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.
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.
रिफलेक्स
Evaluating Rock Comminution Pre-Blast to Post-Blast and Through Mineral Processing
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 रिफलेक्स 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 सोलो 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.
मुझे किस एज डिटेक्शन पैरामीटर्स (ईडीपी) का उपयोग करना चाहिए?
मल के ढेर का विश्लेषण करने के लिए WipFrag का उपयोग करते समय, आप निम्नलिखित दिशानिर्देशों का उपयोग कर सकते हैं:
जुर्माना = दाईं ओर स्लाइडर
माध्यम = बीच में स्लाइडर
बड़ा = बाईं ओर स्लाइडर
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
डेल्टा में, WipFrag सॉफ़्टवेयर का एक उन्नत संस्करण जो WipWare स्वचालित फोटोएनालिसिस सिस्टम पर चलता है, हम बेस्ट फ़िट EDP नामक एक प्रक्रिया का उपयोग करते हैं। ऑनलाइन सिस्टम के लिए, यह प्रक्रिया आमतौर पर इंस्टालेशन के समय ऑन-साइट की जाती है। एक बार सभी हार्डवेयर और सॉफ़्टवेयर सेटिंग्स पूरी हो जाने के बाद इसे विशिष्ट सामग्री की एक छवि लेकर कार्यान्वित किया जाता है। हम मैन्युअल रूप से अधिक से अधिक कणों का पता लगाते हैं और फिर सर्वश्रेष्ठ फ़िट ईडीपी सुविधा चलाते हैं। फिर सॉफ्टवेयर उपलब्ध ईडीपी सेटिंग्स का उपयोग करके कणों के मैनुअल ट्रेस का मिलान करने का प्रयास करेगा। बेस्ट फ़िट ईडीपी संख्यात्मक मानों का एक सेट आउटपुट करता है जिसे ईडीपी उन्नत नियंत्रणों में दर्ज किया जाएगा। यह विधि बहुत सटीक है और हमारे ऑनलाइन सिस्टम को उपयुक्त एज डिटेक्शन पैरामीटर प्रदान करती है। यह दुर्लभ है कि एक ऑनलाइन प्रणाली ईडीपी को बदलने की आवश्यकता होगी, लेकिन यदि ऐसा है तो हमारे मुख्यालय से दूर से किया जा सकता है।
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.
क्या आप फोटोएनालिसिस तकनीक में नए हैं? शायद आपके पास एक इंस्टॉलेशन है, और क्षमता में सुधार के लिए अन्य स्थानों की जांच करना चाहते हैं? WipWare के सबसे लोकप्रिय स्थानों में से कुछ के लिए पिछले कूद पर पढ़ें।
Where would be an ideal location to install your technologies?
There are 5 main locations where photoanalysis technologies are installed, all of which have a similar theme of analyzing material after it has been reduced in size. I’ve listed a few (of the many) popular locations, from the mine to the mill:
Blast Fragmentation
Unlike conveyor belt technologies, blast fragmentation systems are providing particle sizing data that would otherwise be unquantifiable. As an example: When mine team is asked how they were determining blast performance, they responded with: “Well, we try to compare it just by looking at it”. By putting quantifiable values beside the material being dumped into the primary crusher, we eliminate any bias and baseline the blasting performance.
Now, think for a second how much cheaper it would be, if you could do most of your material breaking in the blasting phase: Reduced crusher needs, less maintenance on equipment, and significantly reduced energy costs to name a few of the benefits of optimizing blasting procedures.
Post-primary/Post-secondary crusher
Either Jaw, Gyratory, or Cone, whatever type of crusher you use to break down your material, if it’s primary, secondary or tertiary crushing, you should be looking into evaluating the performance of those crushers, in order to a) maximize liner life, b) make crusher gap adjustments, c) change worn out liners before oversize contaminates your stockpile, d) improve overall crusher throughput.
See, most crusher maintenance schedules are based on a fixed timeline, when many variables can affect the lifetime of the liners. Think ore hardness, size, etc.
वास्तव में, पिछले ब्लॉग पोस्ट पर वापस जाकर, आप वास्तव में अधिकतम दक्षता के लिए अपनी प्रक्रिया के उस हिस्से को स्वचालित करना शुरू कर सकते हैं।
Screen Breakages
यदि आपको तत्काल स्क्रीन टूटना या संकेतक पहनने की आवश्यकता है, तो फोटोएनालिसिस प्रौद्योगिकियां स्क्रीनिंग के बाद बड़े आकार की सामग्री का पता लगा सकती हैं। उदाहरण के लिए, कुल निर्माता स्क्रीन विफलता की पहचान के तुरंत बाद आउट-ऑफ-स्पेक सामग्री की पहचान करने में महत्वपूर्ण मूल्य देखते हैं।
SAG Optimization
This is probably the location with the biggest potential return on investment, and is the most common first installation: Imagine controlling your stockpile blend based on continuous particle sizing information. Being able to optimize SAG feed can save an operation significant cost in a variety of areas.
