousands of tons of material.

Manual Sieving vs Continuous Monitoring

You may notice why WipWare systems are really taking a hold in the mining and aggregate industries: No one will ever argue that a manually sieving a sample is not accurate; but here is a scenario I want you to consider:

You take a sample of a 1-meter belt cut every shift for analysis. When the crusher supplier asks for the material size going into the secondary crusher, you hand him/her the beautiful distribution curves with the data points in the Excel file. Based on the data, he/she decides “based on your material size, you need this kind of crusher/liner/product”.

Do those manual samples accurately represent the hundreds or thousands of tons passing through your process? What if the sample you took happened to be finer than what was typical? Chances are, as granulometry guru Jack Eloranta, of Eloranta & Associates calculates, misrepresentation could be possible.

Take a look:

Presumir:

400 TPH

6 m / s

Amostra de correia de 1 metro por turno

A correia viaja 1 metro em 0,17 segundos

0,17 s x 1 h / 3600 s x 400 t / h = 0,019 toneladas

0,019 t / (8 x 400) t = 0,0000059

Really, when you look at how representative a manual sample is, you are looking at 0.00059% of your conveyor material in this example.

With a percentage like that, I’ll take continuous, non-disruptive particle sizing any day.

So let’s summarize so far: Manual sieving accurately measures the sampled material but may not represent the material continuously running through your process.

What’s WipWare’s role in all of this?

Well, it’s really a complementary thing. WipWare is the ying to sieving’s yang, the Sunny to sieving’s Cher…I’ll stop now.

WipWare’s systems offer continuous monitoring of material. That’s right. 24/7/365 analysis of the most important part of the mining process; the whole reason billions upon billions of dollars are spent each year; the reason why mine and mill employees have a love/hate relationship – the size of material! Manual sieve results can be tied into the WipWare data using Rosin-Rammler or Swebrec functions, covering both the quantity of data needed for accurate analysis, with the quality manual sample information.

WipWare’s systems offer continuous monitoring of material. That’s right. 24/7/365 analysis of the most important part of the mining process; the whole reason billions upon billions of dollars are spent each year; the reason why mine and mill employees have a love/hate relationship – the size of material! Manual sieve results can be tied into the WipWare data using Rosin-Rammler or Swebrec functions, covering both the quantity of data needed for accurate analysis, with the quality manual sample information.

Optimizing Blast Predictions with BlastCast in WipFrag

Predicting blast fragmentation is a complex process influenced by numerous variables and uncertainties. Achieving optimal fragmentation is essential for controlling costs and enhancing operational efficiency.

BlastCast, an advanced blast fragmentation prediction module integrated into Software WipFrag, provides a valuable tool for improving blast outcomes. Available as a free enhancement, BlastCast works alongside WipFrag data to help users forecast fragmentation and make necessary adjustments to achieve desired results.

How BlastCast Works

To begin, users input blast parameters, and BlastCast generates a predicted particle size distribution graph. After executing the blast, WipFrag measures the actual fragmentation. The results can be dragged into the BlastCast window, overlaying actual fragmentation over the predicted graph. By adjusting the Rock Factor slider, users can fine-tune the prediction model to align with real-world results.

Once calibrated, the model enables users to test different blast parameter adjustments, such as spacing or burden, to assess their impact on fragmentation. Over time, continued use of BlastCast enhances prediction accuracy, leading to better-controlled blasts.

Key Features & Parameters in BlastCast

• Size Class Settings: Matches WipFrag’s Output Options.
• Metric/Imperial Units: Allows users to select preferred measurement systems.
• Blast Values Checkbox: Locks the rock factor section to simulate the unknown rock condition using KCO model.
• Burden & Spacing: Determines borehole placement for efficient breakage.
• Drill Accuracy: Accounts for deviations in borehole alignment.
• Bench Height: Specifies the height of the face being blasted.
• Explosive Density & Strength: Pulls specifications from manufacturers to assess explosive performance.
• Rock Factor: The most challenging parameter to determine, considering multiple geological properties affecting blast results.

Why Use BlastCast?

By integrating BlastCast into your blasting workflow, you can fine-tune designs, optimize fragmentation, and improve cost efficiency. Whether adjusting spacing, burden, or explosive selection, BlastCast helps you make data-driven decisions for better blast outcomes.

Want to see BlastCast in action? Contate-Nos for a demo!

Fragmentation analysis is a critical driver of mine performance, profitability, and sustainability. Accurate measurement and control of rock fragmentation from drill and blast to crushing and milling directly influence throughput, energy consumption, equipment wear, and operating costs.

WipWare’s fragmentation analysis solutions use advanced image processing and AI-driven technologies to deliver high-quality, real-time particle size distribution (PSD) data. This enables mining operations to optimize processes across the entire value chain, from pit to plant, while maximizing life-of-mine value.

End-to-End Fragmentation Analysis: From Drill to Mill

WipWare provides a fully integrated fragmentation monitoring ecosystem, offering consistent, accurate PSD measurement at every stage of material handling. By connecting blasting performance with crushing and processing outcomes, operations gain unmatched visibility and control over their production system.

Online Conveyor Belt Fragmentation Measurement – Solo 6

Solo 6 delivers continuous, online particle size distribution analysis for conveyor belts across the comminution circuit, including:

• Primary crushers
• Secondary and tertiary crushers
• Pebble crushers
• Screen decks

With real-time fragmentation data at any conveyor belt location, Solo 6 allows operators to quickly detect changes in feed size, optimize crusher settings, and maintain consistent plant performance.

Real-Time Pit-to-Plant Fragmentation Control – Reflex 6

Reflex 6 measures the particle size distribution of post-blasted rock as it is delivered to the primary crusher, Bin and Stockpile. This real-time monitoring capability ensures effective management of the critical transition from pit to plant, reducing variability, minimizing crusher blockages, and improving overall throughput.

In-Pit Fragmentation Analysis – WipFrag 4

WipFrag is the standard industry solution for post-blast fragmentation analysis in open pit and underground mines. It enables engineers to accurately quantify particle size using:

• Mobile phones
• PCs
• Drones (UAVs)

WipFrag provides fast, reliable fragmentation assessments directly in the pit, supporting blast design validation, performance benchmarking, and continuous improvement.

Outsourced Fragmentation Analysis – MailFrag

MailFrag is a service that offers a simple and efficient solution for teams who like to get results with the help of WipWare in-house image processing specialists. By leveraging WipWare’s experienced analysts, MailFrag delivers professional fragmentation size distribution reports, allowing operations to focus on decision-making rather than data processing.

AI-Based Geotechnical Analysis – WipJoint

WipJoint, a powerful feature within WipFrag, extends value beyond fragmentation by applying AI imaging technologies to geotechnical analysis. It supports the identification and characterization of rock mass structures, joints, and discontinuities, contributing to safer blast design and improved rock mass understanding.

Blast Fragmentation Simulation – BlastCast (Swebrec Model)

BlastCast enables predictive fragmentation modeling using the Swebrec distribution, allowing engineers to simulate blast outcomes before execution. This supports:

• Optimization of blast design
• Reduction of oversize and fines
• Alignment of fragmentation with plant requirements

Simulation-driven planning leads to improved consistency, lower costs, and better downstream performance.

Why Fragmentation Analysis Is Critical to Mine Profitability

By integrating measurement, analysis, and simulation, WipWare’s fragmentation solutions transform raw images into actionable intelligence. This holistic approach improves safety, increases productivity, reduces energy consumption, and aligns pit-to-plant performance.

Fragmentation analysis doesn’t just measure rock; it drives smarter mining decisions across the entire life of mine.

The Need for Energy Efficiency Assessment in Blasting

In today’s mining and quarrying operations, energy efficiency remains one of the most pressing challenges. Blasting, being the first step in the comminution process, consumes a significant portion of total energy in mineral production. Yet, the true measure of blasting efficiency is not merely how rock is broken, but how well the resulting fragmentation supports downstream processes such as crushing and grinding.

A tool is therefore needed to assess and quantify the energy utilization in blasting, specifically through fragmentation analysis. By analyzing fragmented rock sizes in terms of percentage passing, engineers can evaluate how effectively a particular blast design converted explosive energy into rock breakage. Since controllable parameters such as burden, spacing, charge distribution, and initiation timing govern how explosive energy is distributed within the rock mass, understanding fragmentation helps determine how these parameters interact with uncontrollable factors like rock structure and discontinuities.