जानिए कब भंडार के मोटे किनारों से, या बीच से खिलाना है।
What happens to your blast fragmentation when you have excessive inter-row distance (burden)?
Introduction – Excessive Burden
According to Prasad et al. (2017), rock fragmentation size is a very important parameter for an economical point of view in any surface mining. Excessive inter-row distance, often referred to as an increased burden in blasting operations, can occur due to poor drilling operation (human factor, machine factor).
Applying Chapman–Jouguet (CJ) Condition:
The CJ condition holds approximately in detonation waves in high explosives. It states that the detonation propagates at a velocity at which the reacting gases just reach sonic velocity as the reaction ceases. In such case, excessive burden affects explosive energy distribution by diminishing the efficiency of the explosive shock wave travel, which impacts the creation of micro-cracks.
CJ Plane Theory
According to the CJ plane theory, an optimal burden ensures effective shock wave propagation and micro-crack formation, crucial for breaking rock.
With excessive burden, energy dissipates before adequately fracturing the rock, leading to poor fragmentation. This inefficient energy transfer disrupts the detonation process, reducing the effectiveness of the blast and resulting in larger, unbroken rock pieces.
Burden Distance Affects Rock Fragmentation
This article makes use of data from Prasad et al. (2017) to explain further the effect of burden increments from 2.5 to 3m. As shown by the regression line, the analysis revealed that the blast fragmentation size (D50 and D95) increases with more than 50% positive correlation.
This shows that, the larger the burden distance, the bigger the rock fragment generated from the blast. Having excessive burden with the same powder factor will definitely affect the fragmentation size and shape. To account for how your current burden is affecting your fragmentation, you should first assess your borehole condition before charging.
Furthermore, assess your blast results using image analysis software. WipFrag software is the most highly recommended blast assessment software, with a long history in addition to the latest technological innovation. The software offers significant advantages in assessing mine burden effects on fragmentation. Using the app on mobile phones allows for convenient, on-site analysis.
Deep Learning Capabilities
Deep learning capabilities save analysis time by quickly processing images. The boulder detection tool identifies oversized fragments, while the specification envelope helps correlate blast results with downstream primary crusher performance, ensuring optimal fragment sizes for efficient crushing and improved overall operational efficiency.
Prasad, S., Choudhary, B. S., & Mishra, A. K. (2017, August). Effect of stemming to burden ratio and powder factor on blast induced rock fragmentation–a case study. In IOP conference series: materials science and engineering (Vol. 225, No. 1, p. 012191). IOP Publishing.
Excessive burden in blasting refers to having too much rock mass in front of the blast holes. This is relative to the designed blast parameters. The burden is the distance between a blast hole and the free face.
If this distance is too large, it can significantly impact the efficiency and effectiveness of the blasting operation. Here are some effects and consequences of excessive burden:
1. Incomplete Fragmentation:
When the blast design has too much burden distance between rows, the explosive energy may not be sufficient to break the rock effectively, leading to large, unbroken boulders or slabs.
2. Higher Vibration and Noise:
Relating ground vibration to this phenomenon, excessive burden can cause more energy to be transferred to the ground as vibrations, potentially causing damage to nearby structures and creating safety hazards (Blair & Armstrong, 2001).
On the other hand, inadequate burden can result in higher levels of air overpressure and noise, affecting the environment and nearby communities.
It’s worth noting that when there is excessive burden in blast design, the energy from the explosives is not used efficiently, leading to wasted explosive material and higher operational costs.
3. Flyrock Hazards:
Excessive burden can cause unpredictable flyrock, posing significant safety risks to workers and equipment.
4. Inefficient Loading and Hauling:
The resulting muckpile from an overburdened blast may have uneven fragmentation. This makes it harder to load and transport the material efficiently.
5. Incomplete Detonation and Misfires:
Excessive burden can cause incomplete detonation of explosives. This leads to misfires and the need for re-blasting, which adds to safety risks and costs.