WipWare: The Global Ruler for Rock Size Assessment

WipWare Inc. is well known as the world leader in rock size measurement and fragmentation analysis. Known as the ruler for rock size assessment, WipWare provides innovative tools that quantify particle size distributions (PSD) from pre-blast through post-blast and into mineral processing stages, creating a continuous feedback loop for process optimization.

Pre-Blast Assessment with WipJoint

Understanding the geological conditions before blasting is crucial for predicting fragmentation outcomes. To bridge the gap between rock mass discontinuity and fragmentation potential, WipWare re-introduced WipJoint, a technology developed in 1990 by Dr. Norbert Maerz, Dr. John Franklin, and Dr. Tom Palangio.

WipJoint enables users to assess rock joint apparent spacing, apparent orientation, RQD and apparent in-situ block size from digital images of rock faces. This pre-blast information is invaluable for correlating structural conditions with post-blast fragmentation results. By analyzing joint characteristics, mining engineers can refine their blast design to ensure optimal energy distribution within the rock mass, thereby improving fragmentation and reducing energy waste in subsequent comminution stages.

Post-Blast Fragmentation Analysis with WipFrag

Once blasting is completed, WipFrag provides the most reliable and efficient means for evaluating fragmentation results. Using advanced image analysis, WipFrag calculates the particle size distribution (PSD) of fragmented rock piles and compares the results to target sizes such as the primary crusher’s gape.

This capability allows for quantitative comparison between different blast designs, helping to identify which parameters yield the best fragmentation for energy efficiency and crusher compatibility. With tools like specification envelopes and boulder detection, WipFrag makes it possible to assess whether the blast produced the desired material size and shape for downstream processes.

Material Assessment During Haulage with Reflex 6

Fragmentation control doesn’t stop at the muck pile. During haulage, WipWare’s Reflexo extends analysis to every truckload of material. Equipped with high-resolution cameras and an onboard computer, Reflex captures real-time images of material in transit, either while loaded on the truck or when being dumped at the crusher hopper or stockpile.

This technology enables continuous monitoring of material quality from each blast bench, providing operators with valuable data on fragmentation size, shape, uniformity and ore type variation. The Reflex system thus acts as vehicle load assessment platform, ensuring that no load goes unanalyzed.

Conveyor Belt Monitoring and Process Optimization with Solo 6

At the mineral processing stage, WipWare Só revolutionizes comminution monitoring. Installed over conveyor belts, Solo continuously analyzes the size distribution of material feeding the crusher or exiting as product. This intelligent system provides live feedback to operators, empowering them to make real-time decisions for process optimization.

Solo integrates seamlessly with existing process control systems such as Modbus TCP and OPC UA, allowing direct communication with plant control networks. This enables automatic crusher gap adjustment, SAG mill feed control, and load balancing, ensuring that the plant operates within optimal limits.

By maintaining consistent feed size and adjusting operational parameters accordingly, Solo helps minimize bearing pressure, reduce liner wear, improve throughput, and enhance overall energy efficiency throughout the comminution circuit.

WipWare technology provides a fully integrated suite of solutions that cover every stage of the comminution chain, from pre-blast geological assessment (WipJoint), through post-blast fragmentation evaluation (WipFrag), haulage assessment (Reflex), and processing control (Solo). By quantifying and connecting each step, WipWare enables mines to measure, monitor, and optimize energy use across the entire operation. The result is smarter blasting, improved crusher efficiency, and a more sustainable approach to mineral processing, achieving the ultimate goal of energy-efficient comminution.

Mine-to-Crusher Application of WipWare Solutions: Case Study at dstgroup Quarry

This study presents the third phase of a three-part research series focused on optimizing the interface between blasting and primary crushing operations at dstgroup aggregate quarry in Portugal, using WipWare solutions. The central goal is to improve fragmentation outcomes to better align particle size distribution (PSD) with crusher requirements, thereby reducing energy consumption and enhancing operational efficiency.

Building on the baseline methodology developed in Part 1, which incorporated 3D bench modeling and borehole surveys to assess blast compatibility with crusher specifications, the study identified discrepancies between predicted and actual fragmentation results. Part 2 applied targeted adjustments, such as reducing subdrill depth and altering stemming material, achieving measurable improvements in D80, maximum fragment size, and overall blast efficiency. However, boulder formation persisted in certain blast rows, prompting further optimization.

In this phase, the team implemented remaining recommendations, including refined drill and blast patterns, increased stemming size (from D80 12 mm to 21 mm) and length (from 1.8 m to 2 m), improved drilling accuracy, and adjusted inter-hole timing. High-resolution drone imagery and point-by-point blast surveys were integrated into O-PitSurface simulations to evaluate blast performance. WipFrag software was utilized for detailed particle size analysis, enabling comparison of fragmentation outcomes before and after design modifications.

Results demonstrated significant gains: D50 decreased by 19%, D80 and D95 by 20% and 23%, respectively, and maximum particle size reduced by 3%, indicating better control over oversized material. Fragmentation efficiency improved by over 21%, and the uniformity index increased by 16%, reflecting more consistent and predictable PSD. Adjustments to stemming material and length enhanced energy confinement, minimizing premature blowout and promoting even energy distribution throughout the blast column.

Run-of-mine monitoring with the Reflex system above the primary crusher provided real-time PSD analysis, confirming continuous improvement in fragmentation and crusher feed consistency. Over a six-month period, key size distribution metrics consistently trended downward, validating the effectiveness of iterative blast parameter adjustments and demonstrating the value of data-driven, integrated mine-to-crusher strategies.

In conclusion, the study illustrates how WipWare solutions, including WipFrag, Reflex, and O-PitSurface, enable quarry operations to optimize fragmentation, reduce oversize and fines, improve crusher compatibility, and enhance overall operational efficiency. The mine-to-crusher framework serves as a replicable model for energy-efficient, predictable, and high-performance blast-to-crusher integration.

Read Full paper here: Mine to Crusher Framework for Quarries

Quais parâmetros de detecção de borda (EDP) devo usar?

Ao usar WipFrag para analisar pilhas de sujeira, você pode usar as seguintes diretrizes:

Finos = controles deslizantes à direita

Médio = controles deslizantes no meio

Grande = controles deslizantes à esquerda

Generally, you want to have accurate nets on the small- to medium-sized particles. Once you find a suitable net for this size of material you can manually edit the larger material. Using this method will help provide more accurate results. 

It’s also recommended that you try to keep a similar EDP for images of the same muck pile, or when trying to compare different muck piles.

If finer adjustments are required, you can activate the ‘Show Advanced Controls’ checkbox to access numeric inputs featuring a wider range of finer adjustments than the basic sliders provide.

WipWare Automated Photoanalysis Systems and EDP

No Delta, uma versão avançada do software WipFrag que roda em sistemas de fotoanálise automatizados WipWare, usamos um processo denominado Best Fit EDP. Para sistemas online, esse processo geralmente é feito no local, no momento da instalação. Ele é implementado por meio da obtenção de uma imagem de um material típico, uma vez que todas as configurações de hardware e software tenham sido concluídas. Rastreamos manualmente o máximo de partículas possível e, em seguida, executamos o recurso Best Fit EDP. O software tentará então combinar o traço manual das partículas usando as configurações EDP disponíveis. O EDP de Melhor Ajuste emite um conjunto de valores numéricos que serão inseridos nos controles avançados do EDP. Este método é muito preciso e fornece aos nossos sistemas online Parâmetros de Detecção de Bordas adequados. É raro que um sistema online EDP precise de ser alterado, mas se isso pode ser feito à distância da nossa sede.

Best Fit EDP was recently added to WipFrag software. Because of the time involved in editing an image to produce a good Best Fit EDP, this feature is most practical to reduce the amount of manual editing required if you are going to be analyzing many images (20, 30 or more) of the same material under the same conditions. For most users, where smaller batches tend to be analyzed at once, using the sliders to adjust the EDP is faster.

Within WipFrag, there is also a feature called Auto EDP which attempts to determine the edge detection parameters automatically. This feature works well if the particle size range is narrow.

Read more about WipFrag: https://wipware.com/products/wipfrag-image-analysis-software/