Conclusion
In their paper for the 2nd World Conference on Explosives and Blasting Technique in 2003, Onederra and Esen stated that there is usually a discrete element of time that has elapsed from the time of explosive detonation to mass burden displacement. This time is designated as the minimum response time (Tmin) and is dependent on the burden mass, explosive and dynamic material response to the explosive stimulus. Generally, but not always, Tmin can be decreased by employing small burdens, using higher energetic explosives or a combination of both.
References
Blair, D. P., & Armstrong, L. W. (2001). The influence of burden on blast vibration. Fragblast, 5(1-2), 108-129.
Onederra, I., & Esen, S. (2003). Selection of inter-hole and inter-row timing for surface blasting—an approach based on burden relief analysis. In Proceedings of the 2nd world conference on explosives and blasting technique, Prague. Taylor & Francis (pp. 269-275).
Download WipFrag at https://wipware.com/get-wipfrag/. Assess your blasting results, spot regions with poor fragmentation and trace back to your drill and blast design.
हम आपकी पसंद और बार-बार आने-जाने को याद करके आपको सबसे अधिक प्रासंगिक अनुभव देने के लिए अपनी वेबसाइट पर कुकीज़ का उपयोग करते हैं। "स्वीकार करें" पर क्लिक करके, आप सभी कुकीज़ के उपयोग के लिए सहमति देते हैं।
वेबसाइट के माध्यम से नेविगेट करते समय यह वेबसाइट आपके अनुभव को बेहतर बनाने के लिए कुकीज़ का उपयोग करती है। इनमें से, आवश्यक के रूप में वर्गीकृत किए गए कुकीज़ आपके ब्राउज़र पर संग्रहीत किए जाते हैं क्योंकि वे वेबसाइट की बुनियादी कार्यक्षमता के काम के लिए आवश्यक हैं। हम तृतीय-पक्ष कुकीज़ का भी उपयोग करते हैं जो हमें विश्लेषण करने और समझने में मदद करते हैं कि आप इस वेबसाइट का उपयोग कैसे करते हैं। ये कुकीज़ केवल आपकी सहमति से आपके ब्राउज़र में संग्रहीत की जाएंगी। आपके पास इन कुकीज़ को ऑप्ट-आउट करने का विकल्प भी है। लेकिन इनमें से कुछ कुकीज़ का विरोध करने से आपका ब्राउज़िंग अनुभव प्रभावित हो सकता है।
वेबसाइट को ठीक से कार्य करने के लिए आवश्यक कुकीज़ बिल्कुल आवश्यक हैं। ये कुकीज़ बेसिक फंक्शंस और बेवसाइट की सुरक्षा सुविधाओं को सुनिश्चित करती हैं।
कुकी
समयांतराल
विवरण
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देखा गया
11 महीने
कुकी को GDPR कुकी सहमति प्लगइन द्वारा सेट किया गया है और इसका उपयोग स्टोर करने के लिए किया जाता है कि उपयोगकर्ता ने कुकीज़ के उपयोग के लिए सहमति दी है या नहीं। यह किसी भी व्यक्तिगत डेटा को संग्रहीत नहीं करता है।
फ़ंक्शनल कुकीज कुछ फ़ंक्शनलिटीज़ को परफॉर्म करने में मदद करती हैं, जैसे सोशल मीडिया प्लेटफॉर्म पर वेबसाइट का कंटेंट शेयर करना, फीडबैक इकट्ठा करना और थर्ड-पार्टी फीचर्स।
प्रदर्शन कुकीज़ का उपयोग वेबसाइट के प्रमुख प्रदर्शन सूचकांक को समझने और विश्लेषण करने के लिए किया जाता है जो आगंतुकों के लिए बेहतर उपयोगकर्ता अनुभव प्रदान करने में मदद करता है।
विश्लेषणात्मक कुकीज़ का उपयोग यह समझने के लिए किया जाता है कि आगंतुक वेबसाइट के साथ कैसे बातचीत करते हैं। ये कुकीज़ मेट्रिक्स पर आगंतुकों की संख्या, बाउंस दर, ट्रैफ़िक स्रोत आदि के बारे में जानकारी प्रदान करने में मदद करती हैं।
विज्ञापन कुकीज़ का उपयोग आगंतुकों को प्रासंगिक विज्ञापनों और विपणन अभियानों के लिए प्रदान करने के लिए किया जाता है। ये कुकीज़ वेबसाइटों पर आगंतुकों को ट्रैक करती हैं और अनुकूलित विज्ञापन प्रदान करने के लिए जानकारी एकत्र करती हैं।